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Data Labeling: Jumpstarting Artificial Intelligence and Machine Learning Applications

Modern Artificial Intelligence (AI) products may seem like science fiction, but for today’s organizations, it’s a key integrated component that contributes to the growth for a business and acts as an ideal way to solve seemingly insurmountable issues in the digital age. The idea, at its core, is relatively simple since data is the new oil that powers a myriad of the transformative technology we see today including AI, advanced predictive analytics, robotics, Machine Learning (ML), Internet of Things (IoT), and many more. The effectiveness of data is inevitably the driver of growth and change, creating new business infrastructure, innovations, and crucially new economics. Data Labeling is a key component to success.

Data Labeling to Drive the AI and ML Explosion

Nevertheless, in some organizations, data is left untapped and businesses are sitting on a huge heap of uncategorized data. As such, data labeling is the gateway for addressing this key data challenge. The labeled data is a catalyzer to train machine learning systems and AI models in critical areas such as image recognition and speech recognition. Generally, data labeling gives AI its power and general purpose, by directly acting upon data that is relevant to decision-making and determining future outcomes. While data labeling is seemingly a cakewalk required for training a myriad of AI models (models that require data to simulate human thinking processes) and ML models (a vehicle that drives AI development, giving access to data and letting them learn for themselves, without the need for any explicit programming); it takes a lot of time to glean, define, and label data, and implement and control data streams to get them prepared for achieving positive and reliable results.

Most often, AI and ML models are trained via supervised learning, where the robust models are fed with a huge amount of labeled data, which has previously been manually categorized by humans. This type of learning is commonly seen in ML algorithms for classification (organizing labeled datasets) and regression (prediction of trends from the labeled data to determine future events). Currently, ML with deep neural networks requires colossal datasets that need to be labeled via massive human intervention, attention, and effort. This painstaking task will eventually slow down the innovation process and the rate of productivity growth.

The next waves of AI and deep learning models are fueled by unsupervised learning, which reduces the need for labeled datasets and leverages raw, unlabeled data to train the practical applications of AI. In this way of unsupervised learning techniques, the system can perform more complex processing tasks than supervised learning systems, since it finds the structure on its own, for example—learning to sort females from male. Unsupervised learning has more complex algorithms than supervised learning since it has very limited information about the data. This type of learning can be used in applications such as grouping and clustering, density estimation and dimensionality reduction.

Take the case of examining a batch of height and weight data for a specific age group of males and females. In supervised learning, we know what kind of data we are dealing with; while, in unsupervised learning any given sample from the data will not contain any additional information stating the height and weight data of a male or female. Here we use a clustering algorithm, which groups a set of objects based on their physical attributes—such as segregating a set of males and females based on their height and weight. Self-Organizing Maps (SOMs), a neural network method which is widely used in gene clustering, plays a vital role to ensure the clustered objects in the same group are more similar to each other comparatively to those in other groups. These SOMs assume a topological structure among the cluster units and effectively map additional information to the input data. We can feed this data back into the supervised learning algorithm as training data and use the model to make predictions on new hidden data.

Generally, which type of learning has driven most of the recent progress in the field? In unsupervised learning each piece of data passes through a model and there is no corresponding label that is paired with the same. Since data is unlabeled, this type of model will not be able to evaluate itself and understand how well it’s performing, and there is no way to measure its accuracy. On the other hand, with a fully supervised approach, the model will be able to predict the output and improve its own efficiency, becoming more accurate over time. The biggest drawback with this type of learning is that it requires a lot of computational time for training. In the case of voluminous and growing data, it may include anomalies and edge-cases to accurately predefine the rules and teach the algorithm to handle each unique situation. This can be a real challenge.  With supervised and unsupervised learning approaches holding their own pros and cons, it is safe to say, choosing either a supervised or unsupervised learning algorithm depends on the major factors related to the structure and volume of the data. However, supervised machine learning is the more common method that has application in a wide variety of industries; it’s wise to leverage both these types of learning approaches for building predictive data models, which in turn will be beneficial for stakeholders to come up with the best decisions across a variety of business challenges.

