AI in Education – A Realistic Look at the Effectiveness of AI in the Education Sector

A realistic view of the current adoption rate of AI in education, and pointers on how to ensure that it works, amidst the digital-learning hype.

When the kids in Montour school district (PA, USA) turned up to school that day in the fall of 2018, they were in for a surprise. They were told they would begin a brand-new course on Artificial Intelligence (AI). What on earth was AI? And what could it mean to kids in classes 5 and 6?

But this was a serious matter. MIT Media Lab and Media, Arts and Science Department at MIT, had come together and proposed to ‘catch them young’. The idea was to make an early introduction to concepts and practical AI lessons for middle school kids. All students from classes 5 to 8 would go through the AI Ethics program to identify use cases of gender / racial biases, privacy, and fairness. By the end of the 3-day course, they would know if such biases were embedded into the programs they would work on.

Welcome to generation AI. This makes millennium kids look antiquated. This new breed is sensitized to the good of AI and is aware of where it could go wrong. 

That is not all. Montour School district STEM teacher has co-developed a six-week program with Carnegie Mellon Dept of Computer Science called AI in Autonomous Robotics for 7 and 8-grade students. The implementation rigor here is quality stuff as kids are asked to solve real-world problems. 

Amper Music, the world’s first AI music composer and producer, has worked with music faculty at the school to develop a 10-day AI Music program for class 7 and 8 students. This school district is certainly leading the AI drive firing on all cylinders.

A host of universities, AI software firms, educators, and AI experts are coming together like never before to create early engagement for school kids into the AI world. And unlike what most of us would have thought: It is not only about STEM. In fact, the philosophy is to move from STEM to STEAM (with a liberal dose of Art – music, media, entertainment) thrown in for good measure. And this is happening in several pockets across the US.

AI in education sector – AI is here to stay, and the US campuses are already doing it

Across the United States, AI penetration within the education sector is tangible but may not be visible to the untrained eye. While varying in level of experimentation, schools and higher education institutes have embraced the tech and decided to learn how to harness its powers. 

Pittsburg-based Carnegie Learning1 offers AI-based personalized math, applied sciences, and language programs for post-high school students to rediscover learning. The entire program is personalized and self-paced, giving a new approach to STEM learners post-K12 schooling. The results demonstrated in some school districts in Washington and Texas prove the program creates a positive impact.

Duolingo2 is an amazingly popular AI-based customized language learning tool that allows anyone to learn a language. This is based on machine-driven instructions optimized for students based on millions of similar learning sessions held earlier. And most of the learning is for free.

California-based Content Technologies3 is a pioneer in AI and has developed several advanced AI systems for education. The Cram 101 is an AI tool that converts any textbook fed to it into chapter-wise byte-sized summaries, true or false type questions, learning concepts in record time. The company has developed similar tools for different disciplines such as nursing education, high school, and so on.

Some of the interesting outcomes of the approach of starting them young came from a US scientist, Ms. Druga, who built Cognimates, an AI platform for building games and programming robots and training AI models. Cognimates was incubated in MIT Media Labs. 

In a three-year study, where kids were taught to program bots to play games such as Rock and Scissors and build gaming applications using AI. One of the most profound observations came from Druga: When the kids came out after a session and said – “the computer is smart, but I am smarter”.

This was a powerful endorsement of how a young student comes away with a high level of confidence in the programmability of the computer to do what she wants it to do. This clearly establishes the argument about why AI perhaps should be started early on in school.

Next steps in playing this right – How can AI be used in education?

In general, schools and Universities must do the following to stay abreast of the AI curve and help imbue its benefits within the communities.

1.   Create a qualified AI resource team within the institution so they can track AI developments in peer institutes, vendor implementations and research the use cases.

2. Understand own deployments, migration of data systems into the AI realm, define implementation road map and create necessary stakeholder education of the new systems that will come.

3.   Educational institutions should also work with boards, government agencies, and accreditation bodies to define a structured AI curriculum for higher courses. This may require an industry interface also. This combination will create a Special Interest Group -university-industry – regulator group that will work together in ensuring the best interests of all concerned.

4. Faculty training, student and parent education, and awareness programs in terms of how the implementation could affect them need to be made available. Privacy and security rights of all stakeholders are paramount and need to be protected. How the schools intend to ensure data protection as machines become more powerful and open to sharing, receiving data from remote tutors, servers dynamically need to be shared transparently.

The Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) launched the AI for K-12 Working Group (AI4K12) to define for artificial intelligence what students should know and be able to do.

There are several such movements developing effective programs to deploy at various levels. These can help institutes understand better where AI is headed and how to ride this new technology wave to harness its full benefits.

Start your AI journey with Trigent

AI could well be the elephant in the classroom but if it’s a friendly elephant that can help enrich your life, you wouldn’t complain, would you?

At Trigent, we provide intuitive and easy to use AI solutions that ensuring seamless adoption of the latest technology. With the AI-powered tools from Trigent, you will be able to accelerate your digital transformation initiative in your organization successfully.

Want to know more? Get in touch with us for a quick consultation.

 References

  1. https://www.carnegielearning.com/why-cl/success-stories/
  2. https://www.duolingo.com/info
  3. http://contenttechnologiesinc.com/

IoT Asset Management Solutions for the Media & Entertainment Industry

IoT adoption, coupled with cloud platforms and Big Data analysis, provides the Media and Entertainment industry a significant boost to utilizing their machine and human assets. IoT (Internet of things) refers to the ecosystem of connected smart devices and environmental sensors that track assets, machine or human, across locations. 

Without IoT, asset management solutions are limited by delays and errors in manual data collection, under-utilization of assets, poor maintenance and reporting. This loss translates to a lack of awareness of real-time consumer needs, poor utilization of assets, theft, and limited data to predict overall and personalized content consumption in the media and entertainment industry. 

The Media and Entertainment industry can now make better-informed decisions by harvesting the multiple facets of consumer data such as location, time of day, parallel activities tied to consumption, age group, and region. They can develop more detailed consumer profiles that enable them to target ads and personalize content accordingly, providing higher degrees of satisfaction.

IoT bridges the physical and digital world. In general, it enables Asset management through four layers-

  • Data acquisition
    1. Sensors help detect or measure parameters such as light, sound, temperature, humidity, pressure, biometrics, proximity, acceleration, and GPS.
    2. Smart devices act upon the sensor’s input or capture input by themselves –  smartphones, wearables, smart TVs, gaming consoles, and home automation devices.
  • Data consolidation – Gateways collect and consolidate data from sensors and smart devices and transfer them to cloud platforms using a higher bandwidth. They can communicate using multiple protocols such as cellular, Bluetooth, wi-fi, and Ethernet. They also serve as a security layer for the devices.
  • Data hooks  – IoT platform collects data from the gateways or devices, processes, or directly transfers it to applications on the cloud for further processing, analysis, and action. This ties it to cloud platforms and machine learning.
  • Data visibility – Dashboarding and reporting to understand and utilize the insights to predict the future needs of content.

The meteoric rise in connected devices provides a massive opportunity for the Media industry. Consumers get to control what to watch and when to watch it while the content providers gain rich insights into the consumer’s preferences. Some of the key areas where IoT has contributed to the industry in a big way along with overall asset management  –

  1. Immersive content 
  2. Personalized content 
  3. Targeted advertising 
  4. Asset Management

Unique streaming experiences with immersive content

Let’s take the example of the Entertainment industry in the gaming arena. Augmented reality with the aid of IoT devices such as smartphones, tablets, portable gaming consoles provides the highest form of immersive entertainment. AR integrates real-world elements with the virtual world by superimposing the virtual on the real. 

A classic example of the initial showcasing of the power of IoT and AR is Pokemon GO. The game incorporates the real world through maps and smartphones, with fictional characters across the globe. It caused a stir among all age groups making them run all around town trying to gather Pokemon characters. This was in 2016. 

Today a number of the big brands are building an entire ecosystem around AR, Virtual Reality (VR), and IoT for entertainment. There’s Facebook’s AR Glasses, Microsoft’s Kinect as a motion-sensing add-on for XBOX 360, Amazon AR player, AR Emojis using a phone’s camera by Snapchat, Disney, and more. 

Disney is coming up with some disruptive AR and IoT amalgamation to track and notify guests with helpful information on delays on rides or who the particular entertainment is for, depending on where they are in the park. In the future, Disney, given its resources, could well come up with smart devices for some fantastic AR gamification experiences within the park.

Back to the mainstream world of TV, Smart TVs, streaming by OTT providers, and OTT platforms have revolutionized content watching from watching on a specific day at a particular time when the show is aired to binge-watching an entire series. Chrome casting is another new feature that enables you to watch uninterruptedly across devices, from your phone to your TV, be it the latest TED talks or the latest music trend on youtube.

The future holds unique streaming experiences with immersive live events using IoT devices, VR headsets, AR glasses, and more to huge segmented crowds.

Personalized content with user persona and viewer data

With the increasing number of smart devices, content is largely digital and not limited to viewing or listening at home.  You could be on a walk, cycling with friends, exercising, driving your car back home. For instance, based on your location or activity, the music platform you listen to could provide you with upbeat, soothing, or party music. Wearable devices, mobile phones, tablets, and social media data that can be picked from a household pretty much provide a detailed map of the family’s composition, their preferences and needs, their friend circle, and more. 

OTT providers such as Netflix already create multiple user profiles to engage with a family and not just an individual. Based on what you watch, what ratings you provide, through AI, they can figure out what kind of content you would like in the future and what kind of content demographic you fall under. Content is personalized to the level of an individual in a family using the personas and viewer data. 

Taking the social angle from the Facebook gaming world, Netflix came up with Teleparty to stream movies in sync with friends, each using their account and chatting. This was a big hit since group activities were not possible during the pandemic. This social data is something that Netflix, Disney, and others can use further to investigate group dynamics concerning content and advertising.

Targeted advertising with tailored campaigns

Earlier televisions would show ads to everyone without really knowing whether they were able to reach the target audience. There was no way of filtering it out for whom it was not relevant. 

Today thanks to digitally available content and OTT, Media and Entertainment companies can track consumers across devices. 

