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Amrita Students Win CISCO’s Great Digital India Challenge

April 26, 2016 - 2:05
Amrita Students Win CISCO’s Great Digital India Challenge

Amrita Students wo​n Cisco’s first-ever “Great Digital India Challenge – iDeate” – an event focused on Internet of Things (IoT​) based ideation challenge for India. The first prize for the project SMART WATER includes Rs. 2,50, 000 and was awarded to Amrita School of Engineering Coimbatore’s Akshay, Surya, Parthasarathy and Murali Siva, 3rd year B.Tech. Electrical and Electronics Engineering students. They were mentored by Dr. Shriram K. Vasudevan​​, ​Assistant Professor, Department of Computer Science, Amrita School of Engineering, Coimbatore​.

This student project is on its way to becoming a start-up with help from Amrita TBI. The challenge spanned across over 40 of India’s top universities. ​

SMART WATER

​​​Monitoring water bodies such as lakes, ponds and reservoirs at regular intervals of time by analyzing the quality of water present in them, is an essential process that needs to be followed all over the world in order to abate the growing exploitation rate of fresh water.​

Existing manual-sampling techniques consume much time, money and labour. Moreover, when this process has to be done in a large scale​, there is a huge possibility for inaccuracies in the results obtained as humans are liable to make mistakes, especially when the data is too large for them to handle. In order to rectify the defects of the traditional sampling method, remote sensing technology was introduced to monitor the quality of water, but the accuracy of data obtained completely depends upon the number of nodes installed. Advancements in the fields such as data analysis, autonomous boats, machine learning and IOT in the past made it possible for us to monitor the quality of water without implementing sensor nodes. 

The team proposed a novel technique to collect the various parameters of water (pH, dissolved oxygen, temperature, conductivity, etc.) only at certain locations of the water body that have to be analyzed, and to generate a hypothesis function through machine learning that would predict the parameter values at all the other locations. A technique also was framed that would generate the quality state (choropleth map of each parameter) of the water body after a month, or even a year. This methodology enables us to foresee the future state of the water body in advance so that necessary measures can be taken to save the water bodies. This is a novel technique and likely the first of its kind. The prototype was successfully built and tested in many water resources starting from the university swimming pool to Ukkadam Lake.

​The team has special permission from Coimbatore Water Board and the Board has appreciated the effort and given them support to use any of the water resources for testing the product. 

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