Name of the Ongoing Project | Principal Investigator and Co-investigator | Name of the Funding Agency | Project Grant / Assistance | Duration of the Project* |
---|---|---|---|---|
AYUSH Unit Converter | Dr. Senthilkumar M. | Ministry of Human Resource Development, Government of India | 1 year | |
A Behavioral Study of Ransomware – TO Develop a Generic Mitigation System | Dr.Gowtham Ramesh | Science and Engineering Research Board (SERB) | 3 years | |
Indoor Information Representation and Management System | Dr. VidhyaBalasubramanian,Dr. Latha Parameswaran | DST India | Rs. 51.3 Lakhs | 3 years |
Predictive Modeling of Complex IT systems | Mr. Prashant R. Nair, Dr. M. Sethumadhavan | DRDO | Rs. 24.1 lakhs | 1 year |
A Service – Oriented Pervasive Framework for Smart Hospitals | Dr. Vidhya Balasubramanian, Dr. G.Jeyakumar, Dr. C.K.Shyamala | NRDMS/DST | Rs 46.1 Lakhs (Rs 30 Lakhs for year1) | 24 Months |
A Framework for event modeling and detection for Smart Buildings using Vision Systems | Dr. Latha Parameswaran, Dr.T.Senthil Kumar | DST(NRDMS) | Rs 40.64 ,500 | 24 Months |
Technology inputs in promoting indigenous food recipes of Irulas and Kurumbas tribes and empowering disadvantaged youth of Masinagudi and Ebbanad village of The Nilgiri District | Dr. T. Senthil Kumar, Dr. S. Rajendra Kumar, Dr. Udhaya Kumar | Ministry of Tribal Affairs | 9,52,780 | 1 year |
A study on the utilization of student welfare schemes offered by Government of Tamil Nadu in Coimbatore district | Dr. Gowtham. R, Dr. Prakash P, Mr. M.Vamsee Krishna Kiran, Ms. R. Archanaa | Indian Council Of Social Science Research | Rs 1 Lakh | 1 year |
Automation of Transport and Building Feature Extraction using Deep Learning with Super-Resolution Enhancement of Satellite Imagery | Dr. B. Rajathilagam | ISRO-RESPOND | 28.56 | 2 years |
Faculty memebrs of the department have taken up research projects in collaboration with Amrita Institute of Medical Sciences, a multi and super speciality hospital in Cochin. The students of the specialized programme M.Tech in Computer Vision and Image Processign have an excellent opportunity to work in these real time projects. Medical Image Processing is the thrust in this research. A few of these projects are given below. These projects are an eye opener to inter disciplinary research.
AMRITA-VIRTUAL INTERACTIVE E-LEARNING WORLD (A-VIEW)
CYBER SECURITY
The department of CSE has set up a few labs in order to carry out research in the identfied thrust areas. These labs have facilites to conduct research at all levels. Students from Undergraduate and Postgraduate programmes are actively involved in this lab to do research. Also research scholars and faculty members guide these students to do research in these labs. We aim at setting up a reseach hub that would eventually become a center of excellence.
The Amrita Multidimensional Data Analytics Lab has been set up to enable research in large scale intelligent information systems. With the world facing unprecedented challenges, technology has a major role to play in efficiently solving many of them. Our goal is to develop large-scale information systems that can help tackle challenges in education, healthcare and support smart buildings and cities. Towards this we focus on end-end solutions that include designing innovative data models, scalable data management solutions, novel indexing techniques, intelligent retrieval and event-detection algorithms.
This lab was established in the year 2012 with the support of Cognizant Technology solutions, India. Amrita Cognizant Innovation Lab has been setup to conduct research in the areas of Computer Vision and Image Processing, Security, and Wireless Sensor Network.
Mobile and Wireless Networks Laboratory (MWN Laboratory) is functioning under the department of Computer Science and Engineering of Amrita School of Engineering, Coimbatore. MWN Lab caters to the needs of various hardware and software modules for Undergraduate, Graduate Students and Research Scholars of CSE, ECE and EEE departments to carry out their research works in the domain of Mobile and Wireless Networks.
SiGMA Lab is a research laboratory in the Department of Computer Science and Engineering that promotes research on Signal Processing, GPU Computing and Mobile Applications. Thrust areas include innovative signal processing applications, higher dimensional signal analysis algorithms and their adaptation to Mobile platform. Multimedia signal processing that contain structurally parallel data flows and involve iterative, computationally intensive, and time-consuming mathematical operations are the focus.