Consuming content on devices such as smartphones, tablets, wearables, etc., also aids in providing additional information on users in terms of location, time of day, whether they are moving, exercising, or are stationary. Through the multiple connected devices in a home, we can paint a picture of the family, which helps in targeting ads based on their specific needs.

Based on the data captured through wearables and other smart devices, we can now glean metrics on how many people saw a particular ad across devices and how many converted. Further, such detailed user information helps to tailor impactful campaigns and offers for highly effective revenue generation.

Nuances of IoT asset management solutions

Asset Management, in general, comprises of:

  1. Tracking moving assets – In the case of the Media and Entertainment industry, it could be electronic bracelets used by customers in an adventure park to guide them and give them a richer experience.
  2. Monitoring – Monitoring the health of an asset such as a setup box, checking if it’s connected to wi-fi, whether it has a technical error, and racking the usage.
  3. Workflow Automation – Use a voice-activated assistant to switch on/off an asset, decrease or increase the volume of a music system or TV, cast what you are watching on the phone to a TV.
  4. Maintenance – Based on the tracking and monitoring of assets, predictive maintenance. Detect technical faults in the asset using IoT devices such as a Home assistant and then proactively notifying the customer for maintenance.
  5. Security – At the company’s end, the digital assets need to be secured with authentication and role-based authorization to access, collaborate and add content. At the end-consumer end, assets need to be secure to prevent hacking into sensitive personal information.

Using IoT, Mobile, Chatbot, and Artificial Intelligence (AI), Entertainment companies can provide the best customer service. This is very evident at the end customer level. For example, when they choose a TV provider, and a setup box is delivered to them. Earlier, the provider needed to send a person to set it up completely. Today, with the aid of a chatbot on their website or mobile app, a customer can follow the steps to do so. Besides, the setup box is intelligent enough to figure out whether there is network connectivity or not and notify the viewer. 

Similarly, when there is a technical issue or a bill is not paid, the provider can send messages to be viewed either on the home screen of the TV or the customer’s mobile app or phone. Even if the customer faces a technical issue, she can get onto the app and start the diagnostics with the chatbot guiding her. This saves valuable time for the customer support team, which can then focus on more significant problems. It can also help have a smaller, highly skilled support team as the smart devices are connected and work things out with minimal human intervention.

Digital Home Service (DHS) is a cloud-based Oracle solution for set-top-box and service-intensive pay-TV operators. It combines Oracle IoT, mobile, chatbot, AI, and Oracle cloud platform with modern digital customer management to deliver the next generation of digital home service capabilities. This helps to reduce the effort and improve the efficiency of customer service and field services teams.

Today’s world of Smart TVs, gaming consoles, music systems, lighting, Air conditioning are IoT-enabled and interact easily with voice-activated Smart Home devices such as Alexa,  Google Assistant, Roomie Remote. Switching on/off, increasing or decreasing volumes, searching for content or information, playing music, and more can be done by using just one assistant that communicates with and manages all our smart devices. 

Content security is another critical facet to be considered. Data and devices surround everyone, including children. There are many ways to bring in parental control both on devices and platforms to ensure that children see age-appropriate content. Each IoT device and asset collects data, be it your security camera, fridge, or Amazon Echo. This makes them potential threats to privacy and overall security from cybercriminals. 

They can hack into your devices, monitor your activities, steal data both digital and physical, depending on how you have addressed your home’s security. Therefore securing the IoT environment at home is essential. We are slowly moving towards biometric security instead of using not-so-secure and multiple passwords.

IoT Asset Management solutions, therefore, bring endless possibilities to take Media and Entertainment to unimaginable heights. It serves as a powerful predictive monitoring tool that helps with asset maintenance and gives deep insights into the end consumer. Every day there are newer and better IoT devices in the market. A Media and Entertainment house would do well to invest in an intelligent IoT framework early on. We at Trigent can help you reach your IoT asset management goals. 

Call us for a quick consultation.

(Originally published in ReadWrite )

AI in Media: Redefining Customer Experience with Immersive Stories

Artificial intelligence has become an important milestone in the digital transformation journey of all sectors, including media and entertainment. With the buzz it has created, it is no surprise that the adoption of AI in media and entertainment is a game-changer for the pioneering and the digitally inclined. It plays an immense role in the way content and experiences are curated and delivered at scale today. 

The next era of the Media industry is defined by customers’ increased demand for immersive, live, and shareable experiences. Consumers now wish to get more engaged, better connected, and closer with the stories they love – both in the digital and physical worlds. Companies have started empowering these experiences through emerging technologies. Big data and artificial intelligence will create the most dramatic change, redefining how the industry can connect with all stakeholders and drive growth.

Modern enterprises are now deploying AI tools and technologies to ensure effective decision-making and agile responsiveness to market changes. While over-the-top players like Netflix have already adopted a data-first approach, many others are still trying to attain AI success. The road to full-fledged AI adoption is not devoid of challenges. AI can be only as good as the data you have. Every effort must be made to efficiently manage different data types, including audience, operational, and content data.

As workflows and processes continue to become AI-enabled, we analyze the media and entertainment landscape to understand the impact of AI adoption.

Customization to optimization – the role of AI in media & entertainment sector

AI plays an important role in enhancing the user experience across all the six segments of the Media and Entertainment (M&E) industry: Films & TV, social media, journalism, gaming, music, and sports.  

Customer-focused experience with content personalization 

AI powers recommendation engines to predict what content should be promoted and when based on customer viewing data, search history, ratings, and even the device customers use. A classic case in point is Netflix’s landing cards1 helping the streaming website customize what you watch through personalized targeting. Images of lead characters are seen while scrolling to understand popular choices based on the cards people click. 

Machine classification algorithms for improved search optimization

AI also plays a significant role in search optimization thanks to machine classification algorithms that help in improving the categorization of movies. Users can search based on categories instead of individual titles to enable quick searches and smooth navigation. Streaming websites have enhanced streaming quality with AI since it helps them predict future demands and position their assets strategically to help users enjoy high-quality streaming even during peak hours.

Music streaming companies like Spotify and Apple Music rely on machine learning algorithms to segment users and songs to offer personalized recommendations and playlists. Natural Processing (NLP) gives them an edge by providing information about songs and artists from the web. AI has also been helping musicians generate lyrics and compose songs.

Enhanced news reporting with robot journalists

AI has a coveted place in social media and journalism too. While social media platforms like Facebook, Instagram, and Snapchat are using it to offer personalized products and services, Forbes and Bloomberg have been using robot journalists Bertie and Cyborg respectively to create storylines based on their parameters and data.

The Washington Post, too, gave us a taste of the future of journalism with its Heliograf2 that covered the Olympics. However, the Chinese news aggregation service Toutiao took it to the next level by creating an AI-enabled reporter Xiaomingbot that churned out a whopping 450 articles during the Rio Olympics in just 15 days.  

Gaming and customer-specific advertising

As the supply of mobile games continues to exceed demand, companies are now using AI to estimate customer lifetime value (CLV) to bid efficiently in advertising for users, focusing only on those who would enthusiastically engage with their products. AI is also helping animators bring exciting characters to life for a multitude of virtual reality games and movies.

 Improved entertainment quotient in sports broadcasting

The perennial popularization of sports brings new fans, players, and subscribers into the sports and gaming fold. AI satiates them with entertaining shots and angles during live telecasts and enhances the experience by broadcasting exclusive footage captured by drones.

Laying deeper data foundations for successful adoption of AI in media

AI has forayed into virtually all functions and areas to add value in a highly competitive market. As competitive pressures intensify, it has become more critical than ever to fast-track your AI initiatives and reap their benefits. But as with every other digitalization endeavor, AI adoption too brings along unique challenges.

Here’s what you can do to overcome them and lay deeper data foundations for successful AI adoption. 

Assess AI maturity 

M&E businesses are now shifting from B2B to B2C business models due to the direct-to-consumer delivery and consumption trends and hence are currently operating on massive amounts of data. In order to make complete sense of this data and drive decisions, data silos need to be removed first. A fragmented approach is not going to work and should be replaced with a data-first approach.

Organizations often get caught up in a quandary, wondering if they should modernize the data architecture first for their AI models to rest upon or build a model and modernize only that part of the required data. However, the right approach would be to invest in a sound strategy for your target data architecture that relies on proven models to avoid pitfalls and rework. Data management should be a top concern for organizations to interpret and get actionable insights.

Focus on people and processes 

Data sources will continue to increase, causing greater challenges for data management and project management. So while building your technology stack, it is equally important to invest in people and processes that would be at the helm of things while progressing up the AI maturity curve.

AI leaders believe in including technologists and data scientists in business teams to give them the visibility to understand business challenges. It is essential that business leaders, values, people, and culture are aligned to enable successful automation and AI adoption. Only then would human employees be able to work alongside robots and AI-powered machines to build capabilities and deliver value.

Adopt a continuous improvement approach

AI is not a one-time endeavor but will continue to evolve with time. To achieve enterprise-wide AI, it needs to be perceived as a transformational initiative that must be implemented across all front-end and back-end processes.

A comprehensive picture of ROI based on revenue and costs for different functions and processes can give organizations the clarity to track value and identify areas that need to improve. M&E companies are integrating established AI processes into finance, HR, and other functions to garner cost and operational efficiencies.

The future of entertainment looks AI-centric

AI is undeniably transforming the media and entertainment sector, empowering them to make informed decisions based on critical data analysis. It will navigate disruption and drive growth in all spheres by addressing data gaps and helping M&E companies become more agile. Clearly, AI is impacting everyday entertainment in a big way, and it’s time organizations harnessed its power to fine-tune their forward-thinking strategies and explore new avenues.

Discover the power of AI with Trigent

The technology experts at Trigent have been offering robust AI-enabled solutions to M&E companies based on data from diverse sources and powerful algorithms to enable a superlative user experience while giving them insights into customer behavior. 

We help build excellent AI capabilities and advanced features to deliver content in the most effective manner. We can help you build high-quality datasets to get the best results in diverse settings and drive impact at scale. 

