Back close

A Cyber-Physical System for Leak Detection in Water Distribution Networks

School: School of Engineering, Coimbatore

Funded by:ICPS Division of DST
A Cyber-Physical System for Leak Detection in Water Distribution Networks

The goal of the proposed project is to develop an efficient Cyber-Physical System for providing solutions for sustainable water management. This project aims to develop solutions and a testbed for monitoring water usage and leaks, and improve efficiency of waste water treatment plants. Towards this we integrate intelligent algorithms and modeling from the cyber perspective, efficient energy management, novel wireless communication node design and placement for the development of intelligent sensing and actuation techniques. Development of novel water network models and simulations to support development of efficient algorithms for leak detection, and a prediction of spread of contaminants is a major thrust in this project. The testbed comprises of sensing and communication nodes at different points in the system for monitoring water usage and leaks and quality of the recycled water. The data from different nodes will be processed in a distributed manner and this processing is designed to be efficient. Intelligent data analytics and decision algorithms will be employed to derive actuation signals which are wirelessly transferred to the hardware controllers.

Related Projects

Development and Prototyping of ICT enabled Smart Charging Network Components
Development and Prototyping of ICT enabled Smart Charging Network Components
Development of a Model for Evaluation and Assessment of Meanness of SMEs and Effective Large-scale Implementation of Lean Strategies.
Development of a Model for Evaluation and Assessment of Meanness of SMEs and Effective Large-scale Implementation of Lean Strategies.
Amrita Automotive Technology Center (AATC)
Amrita Automotive Technology Center (AATC)
Smart Water Management
Smart Water Management
Malware detection using FPGA, Sandboxing and Machine Learning
Malware detection using FPGA, Sandboxing and Machine Learning
Admissions Apply Now