Seize New Opportunities

Recent studies reveal that more than 75 percent of organizations are investing in meaningful data since AI- and ML-powered smart machines and applications are set to dramatically increase over the next five years. With the recent AI boom, depending on data labeling and synthesis of a huge amount of training data to develop more predictive models, businesses should ensure that the data they collect also becomes more AI and ML-friendly.

Per the McKinsey analysis, modern companies foresee the fourth industrial revolution to increase revenues to $3.7 trillion by 2025 with AI being the cornerstone enabling this huge growth. Anticipating the size of this growth, Ness has pioneered to provide data labeling services for several of our clients. Currently, we are manually data labeling travel videos for one of our automotive clients, including labeling of entities in the road like cars, bikes, trucks, pedestrians, lanes, sign-boards, and many more.  Our labelers are extremely focused because even a single error or inaccuracy negatively affects a dataset’s quality and the overall performance of a predictive model. At Ness, we ensure efficiency and accuracy in every piece of data that we label. Our engineers are working to establish an automated data labeling system to further streamline the data labeling process.

With true innovation at its core, Ness is prepared to drive the rapid take-up of AI and ML applications across a range of sectors. We are aiming to bring positive changes to automotive safety with the goal of stimulating an overall upsurge in car safety for everyone on the road. Since most road accidents occur due to human error, we are focusing on enabling better situational awareness and control to make driving easier and safer through advanced driver-assistance systems. We believe that the progress of these safety approaches will be one of the main trends — by leveraging our technology and expertise, we can help drive future innovation.

When Blockchain Doesn’t Fit

Here’s an insightful article for The Enterprisers Project, where Moshe Kranc, Chief Technology Officer at Ness Digital Engineering, delineates about Blockchain, which enjoys almost as much as hype as the bitcoin. In this article Moshe discusses that with blockchain technology being the topic of considerable interest in recent days, businesses should consider these 3 key characteristics before they get caught up in the recent hype around blockchain. Moshe also reveals the potential uses for blockchain and provide criteria that define the characteristics of an appropriate use case.

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API Gateways: Key Benefits to Consider

Application program interfaces (API) are sets of routines, protocols, and tools for describing how software applications and components should interact with each other. They are the key driver in today’s economy for integrating with an ecosystem much larger than most companies can build on their own.

Today, many ubiquitous digital platforms and services (think Twitter, Facebook, Salesforce, Airbnb, PayPal) are made available through APIs.

Imagine we are building an application to help users with their travel plans. We will require weather information to serve our users with some special offers based on specific weather conditions at a specific location. However, as we do not own any weather data, we can request the information from third-party vendors such as OpenWeatherMap or AccuWeather using their public APIs.

Companies release and promote their services as part of a larger software development kit (SDK) that includes the APIs and instructions to help developers understand the specifications of how to use them. The API layer abstracts all the underlying platform complexities (i.e. simplifies it), and the value in the data is made available via an easy-to-use readable format.

There are different data formats used for API communication and information exchange. The most notable and industry standard data formats are Plain Text, JSON, XML, CSV, and YAML.

Why do we need an API Gateway?

API manager (also referred to as API gateway) platforms are used to easily publish, manage and monitor APIs securely in a highly-scalable environment. Gateways additionally include features such as the ability to apply security policies and usage policies, collecting and analyzing statistics and other value-adds.

Some of the common features offered by today’s popular API manager platforms include:

  • Allowing companies to publish and monitor the API in a secure and scalable environment.
  • Allowing publishers to design, prototype and document APIs in one place. Most of the popular gateways work well with some of the industry standard Open API specifications such as Swagger and RAML.
  • Offering a clean and pluggable environment to make it easy to switch between production and sandbox environments.
  • Defining common security gateway and authentication protocols for all published APIs.
  • Monitoring and managing traffic for individual users or applications.
  • Traffic quota management, which allows you to define the limits of a free quota and where a premium option kicks in based on the volume of incoming traffic.
  • Memory management and data caching mechanisms to improve API performance and response times.
  • API versioning to ensure compatibility between multiple API implementations without any code changes.
  • Some of the API manager platforms even allow developers to define API mock data using JavaScript or a static response. This helps the API consumer to develop and test the application without having to wait for the real working APIs.
  • Defining a load balancer reverse proxy and distribution network for splitting application traffic across several servers.
  • Setting up and managing server failover.