Call us now for a business consultation

References

  1. https://www.wired.co.uk/article/netflix-data-personalisation-watching
  2. https://futurism.com/the-future-of-writing-chinas-ai-reporter-published-450-articles-during-rio-olympics 

5 Principles to Ensure Successful Implementation of AR/VR in Real Estate Firms

In a highly demanding buyers’ market, giving your clients what they need can be very challenging. Also, every client is different, and as they say – one man’s trash is another man’s treasure. A huge living room, for instance, maybe a waste of space for you but would be perfect for someone who loves to host parties. 

AR/VR in real estate presents the perfect solution to the changing needs of discerning customers. The global AR VR in the real estate market ecosystem1 is expected to grow at a CAGR of 31.2%, increasing in value from USD 298.6 million in 2018 to USD 1,151.9 million in 2023.

The pandemic has compelled realtors to change the way they work, and there is no going back. Real estate companies now look to implement perfect customization to help customers flip through properties like the pages of a magazine until they find exactly what they want. 

Virtual reality home tours are becoming a thing as customers visit their prospective homes through strategically placed 360° cameras. The footage acquired is put together to create a seamless, real-life, 3-D experience to give your customers the feeling of actually being there sizing up the space with exact dimensions. 

The virtual experience evokes strong emotions giving potential buyers the feel of owning the place. While this looks great from a customer experience perspective, we seek to gauge the impact of these disruptive technologies on the real estate landscape. And more importantly, to help you decide if it’s for you. 

Real estate needs digital transformation

The salability quotient of any property depends on its Days on Market or the DOM index. There are several factors that affect the DOM index significantly. These include the property’s condition, seasonal variability, buyer’s availability, seller’s lead time to allow in-person showing, competition, location, and price. 

While you may put in a lot of hard work in each area to improve the index, AR and VR can save you considerable time and money even in times of a potential downturn. With the help of a headset and a smartphone or a tablet, you can harness the benefits of these immersive technologies to sell properties in the residential and commercial segment.

Says Maty Paule, head of product at Commercial Real Estate2, “Real estate is all about location and appearances, while two emerging themes in AR are geo-location and image detection. The ability for users to access property data in their current location is a powerful proposition. In contrast, the possibility of modifying a property’s visual appearance to understand development or renovation potential is a game-changer.”

VR allows users to explore in a three-dimensional, computer-generated environment using headsets, and AR creates an enhanced version of reality. Here are our top 5 recommendations to get started.

1. Start small; start now.

Considering the number of tools available today, it is easier to develop content quickly. Start with AR and VR training use cases keeping the devices and tools you will require and how you are planning to source them. After the initial hiccups, you would be able to plan to scale and incorporate exciting ideas along the way to tailor the perfect experience for your customers.  

2. Keep it simple

A test-and-learn approach may be ideal as you can get your team involved in the project to get a taste of how the user experience will be. Starting with augmented reality would be a good idea to get a fair idea of how your digital journey will pan out. Most importantly, start now to be ready to handle intricacies and challenges with better capabilities going forward.

3. Prepare for change

 Every new technology will bring along a shift in the way you work. You need to figure out how AR and VR will change the experiences for your users and how they will impact your team and workforce. There will be a need for greater collaboration since everything will be managed virtually. You need to plan in advance to let change not impede your work. 

4. Assess your needs

You must have a very realistic assessment of your business needs to choose technologies accordingly. For instance, if your people are struggling to finish tasks, the right technologies will empower them with everything they need. AR will enable augmented learning while VR will let them explore, replace, and repair parts albeit in a virtual scenario, to understand and practice adequately before implementing the skill. You must also decide which tools would be required depending on the content you need to create.

5. Choose your people and skills

Your existing workforce may require upskilling, or you may need additional staff to manage new requirements and extend your capabilities. Address the skill gaps early on so that you don’t have to suffer any delays.

Benefits of AR/VR in real estate

AR and VR together give real estate solid value and benefits that make AR and VR investments worthwhile. 

Building on-demand capabilities with Virtual Tours

Those on the lookout for properties can be allowed to experience the property virtually from the comfort of their home, thanks to virtual tours. Guided visits can be shared through 360-degree videos for existing properties, while interactive visits allow users to focus on a specific area. Potential buyers can utilize VR capabilities on-demand to virtually access a property on the very same day. 

Leveraging VR for Virtual staging

As per a survey, 40% of buyers’ agents have confessed home staging affects buyers’ view of the home, while 17% of respondents revealed that property staging had increased the home’s dollar value between 6-10%.

Does that mean you blatantly hide all the flaws and mislead buyers? 

Rather than using virtual staging to hide ugly details, you can always be honest and give a more realistic picture. As Rick Davis, a real estate attorney from Kansas points out3, “Most sellers think it is in their best interest to disclose as little as possible. I completely disagree with this sentiment. In the vast majority of cases, disclosing the additional information, especially if it is something that was previously repaired, will not cause a buyer to back out or ask for a price reduction.”

The adoption of AR/VR in real estate has been helping realtors expand their portfolio the way they did in the case of Sotheby’s International Realty that has been growing by leaps and bounds with an ever-expanding suite of technology-driven tools. After leveraging VR to help their sales team sell homes globally without the buyer setting foot on the property, the company has partnered with Google and RoOomy for their AR offering ‘Curate’.

Visualizing full-scale models with virtual architecture

It is always difficult to get buyers interested in a property that is yet to be built. The virtual architecture allows customers to visualize the interiors and exteriors of the property with the help of full-scale models. This saves realtors time and money while generating a buzz around their property. A mere piece of land can be transformed into complete architecture to enable experiences in the early stages of design. AR comes in handy from the prototyping to the construction phase generating pop-up 3D models of projected structures.

Enhancing customer experience with virtual commerce

While the above principles give your buyers a chance to visualize and experience the property, virtual commerce goes a step further in ensuring that they get to make those tiny tweaks and experiment with the elements on their own. In other words, if they are on a virtual tour and want wooden flooring with an oak finish instead of the plain porcelain tiles that are currently being offered, they can go for an upgrade right away. This applies to all virtual staging objects such as curtains, light fixtures, and furniture by purchasing what they need from partnering hardware and upholstery providers.

They can even choose a property and then move on to other providers like IKEA to spruce up the space with everything they need. After helping customers digitally place furniture in their homes via Place App, IKEA has now come up with IKEA Studio, a much-needed overhaul of its predecessor. It lets you capture 3D room plans with accurate measurements, including ceilings, windows, and doorways, while taking into account the current arrangement of your furniture.

Houzz, a leading platform for home renovation and design, is also helping customers transform living spaces and even tile their floors virtually. The company had added visual tech to its mix not too long ago, starting with 2D stickers. The mobile team took product photos and offered them as stickers after removing the background. This enabled shoppers to view them in their rooms in the form of 2D stickers, and this straightforward strategy gave them a 3X boost in conversions. 

Several product cycles later, Houzz offered AR visualization to visualize products before shopping and saw an 11X boost in conversions.

Building practical solutions with virtual apps

AR/VR apps are convenient and a practical solution to showing the world exactly how a finished property looks like. They are intended to show how it would look in real environments. An app such as RealAR gives your customers the freedom to simply stand on a piece of land and get a good representation of how a property would look like using a smartphone or a tablet. It converts floor plans into walkthroughs that can be used onsite or remotely to understand room size and layouts and get a realistic picture of the property.

AR/VR in real estate is transforming the landscape

VR and AR technologies are changing the tide for realtors worldwide, helping them make stellar first impressions. VR/AR is just taking off now, and real estate firms are getting their feet wet. 

There is tremendous potential, and we are yet to experience the full benefits of these amazing technologies.

So if you are still wondering if you should invest in AR/VR for your real estate business, we’d say, “By all means, go for it!” You can save time scheduling in-person visits and unproductive viewings and create targeted, personalized experiences instead. What’s more, adopting AR/VR is fairly easy. All you need is an expert to help you transform digital engagement and experience one solution at a time.

Adopt AR/VR in your real estate firms with Trigent

Our decades of experience give us the skills to help realtors increase the effectiveness of their business in the residential as well as commercial sectors. We empower real-estate stakeholders with AR/VR solutions to connect with their customers and build trust. We can help you too.

Allow us to help you build a dynamic, detailed, and immersive experience that will not just reduce costs but give you a competitive edge in a relatively volatile market.

Call us today to book a business consultation. 

References

  1. https://www.alltheresearch.com/report/380/augmented-reality-ar-virtual-reality-vr-in-real-estate-market-ecosystem
  2. https://www.commercialrealestate.com.au/news/how-augmented-reality-could-revolutionise-the-way-we-search-for-commercial-real-estate-47597/
  3. https://www.realtor.com/advice/sell/questions-to-ask-before-selling-your-home/

Quick Wins in Enterprise Digital Transformation (yet often ignored) – Intelligent Automation

The modern workplace is seeing widespread usage of machines and automation. Enterprise digital transformation, Artificial intelligence (AI), and automation are changing the tide for businesses globally. This means a significant change in the work culture as employees will have to acquire new skills and adapt to the advanced capabilities of machines. 

As per a recent study1 involving over 600 business leaders from 13 countries, more than 50 percent of respondents confessed to having already invested over $10 Million in intelligent automation projects. The AI market globally is presently growing at a CAGR of 40%, all set to touch $26.4 Billion by 2023.

AI,  along with robotic process automation (RPA), voice recognition, natural language processing (NLP), and machine learning (ML), is allowing businesses to blend automation with human capabilities successfully to create intelligent working environments. 

Automation is driving agility for businesses giving them the much-needed competitive edge over others with quick decision-making powers. Clearly, decision velocity powered by AI-driven insights gives you data supremacy to lead in a highly volatile market.

Making a case for Intelligent Process Automation (IPA)

When automation meets artificial intelligence, you get intelligent process automation to scale up your business. While it allows you to off-load routine, repetitive tasks, it empowers better guardrails for all your automation initiatives. It takes the uncertainty out of the picture and enables more personalized execution and processes.

Intelligent automation enhances the overall customer experience. The speed of response has often been a critical consideration while evaluating the customer experience. Intelligent automation is helping organizations meet customer expectations with personalization. Through customized offers, services, and content, businesses are acquiring and retaining customers.

What do the right IPA endeavors ensure?

