Let’s first understand what is cognitive computing. Cognitive computing are systems that are designed to make computers think and learn like the human brain. Similar to an evolution of a human mind from a newborn to teenager to an adult, where new information is learned and existing information augmented, the cognitive system learns through the vast amount of information fed to it. Such a system is trained on a set of information or data so that it can understand the context and help in making informed decisions.
For example, if you look at any learning methodology, a human mind learns and understands the context. It can answer questions based on learnings and also make informed judgments based on prior experiences. Similarly, cognitive systems are modeled to learn from past set of reference data set (or learnings) and enable users to make informed decisions. Cognitive systems can be thought of as non-programming systems which learn through the set of information, training, interactions and a reference data set.
Cognitive systems in the context of IoT would play a key role in future. Imagine ten years down the line where every piece of system is connected to the internet and probably an integral part of everyday lives and information being shared continuously, how you would like to interact with these smart devices which surround you. It would be virtually talking to smart devices and devices responding to you based on your action and behaviour.
A good example can be a connected car. As soon as you enter the car, it should recognize you automatically, adjust your car seats, start the car and start reading your priority emails. This is not programmed but learned over time. The car over a period of time should also provide recommendations on how to improve the mileage based on your driving patterns. In future, you should be able to speak to devices through tweets, spoken words, gestures and devices would be able to understand the context and respond accordingly. For instance, a smart device as part of connected home would react differently as compared to devices in a connected car.
For a connected home, a cognitive IoT system can learn from you, set things up for you based on your patterns and movements, be it waking you up at the right time, start your coffee vending machines, sending you a WhatsApp message to start the washing machine if you missed to start it based on your routine or take care of the home lighting system based on your family preferences. Imagine putting a smart controller and set of devices around your home, which observes you over a period of time and start making intelligent decisions on Day 10 and continuously learn from you and your family interactions.
From an implementation perspective, at a very high level, building a cognitive platform requires a combination of various technologies like machine learning, natural language processing, reinforcement learning, domain adoption through various techniques and algorithms apart from the IoT stack capabilities that we have discussed earlier. The cognitive platform layer should enable us to analyze structured, semi-structured and unstructured information, perform correlations, and derive insights.
This is one of the areas where we would see a lot of innovation and investment happening in future and would be a key differentiator for connected products and extension to one’s digital lives.