In response to the growing open API movement, some software giants such as Facebook, Twitter, and Google have taken the initiative to build API management software in-house to serve customer data for third-party App developers.

However, implementing such a complex API Gateway platform with the wide variety of transports, security features, authentication, monitoring and usage reporting in-house is very expensive for small and medium enterprises. Hence, some of the big players, including Amazon, IBM, and Microsoft, have built a business model around these platforms to serve enterprises with their API gateway needs.

Overall, there are numerous tools available in this space, and each claims to be more useful than the other. Some of the most popular choices are WSO2, AWS, Azure, IBM API Management, Akamai, MuleSoft and CA’s API Gateway.

During our initial experiments in this area, WSO2 arose as one of the best choices and satisfied most/all the criteria of our business case need. Here are some of our experiences with the WSO2 API manager.

  • It is completely free, open source and released under an Apache 2.0 license. The enterprise license is very affordable.
  • Short learning curve to get started.
  • WSO2 supports OAuth 2.0 security standards with support for quota management and traffic throttling. As we have our own OAuth 2.0 implementation, the integration with the existing system was a straightforward step with standard Java handlers.
  • It doesn’t include a load balancer out of the box, but it works well with our existing Nginx plus load balancer setup.
  • It didn’t support importing RAML specification directly (when we started our investigation), but we’ve been able to convert all our RAML to Swagger and everything else has been smooth since then.
  • As we use a microservices-based distributed architecture, almost all our services communicate using both a synchronous (HTTP based broker-less architecture) and asynchronous (with AMQP message broker) mechanism. WSO2 works nicely with both.
  • Native support for Google Analytics was a plus.
  • Amazing service with extended development support.


For most microservices-based architectures, it makes great sense to consider using an API Gateway that can act as a single-entry point and can provide additional features like authentication, monitoring and load balancing.

It’s been a year since we switched to WSO2 and migrated over 12+ API’s, and I must say, we have not been disappointed. Clearly, WSO2 was the right choice for us, but what works for you?


Never-ending Transformation As An Opportunity


Article was originally published in Euro 26-27, Mlada fronta, Czech Republic.

Interview with Petr Mýtina from Ness Digital Engineering on how businesses must change if they want to succeed.

› What is your perspective on digitalization today?

The digitalization that took place in the second half of the last century was quite straightforward. Clock hands and cogwheels disappeared, while batteries were added. When movies started to be digitalized, everybody understood that film material is not eternal and keeping data on storage media is a great way to save the movies and work with them.

Petr Mýtina,
Managing Director, Czech Republic & Slovakia,
Ness Digital Engineering

Today, a far greater digitalization is taking place. Every day we hear about the digital revolution, yet few people truly know where and how it is actually taking place.

› Do you agree with comparing ongoing digitalization to the next industrial revolution?

No doubt technologies bring major changes to the lives of companies and the whole of society. They change entire industries and the lives of each and every one of us. I recently read about a global financial group which refers to itself as a “technological company operating in the financial services industry”. That is so very true! And, not just for banks and insurance companies. However, I understand the word “revolution” as a dramatic and one-off change. Although technological innovations bring revolutionary changes, I’d rather call it a never-ending digital transformation.

› What is its specific content?

This is a very broad topic, which varies for each industry and individual company. For us it is essential to understand the customer’s situation in the context of its scope, strategy, and individual needs. Only then can we design an appropriate solution. Offering technological innovations just because they’re trendy and everyone talks about them is nonsense.

We can afford such a comprehensive and individual approach because we not only have experts with knowledge of these innovative technologies, but also the years of experience with the systems and businesses of our customers. In the context of digital transformation, we are talking about new customer-oriented technologies, new products and services generating additional sources of revenue, and the use of data and data analysis for decision-making. That is right and logical. Together with our customers, we are also building new portals and self-service zones, and we unite and modernize their business channels and customer platforms. But, you need to see further.

In the field of digitalization of products and services, I find the story of our customer who produces very complex, industrial machines both amazing and iconic. They have gradually added sensors, electronics, regulating and autonomous control systems. But, then they came up with a really transformative idea to sell not only mechanical devices, but also a completely new concept of “machine as a service”.

