Automated Disease Detection and Control for Smart Aquaponics Systems

Main Article Content

Mamatha K R
Rashmi N
Thejaswini S
Ramesh Babu N
Dr. Girish H

Abstract





Aquaponics is a highly efficient, symbiotic system that combines the principles of aquaculture (raising aquatic animals) and hydroponics (growing plants in nutrient-rich water) to create a sustainable agricultural environment. This innovative approach leverages the waste produced by aquatic animals to provide organic nutrients for plant growth, while plants, in turn, filter and purify the water, creating a self-sustaining cycle. The primary objective of this system is to drive advancements in the agricultural sector through the integration of emerging technologies, making sustainable farming more accessible and resource-efficient. A key feature of this system is its built-in disease detection and monitoring capabilities. Through the use of sensors, computer vision, and machine learning, the system actively monitors the health of plants, detecting subtle changes in leaf color, structure, and other visible symptoms that may indicate disease. When a potential disease is identified, the system automatically generates a detailed report outlining the affected areas, potential disease types, and recommended treatments. This report is then instantly sent to the owner via a mobile application, ensuring that they are alerted promptly to any health issues within the aquaponic ecosystem. By identifying diseases at an early stage, the system enables timely intervention, thereby preventing disease propagation and reducing the risk of widespread crop loss. This proactive approach to plant health management not only safeguards the productivity of the aquaponic system but also contributes to overall food security. With its emphasis on sustainability, smart monitoring, and efficient resource utilization, this aquaponics system represents a significant step forward in the modernization of agriculture, embodying a vision for a technology-driven, eco-friendly future in food production. This abstract covers the purpose, technology integration, disease detection, and benefits, creating a comprehensive overview. Let me know if you’d like adjustments.





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How to Cite
Mamatha K R, Rashmi N, Thejaswini S, Ramesh Babu N, & Dr. Girish H. (2024). Automated Disease Detection and Control for Smart Aquaponics Systems. Educational Administration: Theory and Practice, 30(1), 4628–4633. https://doi.org/10.53555/kuey.v30i1.8293
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Articles
Author Biographies

Mamatha K R

Dept. of ECE, B M S Institute of Technology and Management Bengaluru, Karnataka, India

Rashmi N

Dept. of ECE, B M S Institute of Technology and Management Bengaluru, Karnataka, India

Thejaswini S

Dept. of ECE, B M S Institute of Technology and Management Bengaluru, Karnataka, India

Ramesh Babu N

Dept. of CS&BS, K S School of Engineering and Management, Bengaluru, Karnataka, India.

Dr. Girish H

Professor, Department of ECE, Cambridge Institute of Technology, Bangalore, Karnataka, India.