  • Agile services due to a significant reduction in processing time
  • Greater flexibility and scalability for being able to operate round the clock with capabilities to scale up and down as required
  • Improved quality control due to greater traceability of events and instances and checks at different levels
  • Increased savings and productivity due to a high level of automation
  • Clear, actionable insights to predict and improve drivers of performance

While there is unanimous agreement on the benefits of intelligent automation, not everyone has leveraged these benefits across the organization. What you need is an enterprise-wide approach that promotes a new way of working.

Adding intelligence to the digital mix

A highly automated world does not focus on reducing the headcount but increasing its potential to do more in an agile manner to solve the business challenges of tomorrow. It relies on structured and unstructured data the company collects from the public domain and other stakeholders rather than depending on traditional methods.

Intelligent automation compels you to rethink key business processes. The sales and marketing team gets deeper segmentation to target and sell through advanced analytics. Those working to strengthen the supply chain get to improve production and distribution by leveraging technologies like cloud and analytics across the value chain. Planning and development teams, on the other hand, rely on data-driven insights to integrate them into product performance and boost innovation.

Alibaba Group2 is a classic example of what you can achieve with intelligent automation.

After making significant strides in eCommerce and retail, it has further revolutionized its business processes with its ‘Industrial Vision AI‘ solution for manufacturing and production. It allows the company to inspect raw materials thoroughly to detect minute defects, resulting in a 5X increase in production efficiency. Its automated warehouse is managed entirely by robots taking precision and efficiency to a whole new level.

Regardless of your goal, you need to create a strategic roadmap to align it with your business priorities. This is not possible unless you assess your digital maturity.

What is the role of IT in successful IPA transformation?

Intelligent process automation (IPA) is a melting pot of technologies enabling significant gains for businesses worldwide. IPA should not be confused with robotic process automation (RPA) as unlike RPA that performs repetitive, automated tasks based on predefined rules and inputs, IPA can understand the context, learn, and iterate to support informed decision-making using unstructured and structured data.

Those who have been able to get the full value of IPA have been the ones who have put IT leaders at the helm of their IPA endeavors. CIOs need to strengthen their core with IPA programs to support automation.

Here’s what we recommend:

  1. Assess the high-level value potential

You may start with help-desk requests since that’s where a significant amount of incidents originate. While tickets with low difficulty levels are resolved immediately, those with more complexity are often escalated to specialized teams. Determine how many such requests were handled the previous year, and by multiplying them by the average handling time (AHT) required, you can evaluate the value of this whole exercise.

For instance, an organization with a significant number of requests for password reset or access can leverage RPA bots that work across multiple applications via the user interface to automate ticket resolution and free up employee capacity. Reducing resolution times and a drop in costs associated with outsourcing help-desk support will thus improve performance and profits.

The effort required for these activities often varies. Everything needs to be evaluated critically from backups and patching to security audits and upgrades to understand the effort involved and the value you can garner by planning activities for automation.

  1. Identify the use cases best suited for IPA

Let’s consider the same example mentioned above. In order to automate incidents, organizations need to first identify the ones ideal for automation. An organization may be effectively logging incidents in detail, but due to the large numbers and complexities, support teams may not respond quickly and effectively.

AI can make sense of the chaos and understand the reasons behind the alerts. It may be trained to make appropriate recommendations or even make better decisions to ensure suitable responses.

  1. Elevate customer experiences with better service

AI and automation are changing the customer service landscape for every industry, from retail to aviation. Boeing has a fleet of passenger service robots that operate via sensors installed in their bodies. They are doing their best to reduce the manual work of cabin crews. Though experts argue a human perspective is required for these robots to do what humans can.

The key is to understand the power of automation and integrate it seamlessly into processes and workflows to complement human efforts and endeavors perfectly, as we did in the case of one of our clients Surge Transportation.

The company links shippers and carriers and has an automated tracking and monitoring system to assign loads. But the pricing and quotation were being done manually. This drained their resources, led to a huge turnaround time, and left a long log of emails, calls, and paper trails.

Trigent critically evaluated the complexities in its pricing mechanism to bring down the turnaround time to less than a second. Apart from 100% pricing accuracy, the company improved profits by 25%, revenue by 40%, and reduced the load processing time by 91%. With seamless carrier integration, the company now processes 4000 more loads per day.

Other use cases where AI and Automation are driving value

Cashier-less stores

Amazon is popularizing the concept of cashier-less stores with Amazon Go and Just Walk Out. Robotization of stores helps save operational expenses and gives shoppers a smart shopping experience.

Automated medical appointment scheduling

No-shows have been the cause of losses of over $150 billion a year for the U.S. healthcare system with every unused time slot costing individual physicians $200 on an average. No-shows also impact the health of patients since continuity of care is interrupted. IPA challenges traditional scheduling methods by ensuring error-free appointment scheduling based on the nature of the illness, the convenience of patients, and the availability of doctors and healthcare facilities. While patients get to choose a date and time for different health issues, follow-up appointments can be scheduled automatically along with reminders.

Automated supply chains

The ideal supply chain is where there is neither wastage nor out-of-stock scenarios. In tandem with machine learning, AI predicts demand based on location, weather, trends, promotions, and other factors. Revenue losses of up to $4Trillion have been caused due to supply chain disruptions following the pandemic with 33% attributed to commodity pricing fluctuations as per a report.

The automobile giant Toyota is using AI in its manufacturing environment to address waste control with its ability to predict when excess parts, products, and practices threaten to impede work.

Intelligent Automation is clearly on a winning streak!

The potential value of AI and automation is immense for different sectors and will vary depending on the type of industry, availability of abundant and complex data, use cases, and other factors. To get the most out of your automation initiatives, it is however important to tide over organizational challenges with the right mindset and approach.

Create impact and value with Trigent

Trigent with its team of technology experts empowers you to stay relevant and competitive. It is equipped with insights and intelligent solutions to dramatically boost your bottom line and improve customer engagement.

Allow us to help you grow your business and increase revenue with strategies and solutions that are perfect for you.

Call us today for a business consultation

References
1. https://www.analyticsinsight.net/intelligent-automation-accelerating-speed-and-accuracy-in-business-operations/
2. https://datacentremagazine.com/technology-and-ai/alibaba-group-adopts-ai-and-automation-singles-day

AI Implementation Checklist – 5 Points to Evaluate Before Adopting AI in Your Organization

Artificial intelligence is now all around us in household gadgets as well as business workflows. AI adoption is rampant across sectors; the global artificial intelligence market is expected to reach $ 266.92 billion by 20271 at a CAGR of 33.2% during 2019-2027. Nearly half of the respondents who had participated in a survey confessed to being interested in AI implementation and machine learning to improve data quality.

No doubt, artificial intelligence is the proverbial genie that does everything we want it to do without even rubbing the magic lamp. But the lack of nuance and failure to spell out caveats can result in AI systems that will make us think twice before we wish for anything.

Believe it or not, misaligned AI can be a nightmare.

A classic case is YouTube2, with its AI-based content recommendation algorithms that led to users accusing it of radicalization. Its constant upping-the-ante approach led users to extreme content in a bid to maximize viewing time. So videos on vegetarianism led to veganism, and jogging searches resulted in ultramarathons. This unintentional polarizing and radicalizing highlights one significant challenge: we have yet to define the goals accurately for our AI systems!

The sad truth is that we don’t even know what we want, at least not from our autonomous systems and gadgets and other possessions. For instance, a self-driving car may be too slow and brake too often just the way it was designed to prevent itself from colliding with nearby objects. But the object could be as insignificant as a paper bag that was blown away by the wind.

What we need is goal-oriented AI born with a solid sense of purpose with excellent human-machine coordination. But only after you have answered the question- Do I really need AI?

Here’s is your ultimate AI implementation checklist

AI has ample scope in many sectors. AI can interact on your behalf with customers, as in the case of chatbots, or help healthcare providers diagnose cancer and other ailments. If leveraged well, it can help you turn a new leaf in critical interactions with your customers. Understanding the potential of AI and applying it to enhance critical business values can make a world of difference to your business. The key is to know where you stand and whether AI can help you attain your business goals.

Identify the purpose

Organizations with successful AI implementations are usually the ones that have assessed its financial impact or conducted a thorough risk analysis for AI projects. Having the right metrics in place gives you a sneak peek into the risks and benefits of AI implementation and how it would perform in those chosen areas. While it may not guarantee a positive ROI, it gives you a fair idea about what to expect. 

Accuracy, for instance, is an important metric, but it’s not enough to understand how well your AI systems are performing. You need to correlate  AI metrics to business outcomes to ensure you get the most out of your investments. 

The smart pricing tool created by Airbnb to eliminate pricing disparities between black hosts and white hosts presents a classic example. While the AI-based system performed the assigned tasks with precision, the business results fell short – widening the gap further by 20%. 

Appoint mixed-role teams for all AI initiatives

Those who have implemented AI successfully will tell you how crucial it is to build mixed-role teams comprising project managers, strategists, application designers, AI researchers, and data scientists to ensure a diversity of thought and skillsets. As per a Garnet Research Circle survey3, skills are the first barrier to AI adoption, and 56 percent of respondents believed new skills are required for new and existing jobs.

AI needs experts for it to evolve to its best version. TayTweets, a promising chatbot by Microsoft, was nothing but fun, and people loved talking to her. Until, of course, she became the nastiest chatbot ever in less than 24 hours, responding with offensive tweets. It demonstrates how horribly things can go wrong when AI and ML go awry when left unchecked.

Diversity in technical acumen enhances the value of AI to customers since the people working with AI know-how and where it should be used to have the most significant impact. Whether you want to hire new people or train existing ones for newer roles and responsibilities is something you will have to decide based on the business initiatives you have in mind.

Make a business case for AI

Businesses need AI for different reasons ranging from data security and fraud detection to supply chain management and customer support. You need to identify the use cases and applications to determine how AI can be effectively used. Organizations depend on AI to analyze contextual interaction data in real-time and compare it with historical data to get insights and recommendations.

Data plays a pivotal role in every aspect of a business. While a lot of emphases is placed on coding, math, and algorithms, many organizations are not able to apply the data acquired effectively in a business context. You will have to understand who you are building these solutions for and what technology framework you will require to do so.

As Moutusi Sau, principal research analyst at Gartner4, points out, “Business cases for AI projects are complex to develop as the costs and benefits are harder to predict than for most other IT projects. Challenges particular to AI projects include additional layers of complexity, opaqueness, and unpredictability that just aren’t found in other standard technology.”