Together, we have developed and expanded a platform that gathers all of the real-time data from control systems, and monitors, analyzes and compares everything with hundreds of similar devices. Over this platform, we have created a variety of applications that provide invaluable and previously unthinkable information and services. These are applied to improving the planning, management and optimization of the operation of the entire device, data analyses, and predictive maintenance. Here, it is not just about the technology used, but above all, a whole new competitive advantage, as well as a new source of revenue for the company from these services: a new business model.

Customer orientation and digitalization of products and services is just the tip of the iceberg. It is only the surface and often viewed as the priority part of transformation – the front-end part of the business. However, even the best customer application, new service, or product fails to reach its true potential if the company doesn’t manage to handle it properly within its internal organization and information systems – the back-end.

More and more of our customers realize this, and the leading industry analyst firms confirm it. For example, Gartner has come up with a multi-speed IT model, which highlights the conflict between the agility of modern, front-end applications and the stability of robust internal information systems. These internal IT systems often cannot be adapted quickly enough to the new changes due to their nature and technical obsolescence.

› Does this mean that businesses will have to get rid of these older technologies?

All technologies used today have their place. Our customers have invested vast resources and effort into their core systems. Though they are less flexible, large companies could not work without these systems’ stability and reliability. Their replacement is usually an expensive, risky and lengthy process. And, even such a modernized system will not really be agile, because it will once again have to be robust and reliable to meet security and regulatory requirements.

› How do you deal with this dilemma?

There is no single answer. The really outdated and unprofitable systems must be replaced. A significant increase in the flexibility and speed of changes can also be achieved by improving the engineering process support and development of these platforms and by automating testing or deployment of changes into operation. We have several global and local competence centers that are intensely dedicated to these topics.

Yet the fundamental answer is a comprehensive, holistic approach: take advantage of these platforms for their stability, robustness and safety; simplify them where possible; or, migrate functions which are subject to frequent change to the process integration layer. Therefore, we want to be a strategic “end-to-end” partner that helps businesses in linking the world of technological innovation and fast-changing requirements with the permanently necessary and needed world of stable and reliable internal systems.

› In your solutions and services, you put obvious emphasis on the employee experience with technology. Why?

Employees also want to have a good experience with their work and to take advantage of technological innovations, so their work is effective and enjoyable. If employees like what they are doing, this will be reflected positively in their engagement with customers. Motivated, efficient employees and digitalized internal processes are an equally-important part of digital transformation relative to customer orientation. This is also confirmed by Forrester, which has previously predicted needed investment in the digitalization of internal processes and systems, in addition to the digitalization of customer technologies that has already been a focus of organizations.

› Continuing our discussion on processes: what would you recommend to the companies that are holding back?

Companies operate through processes. Process flexibility is key for digital transformation, especially so companies can flexibly respond to changing market situations, customer requirements and new technological possibilities. And, as described earlier, there are ways to modernize stable processes with newer technology options such as automation and internet robots (“bots”).

We build our portfolio on a new generation of agile process platforms, such as ServiceNow, that allow companies to get the necessary part of the logic of their processes from those big transactional systems into separate, flexible layers. Within it, the processes can be changed quickly, while being fully integrated. That is, I believe, a good approach.

› How do technologies affect business strategies?

Technologies release the potential to do things better. They are the trigger or means of changes. But by far, digital transformation is not just about technologies. Whole industries are changing, new companies and business models emerging, and traditional products and services are being digitalized.

› How do you see the development of digital transformation?

Digital transformation will continue, and further innovations will come at an even faster pace. Businesses will have to adapt and become agile by nature. The transformation will involve the entire company making permanent changes to its thinking, approach, culture and management. We call it “end-to-end transformation” and perceive it as an opportunity.

Source: Euro, Mladá fronta, a.s.

