Research Article
Development of a Sustainable and Cost-Effective Automatic Milking System to Enhance Dairy Farming Efficiency
@INPROCEEDINGS{10.4108/eai.28-4-2025.2358036, author={Yamunarani T and Jayanthi T and Kanimozhi G and Bharathkumar R and Jeevitha V and Jagadeesh S}, title={Development of a Sustainable and Cost-Effective Automatic Milking System to Enhance Dairy Farming Efficiency}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part II}, publisher={EAI}, proceedings_a={ICITSM PART II}, year={2025}, month={10}, keywords={automated milking system internet of things milk flow weight management dairy farming sustainable automation}, doi={10.4108/eai.28-4-2025.2358036} }- Yamunarani T
Jayanthi T
Kanimozhi G
Bharathkumar R
Jeevitha V
Jagadeesh S
Year: 2025
Development of a Sustainable and Cost-Effective Automatic Milking System to Enhance Dairy Farming Efficiency
ICITSM PART II
EAI
DOI: 10.4108/eai.28-4-2025.2358036
Abstract
The objective of this research is to develop a Sustainable Cost-Effective Automated Milking System employing renewable energy in order to enhance dairy farming efficiency. The proposed system integrates IoT-based automation to monitor and control the process in real time, and its efficiency is compared to traditional milking processes. This research involves two groups: Group 1 constitutes traditional milking systems subjected to 30 samples, and Group 2 designates the developed automated system subjected to 30 samples. Parameters like milk flow rate, weight of milk, energy efficiency, and operational reliability were studied. Major parts of the system are a 20 kg load cell, flow sensor, Arduino UNO microcontroller, and renewable energy sources to ensure maximum automation and sustainability. Result indicates that milk flow and weight monitoring with an error tolerance of less than 0.01%. The integration of renewable energy lowered operational expenses by 30%, while automation reduced human intervention by 80%. The system prevented overflow at all times and increased milking efficiency with an average accuracy of 99%. Thus, in summary, this study proves the proposed system to be a sustainable, dependable, and cost-effective alternative for small-scale dairy farmers that offers major advantages over traditional systems.
