AgriEnIcs

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Project Name

    Electronic Platform to Monitor Cattle Health and Milk Quality

Project Members

    • Project Investigator : Dr.Hena Ray
    • Project Lead  : Devdulal Ghosh 

Collaborators

    ICAR - NDRI Kalyani, Nadia, West Bengal

    • Dr. Sitangsu Mohan Deb (PI-NDRI)
    • Dr. Ajoy Mandal(Co-PI-NDRI)
    • Dr. M. Karunakaran(Co-PI-NDRI)
    • Dr. Champak Bhakat(Co-PI-NDRI)

     

    Electrical Engineering Department, IIT Kharagpur, WB, India

    • Dr. Karabi Biswas(PI-IIT)

     

     


Background

The role of the dairy sector is essential for the development of the country, especially the rural economy. Dairy can contribute immensely to value-added services and the food processing industry in the country. The ability to create entrepreneurship among the educated rural youth is also very high in these sectors. Consumer demand for milk and milk products increases day by day as the quality of life has improved in urban and semi-urban areas. These sectors can provide supplementary income and alternative livelihood, especially for less land and employment opportunities during the non-agricultural season, and mitigate natural calamities like drought. India continues to be the largest producer of milk in the world. Milk production during 2016-17 and 2017-18 was 165.4 million tonnes and 176.3 million tonnes, respectively, showing annual growth of 6.62%. The per capita availability of milk was around 375 grams per day in 2017-18.

Objective

The major objectives of this proposed project are:

  • IoT framework for cattle health monitoring for studying the cattle Physiological parameters and behaviour (such as pulse, temperature, respiration and rumination/ mastication rate of cattle) for early disease prediction.
  • Heat detection in cattle.
  • EC based sensing for disease detection of cattle at PoC level.
  • Analytics towards Smart Dairy Management.

Deliverables

The perceived major outcomes of this proposed project are:

  • A sensor-based IoT network platform to capture, monitor, and analyze each individual cow's physiological parameters and behaviour 24x7.
  • A stand-alone device for early detection of sub-clinical mastitis through instant analysis of milk.
  • A decision support tool in the form of a Computer software / mobile App for efficient management of the dairy farm.