Amrita School of Engineering, Coimbatore, proudly announces the receipt of a prestigious grant from Sony’s Sensing Solutions University Program (SSUP Japan), to advance research in smart and precision animal farming. The research, led by Dr. Rammohan S, Associate Professor, alongside his esteemed co-investigators—Dr. Ananthanarayanan V., Associate Professor; Dr. Mohanraj T., Associate Professor; and Dr. Karthika R., Assistant Professor—aims to revolutionize the health and welfare of cattle through automation and sensor technologies.

A Vision for Precision Cattle Farming

The project, titled “Smart and Precision Animal Farming for the Health and Welfare of the Cattle,” seeks to develop innovative automation technologies for monitoring and improving the health of cattle. Cattle health is intricately tied to continuous monitoring of several vital signs. The impetus for this research stemmed from the realization that an automated system equipped with sensors could monitor vital signs, predict health status, and provide timely care to cattle. This system will offer farmers the tools they need to ensure optimal health outcomes for their herds.

A Technological Leap in Cattle Health Monitoring

The primary objective of this research is to design a system that integrates smart collars worn by cattle with a farm-assist robot. These collars, equipped with sensors, will continuously track the health of cattle, while the farm-assist robot will support operations such as breath analysis, data transfer, and even feeding. The project’s impact will extend far beyond immediate health tracking, contributing to the development of a comprehensive database for standardizing diagnostic procedures and advancing the field of cattle health monitoring globally.

Key Deliverables and Outcomes

The three-year research program, spanning from 2022 to 2025, will focus on delivering tangible innovations, including:

• Farm-Assist Rover: A robot capable of performing multiple farm operations, including breath analysis of cattle and data transfer from the collars.
• Health Data: Practical data on biomarkers and health indicators from the cattle, contributing to the standardization of diagnostic processes and the creation of a valuable database for future studies.
• Algorithms for Visual Servoing: The development of algorithms that allow the rover to identify and examine cattle, enhancing the precision and effectiveness of the monitoring system.
• Meta-Data and Source Codes: Comprehensive meta-data, demo binaries, and source codes related to the rover’s operations will be made available for further study and development.

Emerging Areas and Future Impact

This research is set to make significant contributions in several key areas:

• Global Advancement of Cattle Health Monitoring: The project will help accelerate the technological readiness of global cattle health monitoring systems, enabling more accurate and timely assessments of cattle well-being.
• Customized Health Solutions: The data generated by the rover will enable the development of tailored solutions for individual cattle, improving care and welfare.
• Emerging Technologies: The project will advance novel technologies, such as visual servoing and tactile perception, which have wide-ranging applications in robotics and animal care.
• Farmers as End Users: The integration of the rover and collar system will allow animal farmers to provide care to cattle quickly and efficiently, improving overall livestock management.
• Technological Innovation: The research will inspire future projects in allied fields, such as robotic solutions for animal health, customized farm equipment, and AI-driven diagnostics.

Exploring Future Research Possibilities

Beyond the current scope, the research team is already exploring several exciting areas for future development:

• Eye Health Monitoring: The team is working on developing algorithms to examine the eyes of cattle to assess their health, implementing visual servoing on the rover to track eye movements.
• Animal-Robot Interaction: The project will explore the use of tactile sensing, breath detection, and vocalization monitoring to enhance the interaction between robots and cattle.
• AI-Based Machine Learning Models: The team plans to implement AI-based machine learning models on Sony Spresense boards to predict cattle health and detect early signs of distress, establishing global standards for health prediction in livestock.

A Collaborative Effort Towards Innovation

With the support of Sony’s SSUP Japan, this research will not only contribute to advancements in animal health monitoring but also foster the development of cutting-edge technologies that will benefit both the academic community and the agricultural sector. The Amrita School of Engineering team is proud to be at the forefront of this innovative research, helping to create a smarter, more efficient future for animal farming worldwide.