Nessian on the Job – Shakti Sahay

My journey so far in Ness:

I believe that a good company keeps its customers happy and a great company is the one which also keeps its employees happy. Being a part of the Ness family, my work as a bid-manager requires end-to-end delivery of the bid/RFx response by coordinating with various stakeholders vis-à-vis solutioning, delivery, practice heads and sales team across all the levels at Ness. I try to create a compelling story for every bid, backed by a client-centric competitive approach of providing solution to the immediate problems of the customer, and focused on setting the foundation for a long-term relationship. As a bid-manager, I make sure that all the client’s concerns are duly addressed by raising the right questions with the internal stakeholders over the lifecycle of the bid-management process right from sales request to building the solutions and commercials to the final proposal. Ness being an agile-focused company with engineering and digital as its DNA, I as a bid manager harnesses the organization’s information and successful engineering stories to establish the company’s market credibility. I am also involved in various analyst reports where I work directly with the Chief Marketing Officer and Chief Digital Officer to create a compelling and differentiating value proposition.

From where it all started:

I have lived across various parts of India throughout my educational and professional life. My graduation in Computer Science engineering has equipped me with the arsenal to understand new and evolving technologies and the MBA has helped me understand the bigger picture of how to connect business and technology.

I have a professional experience of around eight years where I got the opportunity to work across the entire value chain of the software industry. In the past, I have worked as software developer and business analyst. Besides working as a pre-sales consultant, I have also been involved in strategic role in the previous company, like, creating roadmaps for setting up a new offering, establishing partner relationships to supplement capabilities and assisting the recruitment teams with campus hiring.

My journey ahead:

I believe in being out on the field, and meeting new people. My passion therefore lies in sales where I get to meet clients, understand their businesses, their technologies, their problems, and learn something new every day as I strive to help them achieve their goals. I consider my role as a bid-manager as the first step towards achieving my goal at Ness as a successful sales and account manager.

How clients perceive Ness:

I always felt that clients prefer partnering with the right-sized company, which is large enough to have the scale and expertise to meet client’s expectations, and yet provide the level of attention and executive management commitment to ensure success and rapid course correction, if required.

Ness’ early adoption of digital technologies has given it an edge over its competitors in terms of depth of the knowledge and breadth of new age technologies that we can bring to the table.

Ness’ distributed presence enables it to provide services not only from its onsite and offshore facilities but also from its near-shore Eastern Europe centers.

Who am I – Outside Work?:

My professional life complements my personal life where I am able to manage my work-life balance seamlessly. In my free time I try to keep myself busy and engaged by indulging in activities like travelling and playing games. My mantra is “In order to be relevant, one needs to discover and re-discover themselves by investing time and learn something new every day”. I also try to learn something new by reading about the latest digital technologies like blockchain, IoT, AI-ML.

Another Successful Ness City Triathlon in Košice

The result of commitment to excellence, intelligent planning, and focused effort.

It’s another remarkable event at the Košice Center. On June 30th, 2018, Saturday, the 3rd edition of the Ness City Triathlon event took place in the heart of the European city of sport. Looking back at the high-quality Slovak triathlon, it was a successful and fun-filled event for the Košice community. Cheers! to Ness, who was the main partner and the major proponent behind the event’s success.

Ness hosted various contests for the 415 professional and amateur sportsmen from Slovakia and other countries, and also for the Elite category racers. The event was comprised of 750m of swimming, 20km of biking and 5km of running, and included an interesting event for children of Ness employees called “Small Detective”. More than 50 children along with their parents enjoyed fun in seeking and solving various tasks in the City Park. The event was open to all participants including special guests like media and local authority representatives, ice-hockey and water polo players, and more. The Ness City Triathlon has its rigid place in the calendar of sporting events held in Kosice. The event was a unique opportunity that generated exciting, engaging experiences for all of our participants.

The atmosphere during the event was friendly, approachable, responsive, and peaceful. The windy weather was no barrier to the participants in the Triathlon event. The contributors were also supportive of the safety decisions. “The event was simply amazing. Before the race, we set the times we wanted to achieve at each phase, and, despite the windy weather, we did it. Maroš Tyrpák did really well and his time was close to the performance of professionals. Dávid Pinďar was very fast while swimming, and I just finished the race. Primarily we just wanted to support the event—the award received from Marek Uhrín and Zuzka Želinská was a nice surprise for us. I’d like to thank all supporters who cheered us on,” says Roman Pavlanský, QA Lead of Ness KDC.