Assess your AI maturity

It is impossible to arrive at a strategy without evaluating where you stand against the AI maturity model. Once you know it, you can decide the next steps. Typically, the AI maturity model has five levels:

Ø Level 1 – There is awareness in the organization, and AI implementation is being considered, but no concrete steps have been taken in that direction.

Ø Level 2 – AI is actively present in proofs of concept and pilot projects.

Ø Level 3 – AI is operational, and at least one AI project has made its way to production with a dedicated team and budget. 

Ø Level 4 – AI is part of new digital projects, and AI-powered applications are now an essential part of the business ecosystem.

Ø Level 5 – This should be the ultimate goal where AI is now ingrained in the organizational DNA and plays a transformative role for your business. 

Look beyond the hype

AI can cause ‘cultural anxiety’ as a significant shift in thought and behavior is necessary for successful AI adoption. A compelling story to help employees understand how AI would be beneficial to all is necessary to ease the resistance they might feel towards the change.  CIOs should recognize their fears and anxiety of the possibility of being replaced by machines and encourage an open dialogue with team members. This will build trust and help determine if the organization is ready for AI.

The hype around AI itself can sometimes be the biggest problem as organizations hurry to hop onto the AI bandwagon with insufficient understanding of its impact. Explains Whit Andrews, distinguished vice president analyst at Gartner, “AI projects face unique obstacles due to their scope and popularity, misperceptions about their value, the nature of the data they touch, and cultural concerns. To surmount these hurdles, CIOs should set realistic expectations, identify suitable use cases and create new organizational structures.” 

 AI to Impact

The biggest mistake organizations make when they invest in AI is that they have too many expectations and little understanding of AI capabilities. Rather than getting caught in the hype, you have to be realistic and evaluate its role critically in furthering your business objectives.

AI is an expensive investment that will give you good returns if you know how to use it. A lot of tools are good, but not every AI tool is suitable for your business. What you need is the right AI implementation strategy created with professional help from those who know AI like the back of their hand.

Adopt AI with Trigent

Artificial intelligence is a defining technology that can be successfully integrated into business workflows and applications. We at Trigent have been helping organizations from diverse sectors, including healthcare, retail, BFSI, and logistics, create AI operating models that are optimized for faster and effective outcomes. 

We can help you, too, with everything from strategy and implementation to maintenance and support.

Call us today to book a business consultation

References

  1. https://www.fortunebusinessinsights.com/industry-reports/artificial-intelligence-market-100114
  2. https://firstmonday.org/ojs/index.php/fm/article/view/10419/9404
  3. https://www.gartner.com/smarterwithgartner/3-barriers-to-ai-adoption/
  4. https://www.gartner.com/smarterwithgartner/how-to-build-a-business-case-for-artificial-intelligence/

Can Salesforce IoT Cloud Fill the Customer Experience Gap?

With the onset of the pandemic, organizations worldwide fast-tracked their digital transformation endeavors overhauling their internal tech stack and data capabilities. An immediate need to move physical operations online largely propelled the process. From closing sales deals over business dinners, we had quickly moved to engage with clients in digital spaces.

Among the many challenges, the pandemic ushered in the one that daunted every organization was ensuring a stellar customer experience against all odds. Salesforce is helping enterprises combat modern challenges in a digital-first selling world with Salesforce IoT cloud solutions that can help them soar and serve their customers better.

Salesforce known for its cutting-edge solutions has been consistently deploying emerging innovative technologies like the Internet of Things (IoT) to empower them. IoT is driving business growth by enabling real-time management of critical systems across industries. It comes as no surprise that the global IoT cloud platform market is all set to cross USD 5262.7 million by 2025.

The high demand for automation across sectors has contributed to the growth of the IoT-connected machines market. By 2027, the global IoT connected machines market is predicted to touch USD 1.3 trillion with North America holding a dominant position with its 2019 revenues standing at USD 91 billion.

Explains Warren Wick, EVP AMER Commercial Sales and Chief Revenue Officer1, Sales Cloud, “Over the past year, we held more than six million calls with customers to understand what they needed to be successful as they worked to transform their business with more urgency than ever before. We’ve reimagined Sales Cloud to guide every company as they rethink the digital sales experience, from leads to coaching to processing revenue.”

Enterprises are now generating 21% more sales leads every day in 2021 as compared to the previous year thanks to Salesforce. There are several success stories to tell when it comes to Salesforce and the many organizations it has been helping worldwide to drive growth and offer a better customer experience. With IoT Cloud, Salesforce is also helping them bridge the customer experience gap. We will tell you how.

The IoT edge from Salesforce

IoT is an ecosystem; one where physical objects are connected across geographies through an IP address that connects them via the Internet. The devices connect, communicate, and help users come up with real-time insights and analytics to improve business outcomes. Salesforce has been offering IoT services through Salesforce IoT Cloud, Salesforce IoT explorer, and Salesforce Einstein services, to facilitate data collection and analysis.

As per a survey conducted by Forbes Insights in collaboration with Intel2 involving 700 executives from diverse industries, it was observed that practically all the industries had witnessed significant improvements in several areas including customer experience.

Salesforce IoT Cloud connects devices, apps, sensors, software, etc. to collect contextual data and give a better understanding of the customer journey. This enables enterprises to engage with customers and help them better with proactive customer support. While many have been investing in IoT adoption, their success rate varies greatly. But those who have leveraged the Salesforce platform have been able to integrate the data obtained from IoT into their CRM systems to reimagine the way they serve, sell, and promote. Most importantly, it has helped them take a step further towards their customers closing the experience gap in the most meaningful manner.

Customer experience has always been looked upon as a critical factor for enhancing customer satisfaction, brand loyalty, and revenues. Salesforce understands this well and offers a world of benefits to its users. The top ones include:

Seamless connectivity between devices and users

The profiles of customers are linked to the devices they use and this creates seamless connectivity to streamline operations and respond to events in real-time. Tesla’s self-driving cars are a classic case in point and set an example as to how much you can achieve with IoT.

General Motors with its crisis assistance services came as a savior during hurricane Dorian wherein it could help those trying to escape the hurricane with real-time direction, free calls, routing to shelter and basic amenities, an in-vehicle WiFi hotspot, and much more.

Real-time analysis based on context

Without customer context, it would be impossible to analyze past behaviors and take remedial action in real-time. Machine learning plays a big role in providing it. Data collected from diverse locations and devices give a realistic picture of what’s happening and where taking into account customer history, service history, and location.

Opportunities to serve better

With so much information at hand, you get to know exactly how the products are performing, whether they are due for maintenance, are there any new updates, is the warranty about to expire, etc. Salesforce IoT Cloud helps you manage all of this with the help of predefined rules that are orchestrated based on performance metrics.

The Sales and Support teams are instantly notified if the product fails to perform as per the expected standard. This kind of data helps in predicting behaviors while providing opportunities to enhance customer retention.

Offers a low-code, user-friendly platform

The fact that Salesforce employs low-code ensures that enterprises don’t have to recruit dedicated staff or a data scientist to manage IoT-related processes. A few clicks and you get all the information you need.

With the right triggers and responses in place, IoT takes away the stress and sends data to relevant platforms. A simple act like generating a lead form for a customer whose product is about to fail can have a positive impact on the customer experience while ensuring a substantial reduction in costs.

A win-win for all

A proactive approach strengthened by the extraordinary capabilities of Salesforce IoT Cloud enables you to understand your customers and engage with them in more meaningful ways. Salesforce allows you to export your IoT data in whichever format you want. It is easy to integrate into diverse business environments and there are multiple use cases that are currently being powered by IoT.

Salesforce Einstein with the help of AI technologies helps teams across departments like sales, marketing, and IT become more predictive and proactive when it comes to offering a stellar customer experience. Salesforce IoT Cloud empowers enterprises with IoT-driven tools and data-driven solutions to build trust and fill the customer service gap efficiently.

As Victor Abelairas, GM of Tridium Innovation at Honeywell Connected Enterprise explains, “Our sellers were able to continue their sales process virtually without skipping a beat. But more importantly, we were able to empower the rest of the company to stay engaged with the sales team and know what was happening with customers at all times, without having the day-to-day interaction in the office that they were used to. At the end of the day, we want to provide a better customer experience by understanding our customers more holistically than we would have otherwise.”

Deliver a better customer experience with Trigent

Our team of Salesforce consultants can help you integrate Salesforce IoT Cloud within your business environment to help you respond faster and serve better.

They understand exactly what it takes to enhance productivity and improve revenues. They can help you understand the many nuances of Salesforce IoT Cloud right from IoT implementation to customization to create engaging customer experiences.

Call us today to book a consultation and discover infinite possibilities with Salesforce IoT Cloud adoption.

References

  1. https://www.expresscomputer.in/news/salesforce-reimagines-sales-cloud-to-drive-growth-in-a-sell-from-anywhere-world/74233/
  2. https://www.forbes.com/sites/insights-inteliot/2018/08/24/how-iot-is-impacting-7-key-industries-today/?sh=7ad9ef9e1a84

Enable Transparent Tracking with NextGen Technologies for Cold Chain Logistics

Even as globalization has made the world a smaller place, the physical separation of the different regions still remains an important reality, especially when it pertains to the movement of goods. The greater this physical separation, greater are the odds of the consignment getting damaged.

This is even more true when it relates to the transportation of perishable goods. Hence, efficient cold chains have become an essential part of the modern supply chain to transport vital, sensitive cargo over great distances and through diverse climatic conditions.

For the range of supplies labeled as perishables, particularly pharmaceuticals and food (produces), quality expires with time as they maintain chemical reactions, which can mostly be alleviated with lower temperatures. Cold chain logistics have evolved with the growing demand for temperature-controlled logistics to transport consumable goods over great distances safely.

It takes coordination and time to move a shipment efficiently. Every delay can have negative consequences. To ensure that the loads do not become compromised or damaged at any point during this process, businesses in the food, medical and pharmaceutical industries are increasingly banking on the cold chain.

The challenges of cold chain transportation

In addition to the usual risk elements that plague our regular supply chains, cold chain logistics has unique issues, such as rising freight costs, product sensitivity, and growing regulatory obstacles.

