Why IoT has turned from a competitive trend to a means of survival?

We have already stepped into a world where exists virtual communication, Siri and Alexa doing half of the human efforts. Now that we have begun this trend of slashing down human effort, why not doing the same with everything else?

This is what we now call as the Internet of Things which means a network of physical devices, vehicles, electronics, sensors, software and every other object around you that are digitally connected and assists collection and exchange of data.
In its true essence, IoT technology refers to the Universe of devices with in-built sensors that provide data for further transmission in a much more convenient way.

You don’t have to wait for data to reach the desired place that will delay your decisions anymore!

An increasing number of physical objects are being connected to the internet with time, for example, security sensors, smartwatches, and even household appliances like washing machines now can communicate and transfer data over time. Today, companies must leverage the latest technologies simply for survival because what were luxuries earlier are needs now. It is here to impact all industries, from logistics to manufacturing to healthcare – we are about to enter a connected world. Not just organizations, IoT has also led to massive empowerment of the consumers by providing greater control of household systems and appliances, washing clothes is no more a human task!

But the question is how to drive value from IoT, how to make it work in our favor?

It is a mere vision for most of the industries currently, there’s a gap between reimagination and execution that needs to be bridged.IoT will produce a treasure trove data – data that can sash the downtime in production with the help of real-time analysis and decisions, data that can help cities predict an epidemic using thein-built sensors in devices, data that can help manufacturing companies predict the breakdown of a machine with sensors installed in it.The possibilities that IoT bring to the table are endless. But to get these results the unstructured, messy data has to be organized and analyzed.

As the network of connected devices will go on expanding the sheer volume of data produced will be huge, and to derive results from the data it has to analyzed efficiently and well treated, what we call as Big Data Analytics. Businesses are failing miserably in harnessing the true potential of Big Data available to them. Data is only useful when it creates action, and for that, it has to be creative and contextual. To bring in this context to the existing data comes AI (artificial intelligence). The ai-based analysis becomes critical to extract optimum value from Big Data.
But how do Big Data and AI function within the IoT technology?

AI at glance

When we say AI it means machine learning. For data to be useful it must be analyzed, which is exactly what AI does. A large volume of data is of no use to an organization if it cannot lead us to any effective decision may it be minor or major, AI makes that huge volume of data meaningful. It tries to mimic human brains, how the human brain thinks, behaves and react to the respective actions.


  • A situation is to be analyzed from a rational perspective, for which we require patterns and algorithms to drive a structured approach and generate logic-driven output.
  • Data comes from varied sources such as sensors, social media and the like, also the data is unstructured and it keeps changing.
  • AI then uses perceptions to analyze the logic and incorporate machine learning to utilize that unstructured data and bring it in a format such that useful insights can be driven from it.
  • AI applications such as image recognition, language processing, computer vision, robotics and much other leverage machine learning for deriving the accurate predictions from large volumes of data and end up taking effective and efficient decisions.

AI provides results as per consumer behavior, for example, Amazon will suggest you movies and books based on your last buy, Pandora will suggest new songs as per your existing playlist. It brings in ‘intelligent connectivity’ to the users of IoT since mere connectivity of devices will do no good until the data from those devices is analyzed in terms of what is relevant and what is not.
AI can majorly be of three types –

  • Strong AI – produce a machine whose intellectual level is indistinguishable from that of a human being.
  • Applied AI – also known as information processing, aims to produce commercially viable smart systems.
  • Cognitive Simulation – where computers are used to test theories about how the human mind works.

Thus, AI is here to bring similar intelligence in machines that we find and consider high in humans.

How big is Big Data?

Big data is referred to as massive, unstructured and complicated data sets that are of huge importance to businesses. These data sets are so complicated that they cannot be treated with traditional data processing software. The recent developments in technology have exponentially reduced the cost of data storage and compute, making it possible to conveniently store huge volumes of data like never before. It has changed the job of marketers completely. They can obtain actionable insights to create highly effective marketing strategies by interpreting the tons of data that is available to the business.

But it is not possible to do this manually, we need Big Data Analytics to understand the market trends, gauge customer behavior and understand the standing and upcoming competition in the market.


According to statistics in the last five years, the average volume of data generated every day is 2.3 trillion gigabytes. The evolution of Big Data has provided great insights and knowledge through :

  • Adaptive Analytics – what is the appropriate action
  • Predictive Analytics – what will happen
  • Prescriptive Analytics – what should we do

But one major decision about Big Data is stored, people generally decide their medium of storage based on where their data resides currently. Cloud is gaining great popularity lately because of its ability of Vertical Scaling which increases the capacity of a server by adding resources as needed by an application, and Horizontal Scaling that allows businesses to expand hardware resources with an increase in processing requirements; making it an ideal platform to host Big Data Analytics. Cloud offers immensely high bandwidth and processing power to help Big Data applications with improved real-time processing of streaming data.

The Five V’s of Big Data

  • Volume – Organisations have a high volume of data with low density and are unstructured.
  • Velocity – The rate at which data is received and it is acted upon is what you call as velocity.
  • Variety – Data can be available in various types.
  • Variability – Data may vary from time to time and region to region.
  • Value -The value of data represents if it is relevant or not.

The primary value of data comes not in the raw form, but from the processing and analysis done on it. Thus, Big Data plays a very pivotal role in making real-time and efficient decisions.

The convergence of the Trio (IoT, AI, and Big Data)

Internet of Things has unique needs in different market segments, may it be automotive, manufacturing, power or healthcare. But one mutual fact that they share is Big Data!
And all of them want these massive unstructured data sets to be analyzed and put to use in the best possible way, and this requires Big Data Analytics to be coupled with AI. This combination is the utmost for real-time and streaming analytics and to understand customer interests in the best way. The ability to make real-time decisions, capture streaming data and add value to attributes is itself a service to logic, and this is achieved when you apply AI and Big Data Analytics together.


  • There are five basic steps in IoT – Measuring, sending, storing, analysis, acting. The most important step here is acting, which tells why to invest in an IoT technology, it is the aim you are striving.
  • But the latter can be done only when the ‘analysis’ step goes right because ultimately analysis will derive the pattern that is being followed. The more you know about anything or any situation the better decisions you can take.
  • To reap the benefits of IoT data, we need to improve the speed and accuracy of Big Data Analysis and that is done by combining it with the quantitative methodology of AI.
  • After collecting the data from various in-built sensor devices, it is put under Artificial Intelligence and machine learning, for the computer to identify what the data represents, what patterns and algorithms it follows much more reliably than humans do.
  • By combining data intelligently and by interpreting, new insights can be driven to new services, applications, and markets.

Thus, the potential of Big Data can only be realized when it is coupled with AI.


Technology today is a major driver in any business, and we are still struggling to integrate technologies with human effort. Humans and businesses generate trillions of gigabytes of data every day but to put that data to use we need to cope with the operational challenges and implement a digital strategy that works with cloud initiatives and tools. But analytics can only be done when we understand the domain well, the old computing proverb of ‘garbage in, garbage out’ cannot be applied anymore. The trio of IoT, Big Data and AI is going to take industries to a higher notch and bring revolution in a classical sense. But are we prepared for this revolution or are we still dwelling over our past legacies?