Overall, the precise organizing of the event, attractive programs, remarkable venue, and fun-filled atmosphere contributed to the enormous success of the event with wide media reach. According to the main organizers, Progress Promotion leaders, and the other partners, Ness City Triathlon has become a ‘rising star event’ and is also the hot talk of the city.

“We’ve always strive to produce top-class CSR activities. Ness City Triathlon bears all the features we value at Ness KDC—uniqueness, top quality, social responsibility, friendliness, family orientation and employee satisfaction. Thanks to its uniqueness, the event is, beside International Peace Marathon, the most attractive sportive Summer event in the city representing the whole Ness. And we are proud of that,” Marek Uhrín, VP – Delivery & Head of Košice Center.

The Elite category (professional triathlonists) awards were won by a Hungarian racer Andras Kiraly and Slovak female racer Nora Jančušová. Vladimír Gajdoš was named the best male Nessian in the race. Moreover, the relays category was won by Roman Pavlanský, Maroš Tyrpák and Dávid Pinďar.

“The triathlon itself is an amazing event—our enthusiastic team has created a wonderful activity that involves the employee’s children, which made the Saturday a wonderful day for all of us. We are all looking forward to next year,” asserts Zuzana Želinská, AVP – Business Finance and Operations.

Ness Welcomes Mark Shwartz to Its Global Executive Committee

TEANECK, NJ – July 16, 2018 Ness Digital Engineering, a global provider of digital transformation and custom software engineering services, is further expanding its leadership team with the appointment of Mark Shwartz to Chief Legal Officer, Corporate Secretary and Chief Compliance Officer. As Ness continues to grow worldwide, Shwartz will be responsible for legal matters related to all aspects of Ness’ business, including corporate governance, compliance, mergers and acquisitions (M&A), sales and other commercial agreements, and employment matters across all Ness locations and entities.

“Having the right legal guidance is critical for a fast-growing company like Ness, and we’re thrilled to add Mark Shwartz, whose extensive international and technology-related experience working across different regions, including North America, Europe and India, will be a great asset to our organization,” said Paul Lombardo, CEO of Ness. “Mark will help us pursue new opportunities that will further enable us to evolve and deliver, with speed and scale, the innovative solutions and intellectual property we develop for our clients.”

Shwartz said that the opportunity to help Ness in the current, dynamic stage of a leading, global technology enterprise attracted him to join the company. “Ness is growing at a rapid pace to meet customer needs, and I look forward to applying my legal and business experience to enhance the company’s growth during this digital age that includes exciting developments, such as those in artificial intelligence, Big Data and IoT,” said Shwartz. “I am excited to be a part of such a great team and well-respected organization in software engineering and digital transformation.”

Shwartz joins Ness with more than twenty years of legal experience, during which time he focused on mergers & acquisitions, intellectual property, corporate governance, international outsourcing, and financial transactions, often involving technology and private equity. Mark is a former law firm partner and has served as general counsel and in other senior roles at companies in a wide range of industries, including positions at CA Technologies, Cengage Learning, Capmark Finance, Sony, and Fried Frank Harris Shriver & Jacobson. Prior to his legal roles, Mark was the Special Assistant to the U.S. Secretary of Defense for international policy and an international business consultant.

Shwartz will report to Lombardo and the company’s board of directors.

About Ness Digital Engineering

Ness Digital Engineering designs, builds, and integrates digital platforms and enterprise software that help organizations engage customers, differentiate their brands, and drive profitable growth. Our customer experience designers, software engineers, data experts, and business consultants partner with clients to develop roadmaps that identify ongoing opportunities to increase the value of their digital solutions and enterprise systems. Through agile development of minimum viable products (MVPs), our clients can test new ideas in the market and continually adapt to changing business conditions—giving our clients the leverage to lead market disruption in their industries and compete more effectively to grow their business. For more information, visit

Media Contacts

Vivek Kangath
Senior Global Manager – Corporate Communications
Ness Digital Engineering
Mobile: +91 9742565583 | Tel: +91 80 41961000 | DID: +91 80 41961027

Amy Legere

Machine Learning Workflow: A New Product Category Is Born

Machine learning is being touted as the solution to problems in every phase of the software product lifecycle. However, like every solution, it comes with challenges. In an article contributed to InformationWeek, Ness CTO Moshe Kranc outlines the phases and challenges of the ML workflow and introduces us to a new category of products that counter these problems by providing a seamless, end-to-end ML operational environment. As Moshe concludes, machine learning is poised for explosive growth, and we can expect to see this product family mature and expand in the coming months.