The recent reports of over 12,000 vaccine doses spoiling due to fluctuations in the truck temperature are evidence of some of the main challenges faced by the industry today. According to the Department of Health and Human Services, the majority of 21 shipments of the Moderna COVID-19 vaccine sent to Michigan were unusable as they got too cold during transit.

The incident has, however, brought clarity to the fact that fleet managers need a better way to access and manage real-time information. The need for real-time data to manage deliveries with efficiency and precision is ever increasing. The insights drawn from this data can help fleet managers, drivers, and businesses work together towards the best outcomes.

The numbers linked to food recalls and losses are also staggering. In 2008, a single recall cost the food companies over $500 mn in settlements. Also, over $161 billion worth of losses were reported in 2010 due to food waste. A precise process to track and trace processes with new technologies such as blockchain, IoT, big data and AI can reduce or potentially eliminate waste and recalls. This can be done by ensuring safe and well-prepared supply chain operations, advanced disposal mechanisms for contaminated food batches, and timely deliveries.

The need for supply chain visibility

Supply chain visibility is crucial to both companies and customers today. According to popular research, 94% of customers are more likely to be devoted to a freight company that offers complete supply-chain transparency. Also, about 39% of consumers say they would willingly switch to a more transparent company if offered the chance.

This trend has some big brands implementing technology such as Blockchain to trace and track every activity across their supply chain. Real-time tracking with RFID enables tracking of tagged objects, creates a system of connected devices that continuously transmit data about their location, product condition, and more.

Given the highly dynamic and unique nature of the cold chain challenges, fleet managers require technologies that have fast information processing capabilities. It should also be able to digest streams of data from million sources at the moment and also be agile enough to acclimate to evolving situations.

Digital Twin is a new, powerful software technique built upon in-memory computing. It has recently emerged with the ability to meet real-time data requirements and is cost-effective to implement, thanks to the Internet of Things (IoT). It helps fleet managers boost their situational awareness by identifying and tackling delivery challenges.

A logistics management system with real-time dashboards, timely reports, and better contextual information can make cold chain management and monitoring easier. Leveraging cloud-based systems equipped with real-time predictive analytics would help identify risk and provide opportunities to improve logistics efficiency.

Reducing cost with real-time cold chain monitoring

A well-run supply chain enhances customer service, saves money, and reduces transit time. The savings don’t come easy, though. They can only be accomplished through some digital transformation in the existing system. It requires some incremental improvement in processes along with a proactive risk-management approach.

Real-time monitoring can help logistics companies eliminate one of the most significant pain points of cold chain logistics – spoilage. Monitoring shipments in real-time and instantly flagging issues such as temperature excursions, hardware/coolant malfunctions, or deviations from handling protocols can help prevent damage in transit. 

While reducing spoilage with a better refrigeration system and managing transportation costs with multi-modal shipments is an option, this involves many hidden costs. Compliance mandates, labor, spare parts, weight, and several other factors contribute to the intricacies of maintaining the cold chain shipping costs.

The use of real-time data enables real-time analytics and response. It provides the opportunity to not only prevent cold chain risk but to eliminate it outright. It helps run a reliable and leaner cold chain taking off the weight of process and quality management with automation. 

The hybrid combination of all accessible data, constant connectivity, robust monitoring devices, and analytics that support data-driven improvements in logistics operations embodies the pinnacle of cold chain management and monitoring systems. Though small, real-time shipment process intervention and monitoring will be vital to your overall logistics efficiency plan.

Although it is logical to think of cost reductions from the bottom-up, the effort to evolve needs to be top-down. A digital transformation of your legacy system will help support the more extensive landscape for your business if it is used right, as in any tool.

Automate your cold chain logistics with Trigent

With a highly experienced team of technology experts having over decades of experience in TMS solutions, Trigent helps revamp your legacy systems to drive revenue and efficiency. We combine the best disruptive technologies, analytics, and trade intelligence to create custom-made solutions to overcome your supply chain challenges. 

We help our customers increase their market value and visibility with seamless integration of the latest technology solutions. Our solutions help you cater to diverse load requirements, optimize routing, market best rates, gather real-time location data, weather forecast & utilization of space, among others.

Build your next-gen cold chain logistics solutions with us. Call us today to book a business consultation.

Effective Predictive Maintenance needs strategic automation and human insight

New-age technologies like Artificial Intelligence (AI), Machine Learning (ML), Internet of things (IoT), and predictive analytics are automating processes and augmenting human capabilities. Together, they set the stage for innovations in different sectors. Manufacturing is leveraging Predictive Maintenance (PdM) that takes preventive maintenance several notches higher.

What is Predictive Maintenance?

PdM changes the approach from reactive to proactive maintenance, empowering enterprises to anticipate changes in the system and preemptively manage them. In other words, it helps enterprises predict and avoid machine failure and resultant downtimes. These analytics-led predictions optimize maintenance efforts and facilitate frictionless interdependence.

According to Deloitte, PdM increases equipment uptime by 10-20% and reduces overall maintenance costs and maintenance planning time by 5-10% and 20-50% respectively. With a CAGR of 25.2%, the global predictive maintenance market is set to grow from USD 4.0 billion in 2020 to 12.3 billion by 2025. The growth is fueled by the continued demand for reducing maintenance costs and downtime.

In the current Industry 5.0 environment, the role of maintenance has evolved from merely preventing downtimes of individual assets to predicting failures and creating synchrony between people, processes, and technologies. Predictive maintenance plays its part well, though it does bring along certain challenges that necessitate human intervention.

Benefits of predictive maintenance in manufacturing

As mentioned earlier, predictive maintenance helps eliminate unplanned downtime and related costs. In an IoT-driven world where sensors, devices, systems, etc. are connected, McKinsey believes that the linking of physical and digital worlds could generate up to $11.1 trillion annually in economic value by 2025.

Maximized runtime also means better profits, happier customers, and greater trust. Predictive maintenance can ease logistics by choosing maintenance time slots outside of production hours or at a time when the maintenance personnel is available. It contributes to supply chain resilience, material costs savings, and increased machine lifespan.

However, PdM is only as good as the data it relies upon. Due to IoT technology, data comes from different sources and needs to be duly analyzed before it can be harnessed to make predictions. Hence the importance of IoT Predictive Maintenance

Limitations of predictive maintenance

We need to consider several elements to translate the information PdM provides into positive outcomes. For instance, depending on usage and maintenance history, it may advise you to replace a certain part or component. But this information can lead to further questions. You may need help in deciding which brand and vendor to consider, whether replacement of the component is a good option, or would it make better sense to replace the equipment entirely.

The forecast is often prescriptive and based on statistical models. While optimizing the operational efficiency of a particular line of business, PdM often fails to consider how it impacts other lines. For instance, when it suggests particular equipment is due for maintenance, it may not be able to offer advice as to where the production/processing needs to be shifted when it’s down. The value it offers will therefore be shaped by how decision-makers respond to predictive data.

Data quality and coverage are critical to make predictive maintenance work for the organization. For data to be suitably collected, integrated, interpreted, and transformed, we need dashboards, notification systems, and a bunch of other things to get started. This requires considerable research and planning to go into its implementation for it to start providing the insights we need.

Predictive maintenance use cases in manufaturing – The key lies in the way you respond

Decision-makers typically respond to predictive data with either hypothesis-driven or data-driven responses. The former stems from past business experiences and determines the plan based on a limited scope of response actions. Data-driven responses, on the other hand, aim to find solutions based on real-time business realities and consider several optimization scenarios to determine the way forward.

In contrast to hypothesis-driven decision-making, optimization ensures that all possible paths are explored and evaluated, relevant constraints are taken into consideration, and cross-functional interdependencies are looked into. A workable scenario based on business realities is thus created with no scope for purely intuitive responses.

Despite the analytics-driven insights, predictive maintenance is incomplete without human judgment. Smart decisions come from the ability to visualize the physical and financial outcomes before enforcing them. High-risk situations might arise, and thus they are best left to human discretion.

A predictive maintenance model for Industry 5.0

Manufacturers need clarity on several variables to understand the implications of failure. A false alarm triggered due to inaccurate predictions can result in a lot of unwarranted chaos and anxiety. However, a missed detection might often prove to be a costly error, sometimes resulting in loss of humans and property. Therefore, while understanding variables, they need to first know how often the variable behaviors occur on the factory floor. Strong domain knowledge along with solid data based on previous failures and scenarios is the key to understanding a machine.

Prediction accuracy will improve if we have adequate data on the behavior of machines when they are very close to failure. Only skilled personnel can determine this; some data sets, despite being important, are harder to collect and yet very critical for decision-making.

If we need data on a machine that breaks just once in a year or two, we need to work closely with machine makers who already possess a large pool of relevant data. Alternatively, we may choose to create a digital or a simulation model to create relevant data sets. The most expensive failures are usually the ones we never expect and hence relevant testing for different scenarios should also be considered.

The future of predictive maintenance

The way forward into Industry 5.0 is to create a predictive model that uses analytics, machine learning, and Artificial Intelligence (AI) in conjunction with human insights.

Manufacturers are now relying on predictive models to facilitate smart manufacturing as they struggle with quality issues more often than machine failures. Unusual temperatures, random vibrations, are all telltale signs that a machine may be in dire need of maintenance. Simple data sets can be a good starting point as we scale up with the right predictive maintenance solution. But, in the end, it’s the human insight that can give predictive maintenance its winning streak.

Predict business success with Trigent

At Trigent, we are helping organizations benefit from Industry 5.0 We help them build value with predictive analytics and rise above maintenance challenges. With the right guidance, we help them foster the man-machine symbiosis to harness new levels of operational efficiencies.

Call us today for a consultation. We’d be happy to help with insights, solutions, and the right approach to predict better business outcomes.

What do Brown M&Ms Have to do with Outsourcing?