With the government of India’s focus on “Digital India”, building Smart Cities is one of its major initiative. For smart cities to be built or renovated, it is essential that the existing buildings and infrastructure become smarter. In this project we aim to develop a software framework on which applications can be developed for buildings, to respond to emergencies and disaster management. In this context we refer building to include indoor spaces (rooms/halls/closed areas) and outdoor spaces (floors, stair cases, corridors, open spaces). Pervasive systems are necessary to make existing buildings smarter and to respond to emergencies. Ability to identify critical events, assets and people and answer to queries about their location in a building is critical to many applications; integrating object recognition with spatiotemporal analysis enhances the system to handle crisis. Major aspects that are essential for such an aspect of smart building are:
In this project, we aim to make existing buildings smarter and intelligent by developing algorithms with data from low-cost vision systems. We shall also consider the standards available in OGC to model such events and represent the voluminous data.
Specific Use cases: This proposed project will be more useful in places like hospitals, large University campuses, shopping malls where a large number of people and objects move from time to time. In these places the above mentioned aspects are of high significance.
Though many researchers have developed algorithms or techniques or methods to perform event detection, object identification and tracking, most of them have developed and tested it for a known dataset (or a publicly available dataset). Very less work has been reported on such techniques for a real-time environment. Thus in Indian context, our proposed project and research will be significant, as we are planning to develop and deploy this in an existing building, thus making it become “smarter” to cater to safety of people. In precise, this work will focus on safety and security of people and objects in a building and to connect to first responders in case of emergencies.
The proposed system includes setting up cameras and vision systems in a building, developing smart applications that run over this infrastructure and the underlying database system to record events and the videos. The major components of this project would be:
Setting up vision systems: This would be required to detect events, objects, people, identify location, and monitor the infrastructure. There are a variety of cameras and vision systems available in the market such as night vision cameras, IP cameras, thermal imaging cameras, web cameras etc. Our goal is to utilize the experience we have gained from our pervious project Indoor Information Representation and Management System (IIRMS) project funded by NRDMS, DST where some work on event detection has been done [19]. Identifying suitable cameras and selecting the appropriate locations for day and night vision will be the highest priority.
Developing Applications: Once the infrastructure is set, we propose to develop efficient algorithms for object identification and tracking; unusual event detection and raising alarms/ warnings.
At the end of the project, we plan to have a complete study suggesting the best location for placing cameras/ vision systems for a smart building, a framework for configuring vision systems, a suite of algorithms to support object identification and tracking and specific events detection.
Key words: Event detection, image and video sequences, people tracking, vision systems
Objectives:
The broad objective of this project is to develop a) a framework for smart buildings that supports efficient indoor tracking algorithms for detecting events such as crowded areas, fire, smoke etc. using vision systems b) identification and tracking of moving objects over indoor spaces. This framework will complement the indoor information system developed as a part of the earlier IIRMS project funded by DST. We shall also explore integration of standards like SWE over IndoorGML and extending IndoorGML to include representation of objects and event is another important goal, which can help standardize the smart building applications. Specific objectives include the following, efficient algorithms will be developed, tested and deployed:
Specific Objective 1: Develop algorithms and build application for identifying unexpected events like locating crowded areas, fire detection, rain detection, smoke detection, electrical burst, and water burst in a given building.
Specific Objective 2: Develop algorithms and build application for identifying major assets and tracking their movement from one place to another from time to time (spatiotemporal) in this environment.
The CORE Lab is an initiative by an Interest Group from the Computer Science and Engineering department in an attempt to transfer learning process from classrooms to practical domains. The lab offers opportunities and mentorship for students to strategically approach and solve problems the Computational Thinking way. This is the first lab of its kind in the country that sets a personal timeline for students to explore, experiment and learn by integrating theory and practice using computational thinking strategies.
For details on projects, talks, research activities, etc. please contact corelab@cb.amrita.edu
With the government of India’s focus on “Digital India”, building Smart Cities is one of its major initiative. For smart cities to be built or renovated, it is essential that the existing buildings and infrastructure become smarter. In this project we aim to develop a software framework on which applications can be developed for buildings, to respond to emergencies and disaster management.