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You're reading from  Smarter Decisions - The Intersection of Internet of Things and Decision Science

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Published inJul 2016
Reading LevelIntermediate
PublisherPackt
ISBN-139781785884191
Edition1st Edition
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Jojo Moolayil
Jojo Moolayil
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Jojo Moolayil

Jojo Moolayil is a data scientist, living in Bengaluru—the silicon valley of India. With over 4 years of industrial experience in Decision Science and IoT, he has worked with industry leaders on high impact and critical projects across multiple verticals. He is currently associated with GE, the pioneer and leader in data science for Industrial IoT. Jojo was born and raised in Pune, India and graduated from University of Pune with a major in information technology engineering. With a vision to solve problems at scale, Jojo found solace in decision science and learnt to solve a variety of problems across multiple industry verticals early in his career. He started his career with Mu Sigma Inc., the world's largest pure play analytics provider where he worked with the leaders of many fortune 50 clients. With the passion to solve increasingly complex problems, Jojo touch based with Internet of Things and found deep interest in the very promising area of consumer and industrial IoT. One of the early enthusiasts to venture into IoT analytics, Jojo converged his learnings from decision science to bring the problem solving frameworks and his learnings from data and decision science to IoT. To cement his foundations in industrial IoT and scale the impact of the problem solving experiments, he joined a fast growing IoT Analytics startup called Flutura based in Bangalore and headquartered in the valley. Flutura focuses exclusively on Industrial IoT and specializes in analytics for M2M data. It is with Flutura, where Jojo reinforced his problem solving skills for M2M and Industrial IoT while working for the world's leading manufacturing giant and lighting solutions providers. His quest for solving problems at scale brought the 'product' dimension in him naturally and soon he also ventured into developing data science products and platforms. After a short stint with Flutura, Jojo moved on to work with the leaders of Industrial IoT, that is, G.E. in Bangalore, where he focused on solving decision science problems for Industrial IoT use cases. As a part of his role in GE, Jojo also focuses on developing data science and decision science products and platforms for Industrial IoT.
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Chapter 9. A Promising Future with IoT

We have studied the length and breadth of IoT and decision science and also solved multiple use cases to cement our thoughts foundationally. In the previous chapter, we explored the disruptions in the industry due to IoT and studied how they fostered many more disruptions where IoT played a pivotal role. In this final chapter, we will study how IoT would deliver a promising future for mankind. This chapter will focus on emphasizing the importance and impact of smarter decisions in IoT by showcasing a glimpse into the promising future that has been triggered by IoT. We will start by studying an extremely important business model that emerged in the industry with the inception of IoT, that is, the Asset as a Service or Device as a Service model. Combined together, the asset and device models cover the consumer as well as the industrial sectors to offer cost-effective solutions for customers and higher revenues for business.

We will also understand in brief...

The IoT Business model - Asset or Device as a Service


The Internet of Things started with the simple concept of Connected Devices and Connected Assets. A small network of connected devices made a lot of tasks easier and intuitive that were not feasible earlier. Gradually, connected devices/assets opened up new opportunities with smart devices/assets. In no time, the evolution paced up, and we had a tangible implementation of smart devices in every dimension of consumer electronics, home appliances as well as industrial assets. As the technology matured, the concept of smart factory evolved, that is, Industry 4.0 or the fourth industrial revolution, and eventually smart connected operations became a reality that was complemented with success stories from different parts of the globe.

The Asset as a Service model has its roots in the vanilla 'lease model' widely adopted in the world. You can lease your house, vehicle, or some appliance for a while and earn money for the time period it was utilized...

Smartwatch – A booster to Healthcare IoT


The healthcare industry is experiencing a serious technology boom with the inception of IoT. Connected devices are continuously being leveraged in healthcare to innovate solutions and reduce costs. Smart hospitals and other innovations have been conceptualized where doctors and patients have a digital connection that can aid faster access to health records and other details that can be used to study the current and historic conditions of the patient precisely. Also, as we studied in Chapter 8, Disruptions in IoT with the growth of IoT and the emerging disruptions, the use of genomics for better healthcare solutions is already being practiced.

