Keynote: Next generation internet, data science, & soft computing

The Internet used today can be described as a network of computers, which connecats one user to others around the globe. Most of the usage and application of the “Internet of Computers” involves human intervention. The future of the Internet would be — a world where manual intervention for the objects on the network could be minimized and its functionalities would be automatic and smart. This internet would not only connect computers and smart phones; it would be a network of smart objects, the “Internet of Things”. These “things” would be smart enough to sense, process and decide a corresponding action, Examples include smart appliances (refrigerator, lights, air conditioners), traffic signals, smart body monitors, etc. The individual objects along with the network would collect process and exchange data strategically. This interconnected network along with all the smart objects working together in correspondence with each other form a larger “Cyber Physical System” (like smart cities, smart hospital, etc.). A working CPS would generate tons of data, hence efficient processing and effective use of this data is very crucial. There will be data from everywhere like climate data, social network data, video data, medical data, scientific data, etc. Storing these data for analytics may not always be feasible and analyzing them in real time will also be too difficult. Traditional analysis tools are not well suited to capture the complete essence of this massive data. The volume, velocity and variety is too large for comprehensive analysis, and the range of potential correlations and relationships between disparate data sources are too great for any analyst to test all hypotheses and derive all the value buried in the data. Some algorithms already have good capability of letting computers do the heavy thinking for us in case of smaller data. But, we are striving for more to deal with large volumes of such data in a short time. Therefore, we need to revisit old algorithms from statistics, machine learning, data mining and big data analytics and improvise them to tame such big data. Major innovations in big data analytics are still to take place; but, it is believed that emergence of such novel analytics is to come in near future from various domains. Soft computing tools, nature inspired algorithms, are likely to play a key role in this regard.