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. The lab aims 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.

Funded Project Details

Sr. No. Title of the Project Funding Agency Amount Sanctioned in Lakhs (Rs.) Status
1 A Framework for event modelling Detection for Smart Building using vision System DST 40.64 Completed

Equipment Details

Sr. No. Component List No. of Items
1 CP PLUS 4MP OUT DOOR IPCAMERA 36MM 4
2 CP PLUS SPEED DOME 30XOPTICAL IP CAMERA 1
3 UTEP 8 PORT POE SWITCH 30 V WITH CCTV MODE 1
4 DAHUA 4K 2 SATA 16CHNVR 1
5 JOYSTICK IP SPEED DOME CAMERA CP PLUS 1
6 FLUKE THERMAL IMAGER TiS 40 1
7 HP DL380 Gen9 2U Rack Server 1
8 Lenova Work Station 4
9 SATA 4 Tb 1
10 SEAGATE 1 Tb ,External HDD 1
11 Rasberry Pi Camera moduleV-2-8 Mega Pixel 1080p 1
12 SEAGATE 1 Tb Backplus Slim 1
13 Logitech c270 Webcam 3

Projects

  1. A Mobile Based Framework for Detecting Objects using SSD-MobileNet in Indoor Environment
  2. Object Detection, annotation and monitoring in Smart Environment using Thermal Images
  3. Video-Based Fire Detection by Transforming to Optimal Color Space
  4. Dynamic and Chromatic Analysis for Fire detection and Alarm raising using Real-time Video Analysis

Publications

  1. Srishilesh P S, Sanjay Tharagesh R S, P.Sridhar, Dr.Latha Parameswaran, Senthil Kumar Thangavel,Dynamic and Chromatic Analysis for Fire Detection and Alarm Raising Using Real-Time Video Analysis",Proceedings of 3rd International Conference On Computational Vision and Bio Inspired Computing,2019.
  2. Kavin Kumar D, Latha Parameswaran,Senthil Kumar Thangavel,"A Computer Vision Based Approach for Object Recognition in Smart Buildings",Proceedings of 2nd International Conference On Computational Vision and Bio Inspired Computing,2018.
  3. Thanga Manickam M,Yogesh M, P.Sridhar ,Senthil Kumar Thangavel ,Latha Parameswaran,"Video-Based Fire Detection by Transforming to Optimal Color Space",Proceedings of 3rd International Conference On Computational Vision and Bio Inspired Computing,2019.
  4. Sridhar P,Latha Parameswaran,Senthil Kumar Thangavel,"An Efficient Rule Based Algorithm for Fire Detection on Real Time Videos",Proceedings of the first international conference on Intelligent Computing,2018.
  5. K S Gautam, Latha Parameswaran, Senthil Kumar Thangavel,"Computer Vision based Asset Surveillance for Smart Buildings",Proceedings of the first international conference on Intelligent Computing,2018.
  6. K S Gautam, Latha Parameswaran, Senthil Kumar Thangavel,"A Cascade Color Image Retrieval Framework for Image Retrieval",Proceedings of 2nd International Conference On Computational Vision and Bio Inspired Computing,2018.
  7. Harsh Motka, Latha Parameswaran, A Vision Based Approach For Anomaly Detection In Smart Environments Using Thermal Images”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume-8 Issue-7, May 2019, Page No.2838-2844, ISSN: 2278–3075 (Online).
  8. Sudipta Rudra,Senthil Kumar Thangavel,"A Robust Q-Learning and Differential Evolution Based Policy Framework for Key Frame Extraction", Springer Advances in Intelligent Systems and Computing ,Vol.1039,pp.716-728,2019.
  9. Padmashini, R. Manjusha, , Latha Parameswaran, Vision Based Algorithm for People Counting using Deep Learning, International Journal of Engineering and Technology"(UAE),Volume 7, issue 3, pp 74-80, 2018