At the same time, we can see the smartwatch industry gathering a lot of traction. The smartwatch is basically a watch that can connect to different devices such as your smartphone, other smartwatches, and other smart devices. It is generally equipped with a wide variety of sensors and does much more than showing...

Smart healthcare - Connected Humans to Smart Humans


The title may sound weird, but it definitely doesn't mean that we are not smart. Yes, we are already smart individuals, but the 'smart' in this context refers to the smartwatch that identifies an individual. We have already studied how the smartwatch has added phenomenal value to the healthcare industry. Most of us have already used the smartwatch or fitness trackers like Nike's Fitbit, Apple's Watch, and many more from other brands. We have always used these devices to track our health and exercise plan or study the calories burnt and so on. We call the smartwatch an integral part of the IoT fraternity, but we still missed out on emphasizing an extremely vital mode of communication in the smartwatch, that is, smartwatch-to-smartwatch communication.

Yes, the communication between different smartwatches can help us take the smartness in it to the next level. When smartphones can talk to each other and take decisions based on the data signals...

Evolving from connected cars to smart cars


We touched base on the healthcare industry in more detail by understanding how the smartwatch can be a game changer. Leveraging the increased adoption of the smartwatch helps in evolving from connected humans to smart humans. The same success story holds true for multiple industries. We have witnessed the transformation of dumb assets into connected assets and its evolution to smart assets. We will explore the last topic of the book to understand how IoT has laid foundations for a promising future. We'll study the evolution of connected cars to smart cars.

Today, this topic is more of a concept and has seen only a fraction of the possibilities adopted in reality. The autonomous car is also a part of this evolution, but there are many more things that are possible. In the previous chapter, we studied how the autonomous car was born from the disruptions in the industry due to IoT. We studied in brief about the improved integration of the autonomous...

Summary


In this chapter and this book, we have navigated through a beautiful journey of building smarter decisions from IoT when it intersects with decision science. We started our humble journey by understanding the fundamentals of decision science, the Internet of Things, and industry-standard frameworks to solve a problem. We spent quality time to understand the problem more concretely by studying the different dimensions that can be used to define a problem. In the second chapter, we touched base with two important areas of the IoT problem universe-Connected Assets and Connected Operations. You learned to design the approach and draft the blueprint for a problem using the problem solving framework. We leveraged a real IoT use case from the manufacturing industry where we tried to solve the problem of improving the quality of the manufactured product.

In Chapter 3, using the R software, we practically attempted to solve the business use case we defined and designed in Chapter 2. You learned...

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Author (1)

author image
Jojo Moolayil

Jojo Moolayil is a data scientist, living in Bengaluru—the silicon valley of India. With over 4 years of industrial experience in Decision Science and IoT, he has worked with industry leaders on high impact and critical projects across multiple verticals. He is currently associated with GE, the pioneer and leader in data science for Industrial IoT. Jojo was born and raised in Pune, India and graduated from University of Pune with a major in information technology engineering. With a vision to solve problems at scale, Jojo found solace in decision science and learnt to solve a variety of problems across multiple industry verticals early in his career. He started his career with Mu Sigma Inc., the world's largest pure play analytics provider where he worked with the leaders of many fortune 50 clients. With the passion to solve increasingly complex problems, Jojo touch based with Internet of Things and found deep interest in the very promising area of consumer and industrial IoT. One of the early enthusiasts to venture into IoT analytics, Jojo converged his learnings from decision science to bring the problem solving frameworks and his learnings from data and decision science to IoT. To cement his foundations in industrial IoT and scale the impact of the problem solving experiments, he joined a fast growing IoT Analytics startup called Flutura based in Bangalore and headquartered in the valley. Flutura focuses exclusively on Industrial IoT and specializes in analytics for M2M data. It is with Flutura, where Jojo reinforced his problem solving skills for M2M and Industrial IoT while working for the world's leading manufacturing giant and lighting solutions providers. His quest for solving problems at scale brought the 'product' dimension in him naturally and soon he also ventured into developing data science products and platforms. After a short stint with Flutura, Jojo moved on to work with the leaders of Industrial IoT, that is, G.E. in Bangalore, where he focused on solving decision science problems for Industrial IoT use cases. As a part of his role in GE, Jojo also focuses on developing data science and decision science products and platforms for Industrial IoT.
Read more about Jojo Moolayil