It is a folklore that has been proven true. In the 80s, Van Halen had strict conditions to remove brown M&Ms from their dressing room at the tour venues, or the show promoter will forfeit their money. The 53 pages typewritten rider contained the condition that along with a wide selection of beverages and food, M&Ms must be provided, but absolutely no brown ones. Years later, David Lee Roth charmingly explains the truth behind this clause in his video – that it was not a silly rockstar misdemeanor excess, but an intelligent safety check measure. Simply put, if the band found brown M&Ms in the dressing room, they will assume the promoters have not taken care of all the electrical and mechanical safety conditions in the rider. Then the band would spend time checking everything with a fine-tooth comb to ensure a safe and flawless show.

In other words, it is a simple assumption that if someone has taken care of the small stuff, they certainly can be trusted to take care of the big things. Just like Van Halen, check if your outsourcing partner has done the small things right. If they did, you could rest assured that they will take care of the big things.

Access to everyone on the team

Did the outsourcing company set up a meeting early to introduce everyone on the team? Such meetings are impactful when done with video. You should have all the details to reach everyone on the team – their emails, phone, skype, etc. Easy access increases communication among the teams. Highly collaborative companies set up Slack channels to communicate instantly with team members. Do you have easy access to the provider’s senior management? The provider’s leadership must check in with you periodically. When needed, you also should be able to get their senior management’s attention.

Transparency in daily activities

You should know what your outsourced team does every day. Though they maybe thousands of miles away and separated by timezones, you should get brief but crisp updates each day – on Slack or via email. Your daily stand up may include them to provide the updates. The remote teams should be check-in code into your repository every day. Weekly timesheets with a judicious amount of details will provide better insight into the time spent on various activities throughout the week.

Empowered Client Partner/Project Manager

Your project manager must your trust to make decisions on their end – as well as demand changes on your side – to ensure mutual success. While you have access to all of your team – who are hyper-focused on coding, testing, etc., you need a client partner who has your perspective to make everyday tactical decisions. They do not lose sight of the forest for the trees. The project manager should make specific, concise, and realistic communication about what they need and expect from each other. Do they take the liberty to suggest process changes? To put is crude, while you may have many backs to pat, you need one throat to choke.

The flexibility of the engagement

Good partners make the engagement flexible for both. Does your outsourcer lock you down with long term commitments and penalties? An outsourcing provider should be agile in terms of process, contracts, and other demands. How easy is it for you to scale your team up or down with relatively short notice, say weeks and not months.

How well do they treat their employees

“Customers will never love a company until the employees love it first.” — Simon Sinek

Companies that treat their employees well, certainly will treat their clients well and value them. When employees are valued with trust, respect, and dignity, they perform at their best. High performing teams will produce results that matter to you. See if your outsourcing vendor provides their employees a good work/life balance, continued carrier training, rewards, and recognition.

In summary, little things make big things happen. See if your outsourcer takes care of some of these small things. If they do, then you can trust that they take care of more complex and critical things too.

Ten Blockchain Benefits for Supply Chain Management

Blockchain, as a distributed database that stores digital information securely is transforming supply chain management in the manufacturing space.

Even though blockchain was initially intended for financial transactions, smart factories are finding different usages for this technology, as it can hold, record, and verify anything of value.

Deloitte describes the potential of blockchain for the intelligent factory as, “Smart factories can operate within the four walls of the factory, but they can also connect to a global network of similar production systems and even to the digital supply network more broadly.”

I draw upon our recent experience with a leading manufacturer of food products in NA to write up this blog to list top ten benefits of blockchain for supply chain management in manufacturing.

1. Increase Automation

Blockchain reduces dependency on paperwork and manual processes. Manufacturing supply chains, if they have even one single bit of inaccurate data can result in disputes, and disrupt operations. This leads to operational inefficiencies and the delays can be costly. Blockchain provides `an automated method for storing information in a tamper-evident digital format. This ability of blockchain can benefit planning, compliance, deliveries and inter-department approvals.

2. Efficiency in Connectivity

Supply chains can benefit from high levels of transparency where data silos are reduced and document authenticity is not compromised. A single source of truth helps operations to move documents from one stakeholder to the next safe in the knowledge that the documents are secure and tamper proof. In addition, error-free document flow ensures the free flow of goods, which help to speed up deliveries. A recent survey by Deloitte states that over 90 percent of consumers’ surveyed list, food product transparency, as a critical factor affecting the purchase and they expect manufacturers to provide the necessary information.

3. Erasing Boundaries

Supply chains that are spread across geographies require the management of transportation, customs collaboration and other such dependencies. Accurate documentation ensures that there are no broken links that can cause delays to supply. Blockchain helps to digitize physical assets and create a decentralized record of transactions making it possible to trace and track.

4. Adding Authenticity

Blockchain ensures that authenticity can be added to products which are produced in one country but supplied to another. Especially in the case of luxury items or pharmaceutical products, blockchain provides the authenticity on its source and preservation through tamper-proof digital documentation.

5. Cooperation Between Man & Machines

Blockchain invokes digital trust between partners, customers and suppliers. Trust is the bedrock of supply chain management and blockchain enables this by enhancing communication between machines and humans. “Blockchains allow us to have a distributed peer-to-peer network where non-trusting members can interact with each other without a trusted intermediary, in a verifiable manner.”- Institute of Electrical and Electronics Engineers (IEEE)

6. Blanket RFQs

Blockchain enables the creation of tamper-proof smart contract that automatically includes multi-party agreements. Smart contracts self-verify terms and conditions and self-execute by releasing payments to concerned parties. Multiple contracts can be created across an entire supply chain where the value and terms are integrated. Though such agreements are tamper-proof, they are outwardly visible to stakeholders across each stage of the chain.

7. Origin Tracking for CRM

In a typical manufacturing supply chain, all stakeholders focus on moving products from one stage to the next. Sometimes the broad picture is ignored for the small, i.e. in this case the customer. Customer tracking from the first order is imperative for long-term relationship management and brand building. Blockchain helps with provenance tracking and ensures that all data is never lost or compromised.

8. Cost Control

A survey of supply chain works conducted by the Digital Supply Chain Institute (DSCI) states that more than one-third of people quoted reduction of costs as the highest benefit of blockchain in supply chain management. By hastening administrative processes, it controls extra costs without compromising transaction security

9. Fraud Management

Digital consumers are making conscious buying decisions and suppliers are searching for newer and better ways to invoke confidence and prove authenticity. Blockchain provides all the proof required by consumers to ensure that compliance has been maintained by the manufacturer. In the food industry, especially, it is estimated that there is a loss of $40 billion every year from food fraud. Food fraud refers to the deliberate and intentional substitutions of inference products for financial benefits. Blockchains can embed origination data and as the food travels down the chain, all other historical data is added and the customer gets the complete origination history.

10. Outsourced Contract Manufacturing

Businesses can maintain more control over their outsourced manufacturing by providing all parties in the supply chain with access to the same information. Less time is spent on data validation and focus remains on improving goods, reducing costs and delivering within stipulated time lines.

Blockchain opens up possibilities to expedite and streamline the everyday processes businesses run on. The beauty of blockchain for supply chain management, specifically, is that it not only simplifies the procurement or precision parts selling process, but it also makes the method safer, faster, and less expensive. Trigent has in-depth domain knowledge and technology expertise of manufacturing systems to help companies optimize their supply chains.

Four disruptive technologies for Banking in 2019

In the brave new world of banking and financial services, technology has become the key to a locker filled with goodies. As a result, it is not impossible to imagine a future where opening a bank or a financial company is as simple as connecting an appliance. In that world, a robot could guide an investor on the best possible options or you could walk into a bank manned by robot tellers. PWC’s report titled ‘Financial Services Technology 2020 and Beyond: Embracing disruption‘ envisages a future where the impossible will become reality. While this list may seem a little too futuristic, banks and financial services organizations are already feeling the tremors of new technology waves that are disrupting existing business models to pave the way for faster, smarter, cheaper operations.

Here are a few emerging technology disrupters:

Distributed ledger technology (DLT)

Algorithms are enabling the collaborative creation of digital distribution ledgers that are far smarter than their paper counterparts. Distributed ledgers are asset databases that can be shared across multiple devices, sites, and geographies where participants can own identical copies of the ledger. Used for various purposes, these ledgers are stored in cryptographic forms and accessed with electronic keys and signatures. Participants, based on rule-based permissions, can update these ledgers, whenever required.

Accelerating change in financial services through Digital Transformation

Distributed ledgers are beneficial to banks as they can reflect changes on a real-time basis. As they are extremely secure, they prevent unauthorized entries, making corruption virtually impossible. As a technology solution, distributed ledgers reside on top of existing applications. Within the field of distributed ledgers, block chain is one more method of distributed ledgers. However, block chain is restricted to a sequential model while DLs do not necessarily fit into a sequential pattern when distributing ledgers. Distributed ledgers may be a good first step forward with immediate benefits for the banking sector.

Artificial Intelligence

Robo-advisor – Fancy though the name sounds, robo-advisors have been around for over a decade. However, it is only in the recent past that this concept has gained popularity. Robo-advisor is an algorigthm-based AI for automated financial advice. This concept has become especially popular for small investors with limited investment options. However, even in cases of larger investments requiring complex decision-making, robo advisors help to automate activities such as tax losses and rebalancing. Robo advisors are useful for single investment goals, and are very good with automated portfolio rebalancing.

As an add-on service, banks can provide value-added services to customers using robo-advisors. Customers can, thus, benefit from customized financial plans and automated investing. One of the key advantages of robo-advisors is the ability to negate human-made calculation mistakes. Uncolored by human emotions, robo-advisors rely purely on algorithms and numbers, reducing chances of errors in investment decisions. In the competitive world of banking, robo-advisors can combine the derive intelligence on existing customers to offer customized investment plans that are beneficial to banks and customers.

e-KYC and identity

Know Your Customer (KYC) is a process adopted by businesses who offer products and services to traders, customers and agents. It is also a process followed by financial services organizations to adhere to regulatory requirements and also to target segment customers. Till recently KYC was a physical activity which required human intervention. While several organizations continue to rely on physical KYC, some forward thinking financial institutions are incorporating eKYC as a procedure for information and verification on customers. By minimizing paperwork and manual labor, eKYC presents a huge opportunity for banks to reduce operational costs without compromising security and information. eKYC reduces paper dependencies thereby helping to avoid identity thefts, and eliminating forgery. Banks can adopt eKYC as it is extremely secure. In the future, eKYC would be the first step forward in a world of secure, paperless transactions.

