Co-Project Incharge:Manoj Guleria, Aneena John Panicker, Rayappa Raja S.R
Thematic Area: Agriculture & Risk Management
Project Guides: Dr. B. Soundarajan and Dr. Rekha Manoj
International Partner: Mathew Falcone, University at Buffalo, U.S.
Amrita Partner: Manoj Guleria, Department of Electrical and Electronics Engineering, Aneena John Panicker, and Rayappa Raja S.R., Department of Civil Engineering
Village: Dewgain, Jharkhand
Project Duration: 1 month (also part of Live-in-Labs® 5th semester course)
Identified Challenge & Aim:
Farmers have been unable to meet irrigation requirements during the summer months in Dewgain due to insufficient availability of water. This has lead to low crop yields and a drastic decrease in income during these months. This project examines alternative methods for water conservation and management of available water resources via wireless sensor networks and is a continuation of Traditional Irrigation Systems on Agricultural Outcome
Before heading the the field, the student team met with the project guides to clearly plan out the additional data they wanted to collect and the subsequent methodology. After consulting villagers, the team chose an experimental site with the aim of testing two independent variables: the type of irrigation (rainwater, channel, or drip) and the method of determining irrigation frequency. The team did a site survey of the village and surrounding agricultural areas, searching for distinct soil types by visual observation of soil color, texture, and land use. The team then conducted sensor tests on several sites throughout Dewgain, with a focus on the area around the experimental plot.
After several brainstorming sessions, the team felt it was important to create awareness among villagers on new technologies in farming such as drip or diffuser methods to use water efficiently. After inputs from the villagers, students came up with a design of an Internet of Things (IoT) framework to improve agriculture yield by effectively scheduling irrigation and fertilization based on a crop’s water requirements, the surrounding environmental conditions, and daily weather forecasts.