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Internet of Things – A Real World Business Problem Solver

I recently attended the 7th edition of the India IoT Symposium 2018 event in Mumbai, India, which covered a myriad of Internet of Things (IoT) applications in the Manufacturing, Industrial, Agriculture, Aviation, Real Estate, and Healthcare arenas. The event captured the interests of the top IoT solution providers in the market, namely Thingworx, IOTany, PTC, Ansys, Samsung, Vodafone, and Dell EMC. These providers were also granted the opportunity to present their best-in-class solutions to their prospective customers catering to various industries like cement, paint, chemical, and automobile.

It was evident that these organizations in these areas are leveraging the power of data to drive smarter business decisions, reimagine business models and reduce costs. Here are some of the interesting takeaways from this event:

Ongoing Development of Internet of Things Standards and Products

While some devices can communicate with each other, no universal language exists for the Internet of Things. Device makers instead have had to focus on one of several disparate frameworks, limiting their market share, or to develop across multiple ecosystems, thereby increasing their costs. The burden then falls on the end users to determine whether the products they want are compatible with the ecosystem they bought into or find ways to integrate their device into their network and try to solve interoperability issues on their own. However, these issues can be addressed by providing specification, code and a certification programs to enable manufacturers to bring unique products to the market that can interoperate with the current breed of IoT devices and legacy systems.

Interesting Challenges and Use Cases for IoT

A plastics industry spokesperson, Mr. Jayesh Rambhia, Managing Director at Premsons Plastics P Ltd, discussed the problem of making plastic bags in India, as the government has made it mandatory to control the width of a plastic specified in microns. However, he noted that some manufacturers were still ignoring the mandate and continuing making the bag in their own size. This problem, he suggested, can be overcome with a solution to put a sensor on the machine manufacturing the plastic and to take readings of the size being specified. This can then be connected to the cloud and monitored by the respective authorities. This kind of solution can be implemented at scale on 15,000 plastic manufacturing machines across the country.

There are several common problems in each industry not specific to any one business case. One such problem is ensuring internet connectivity in a remote area, as many manufacturing industries are located in remote places with limited connectivity. The solution suggested to address this problem was Edge computing. According to this solution, most processing can take place at the edge device and only a subset of the data can be sent to the cloud for further analysis.

Manufacturers are also looking at IoT as a strategy to overcome existing problems, make the process of manufacturing much smoother, reduce human error, and get detailed insight into business operations and the manufacturing shop floor.

For example, a cement manufacturer at the event described how it has adopted IoT in its manufacturing process. The profit margins around manufacturing cement are minimal. Any variation in the raw material cost, supply, and machine efficiency directly impacts the cost. Even a 2-3% variation leads to significant financial losses. To control these variations, the company deployed sensors on the machines, where only human interaction could have revealed a problem with the manufacturing machine before. These Radio-frequency identification (RFID) sensors not only helped the company identify variations, but also provided insights into machines operating at low efficiency—because of high temperatures and low speeds – which could then be rectified.

Shashi Kapoor, Dell EMC Spokesperson and Regional Sales Director, spoke about Thyssenkrupp’s use of IoT to reduce the maintenance cost of its elevators by equipping elevators with sensors to help reduce downtime. The company has taken it to the next level by including advertisements using a LCD and camera inside the elevator and facial analysis to play customized advertisements.

In another interesting use case, Michelin has started to provide tires as a service. By leveraging IoT, the company launched an ecosystem that uses sensors inside vehicles to collect data, like fuel consumption, tire pressure, temperature, speed, and location. This data is then processed in a cloud solution and analyzed by Michelin experts, who provide recommendations and training in eco-driving techniques.

Overall, it was an insightful event that clearly portrayed IoT as offering clever ways to address the needs of specific business segments, and its evolution is sure to continue.