The Internet of Things(IoT) represents a vision in which the Internet extends into a real world embracing everyday objects. The Physical items are no longer disconnected from the virtual world, but they can be controlled remotely and also serve as physical access points to Internet services. An Internet of Things makes computing truly ubiquitous and the early expectations of any new technology almost always surpass what is really achievable. Moreover, IoT has hit an inflection point in the minds of business executives across the globe. The very high level research challenges might be “IoT design”, but this includes a number of lower level research challenges such as Architecture, Interoperability and Scalability, M2M communication, Security, Connectivity, Compatibility , Longevity and Intelligent Analysis. IoT educate and train the students to develop Smart Cities, Smart homes, Smart Cars making use of the latest upcoming technologies.
The advancements in digital technologies had led to the abundance of Image datasets, various Image processing techniques to understand and deal with complex problems and challenges in adverse conditions in the image acquisition process, occlusion, objects with complicate shapes, with topological variations or undergoing complex motions. Computer Vision harnesses the power of complex Image Processing techniques to extract meaningful features from a given image or video samples. The students are continuously motivated which opens various avenues to do research in the fields like Medical imaging, Steganography, Video Surveillance, Forensic Analysis and Social Network analysis.
With the emergence of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. Machine learning techniques will be helpful to get insight, patterns and for better strategic decision making. Machine Learning deals with Pattern Recognition and Computational Learning in AI systems using sophisticated data-prediction algorithms and Artificial Neural Networks . The combination of Machine Learning algorithms is found in various applications like Face recognition, Gesture recognition, Fraud detection, Motion Sensing using Camera, Pattern recognition and Security Footage. The students are encouraged to focus their research in current emerging trends like robotics, Internet of Things, Big Data and deep learning
As worldwide systems extend the interconnection of universal information network, the smooth activity of communication and computing arrangements becomes vital. However, repeating attacks as virus and worm assaults and the achievement of criminal assailants delineate the shortcoming in current data advances and the need to give increased security in the network. Network security issue for the most part incorporates and organize network and information security. In particular, it alludes to the unwavering quality of system framework, classification, uprightness and accessibility of information data in the network. With this, the students are motivated in research, presents the system and network security advancements principally in detail, including verification, information encryption innovation, firewall innovation, interruption discovery framework , antivirus innovation and virtual private system. System security issue is identified with each system client, so the students must put a high incentive upon arranging security assaults and guarantee that the entire system is secured.
Big Data refers to all the data that is being generated across the globe at an unprecedented rate. This data could be either structured or unstructured. The tools used to store and analyze Big Data are Hadoop, Hive, HBase, Sqoop, Pig etc. The aspirants will focus on the Big Data applications in making digital India implemented in various sectors both public and private through activities like call logs, mobile banking transactions, online user generated content like blog posts and Tweets, online searches, satellite images into actionable information which require computational techniques to unveil trends and patterns within and between these extremely large socioeconomic datasets.
Cloud Computing has provided Big Data with a way to store and retrieve massive amount of information. It has evolved from personal cloud storage to entire organizations moving all of their data to the cloud. In the research market, cloud simulators are widely used by research scholars without paying fees to any cloud service provider. Using cloud simulators, researchers can execute their algorithmic approaches on a software-based library and can get the results for different parameters including energy optimization, security, integrity, confidentiality, bandwidth, power and many others. The students will focus and make some cloud computing models for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Robots are becoming an important fixture in our day-to-day life and also becoming a revolutionary based on innovative technologies. It is a platform in which the students are engaged in ground-breaking work in mechanism design, sensors, computer vision, robot learning, Bayesian state estimation, control theory, numerical optimization, biomechanics, neural control of movement, computational neuroscience, brain-machine interfaces, natural language instruction and physics-based animation. The students will currently focus to define large-scale joint initiatives that will enable us to leverage our multi-disciplinary expertise to attack the most challenging problems with the help of robotic automation in real world.