Cybersecurity

According to the 2017 True Cost of Fraud Study from LexisNexis® Risk Solutions, financial services companies earning at least half of their revenues through digital channels incur up to $3.04 in costs for every dollar lost to cyber-fraud. However, as per the same survey, banks that adopted a multi-layered approach to cybersecurity experience less than 50 percent of the average losses attributed to lapse in cyber security. To ensure cybersecurity, banks are leaning on digital identity intelligence, advanced behavioral analysis, clear-box machine learning technics and integrated risk based authentication. With over one billion new internet users entering the field on an annual basis, the fear of cyber threats can be extremely overwhelming. However, digital identity-based authentication is helping to control fears while providing a real boost to this industry.

To summarize, technology disruptors are providing opportunities and challenges to the banking sector. While challenges such as data breaches, cyber attacks and compromised data will be a fear factor, banks that want to meet the heightened needs of customers should plunge ahead and adapt digital technologies for competitive success.

Internet of Things – Three Popular Development Boards

The Internet of Things (IoT) is developing at a rapid pace, as a result of the availability of small, inexpensive computing hardware. IoT development boards combine micro-controllers, processors, wireless chips, and other components in a pre-built, ready-to-program package. Development boards come in various configurations and here are three popular ones.

Arduino Uno

The Arduino UNO is an open-source microcontroller development board based on the ATmega328P(datasheet) which has:

  • 14 digital input/output pins
  • 6 analog inputs
  • A 16 MHz quartz crystal,
  • A USB connection,
  • A power jack,
  • An ICSP header and
  • A reset button

The Arduino Software (IDE) runs on Windows, Macintosh OSX, and Linux operating systems. The Arduino IDE supports the languages C and C++ using special rules of code structuring.

Applications:

Few applications of the Arduino Uno boards are:

  • Robotics and Control Systems
  • Home and Industry Automation
  • Traffic Light Countdown Timer
  • Underground Cable Fault Recognition
  • Controlling of Electrical Appliances using IR
  • Parking Lot Counter
  • Weighing Machines
  • Medical Instrument
  • Emergency Light for Railways
  • Auto Intensity Control of Street Lights
  • Biotechnology
  • Agriculture

Pros:

  • Inexpensive
  • Cross-platform
  • Simple, clear programming environment
  • Open source and extensible software and hardware
  • Large support of community

Cons:

  • Memory limitations
  • Less powerful
  • Processing power is weaker than the microcontroller
  • Requires effort to accomplish some tasks such as scheduling and database storage

Transform your industry and disrupt the competition with IoT

Raspberry Pi 3

Raspberry Pi is a fully functioning credit card-sized computer, which runs on a customized Debian Linux called Raspbian. Like a computer, a Pi has a memory, processor, USB ports, audio output, a graphic driver for HDMI output.

Pi is a powerful platform based on a Broadcom BCM2837 SoC with a:

  • 2 GHz 64-bit quad-core ARM Cortex-A53 processor
  • 1GB RAM

Raspberry Pi 3 is equipped with:

  • 4 GHz WiFi 802.11n
  • Bluetooth 4.1
  • 10/100 Ethernet port

Advantages of Raspberry Pi over Arduino:

Raspberry Pi Arduino
Multitasking and suitable for complex projects Runs one program at a time, used for repetitive work
Suitable for software projects Suitable for hardware projects
No limiting to programming language Limited to Arduini, C/C++
Built-in Ethernet port for networking Need to connect external hardware and implement coding
Act as a server and communicate to other computers, connected devices. Excels in controlling small devices like sensors, motors, and lights

Applications of Raspberry Pi:

  • Media Streamer
  • Arcade machine
  • Tablet computer
  • Home automation
  • Carputer
  • Internet radio
  • Controlling robots
  • Cosmic Computer
  • Hunting for meteorites and Coffee
  • Raspberry based projects

Pros:

  • Super powerful with lots of memory and processing capabilities. Expandable memory.
  • Linux based OS and now even Windows 10 can be run on top of it to make processing more user-friendly.
  • A lot of GPIOs available, and the more the GPIOs, the more sensors you can interface.
  • If you have experience with Linux, it’s very easy to get started with it, otherwise it will take some time to get the hang of it.
  • Python, C, C++, Ruby, Go and many more can be used to program the Pi exactly the way you can code any computer.
  • People have successfully used Pi to run Open CV , data mining algorithms etc. and connected the results to various applications.
  • In terms of cost, better than an Arduino with Ethernet shield.
  • Great on-line community and endless possibilities of what can be done using it.

Cons:

  • You need good knowledge of Linux systems to get things moving
  • The processing power will be an overkill processing-wise for most of the applications since we will use it only to send data across.
  • Closed source.
  • Power hungry.

NodeMCU

The NodeMCU is an open source firmware, built around a System-on-a-Chip (SoC) called the ESP8266, and features:

  • Wi-Fi capability
  • Analog pin
  • Digital pins
  • Serial communication protocols

Applications of NodeMCU:

  • Geolocation using ESP8266
  • ESP8266 based wireless server
  • Pressure Sensors on Railway Tracks
  • Air Pollution Meter
  • Humidity and temperature monitoring
  • Wi-Fi controlled robot
  • Temperature logging system
  • M2M using ESP8266
  • Make your personal assistant

Pros:

  • Provided inbuilt WiFi functionality
  • Cost-effective
  • Integrated support for WIFI network
  • Low energy consumption

Cons:

  • It is a 3.3V device, so it may not be compatible with some peripherals
  • Lack of official documentation
  • WiFi code takes a lot of CPU power

Trigent helps global companies to apply IoT Command Control and Coordination systems to solve real-world business problems. To know more visit: Disruptive Technologies.

Glossary:

ATmega328P – Single-chip microcontroller created by Atmel in the megaAVR family

BCM2837– Broadcom chip

ESP8266 – A low-cost Wi-Fi microchip capable of either hosting an application or offloading all Wi-Fi networking functions from another application processor.

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Can Small Businesses Benefit from Big Data?

All organizations irrespective of their size generate volumes of data. However, for SMBs, the question is, does the cost and effort justify the value to be derived from data? Data analytics provides deep insights that complement human judgement. Forrester describes the power of big data for small business as “A major disruption in the business intelligence and data management landscape.”

There are several success stories of small businesses benefiting from data analytics. One interesting story is of a zoo in Washington State that was unable to plan daily staffing commensurate with attendance. The zoo’s major source of income was through attendance, which was highly dependent on weather.

By parsing historical data, and analyzing it against decades of local weather data, they found some predictable intelligence. This helped them to fine-tune their plans regarding staffing and promotional activities.

The fear of big data is probably related to the word `big,’ and small companies wonder if they have enough data to qualify for big data. It does not matter. Any data, including visitor logs from a website, is enough to provide vital information on customer behavior.

Another reason why SMBs shy away from big data could be the lack of streamlined processes and information silos. A lease-management company in North Carolina, that manages nearly 1,000 rental properties in the Outer Banks, was unable to accurately predict profitability for homeowners through tourist rentals. With data stored in spreadsheets, the management found it impossible to analyze the data that they had amassed over the years. The company opted for a business analytics tool, which distilled the data and simplified the available information.

Based on the analytics, the company could share vital information with its guests. They could now make rental-pricing recommendations to owners based on seasonal trends and so forth. The business has grown by over 10 percent and costs reduced by 15 percent in the last three years. Big data analytics for small business also helped this company to identify invoice-processing errors, and overall it saved $50,000, annually.

Leverage our Big Data Services to get insights from your Structured and Unstructured Data Repositories

Smaller organizations focused on business needs may not have the time, or even not see the need for streamlined processes. Big data makes allows us to think about the current strategy, economic environment, and competitive landscape. To move from small to medium and from there to large requires processes. Incorporating them now can help to mine data, which will be useful in the short and long term.

To summarize, big data for small business helps small organizations to watch and learn about their customers and their preferences. Even if it is just from their website, it is still intelligence. For retaining customers and acquiring new ones, for up selling and cross-selling, for streamlined processes, which lead to operational efficiency, big data has a hoard of benefits that simply cannot be ignored!

  1. https://www.inc.com/magazine/201407/kevin-kelleher/how-small-businesses-can-mine-big-data.html

To Opt or Not? Can Traditional Industries Use Machine Learning to Garner Business Insights?

Machine learning is a scientific discipline that uses algorithms to learn from data instead of relying on rules-based programming. It works in three stages, i.e. data processing, model building & deployment, and monitoring, with machine learning binding the three together. The power of machine or deep learning cannot be underestimated and as Alexander Linden, Research Vice President of Gartner says, ‘Deep learning can give promising results when interpreting medical images in order to diagnose cancer early. It can also help improve the sight of visually impaired people, control self-driving vehicles, or recognize and understand a specific person’s speech’.

To Opt or Not

Traditional industries have many processes which are governed by rules-based software. This approach is limited in its ability to tackle complex processes. If the rules-based learning can be substituted with self-learning algorithms, then valuable patterns and solutions would emerge.

As a result of digital data and Internet of Things there is a proliferation of data. If you believe this data will help you make intelligent decisions based on patterns, add machine learning. There is no need to add it otherwise as it can make an existing business complicated. Starting with the smaller pieces of the puzzle is better than jumping into it head on. For example, one can collate information from regular reports, apply machine learning to forward-looking predictions.

Machine learning can be useful to detect anomalies, enhance customer services and recommend new products. Manufacturing companies, for example, can benefit from machine learning by self-examining videos where defects can be spotted and automatically rerouted.

Recent developments in machine learning suggest a future in which robots, machines, and devices will be able to operate more independently if they run on self-learning algorithms. This would have far reaching effect in terms of improved efficiency, and cost savings.

Related: Reshaping your business with AI

Machine learning works best on specific tasks where input and output can be clearly stated. If an organization has a sufficient amount of data, with enough variation, machine learning can produce meaningful approximations.

Finally, it is the technical barriers that become the biggest hurdle in the transition process. To address the actual challenges and the perceived ones, companies need to identify expert data analysts who are capable of developing the intricate algorithms that machine learning requires. It will also require a team of engineers who can provide strategic direction, manage quality, and train internal resources on the tool.