PROJECT EXPO 2025

Project Expo 2025: Showcasing Innovation in Agricultural Technology

Coimbatore, Tamil Nadu – January 30, 2025, was a significant day for innovation as SNS College of Technology hosted Project Expo 2025. The event brought together students, faculty, and industry experts to present cutting-edge projects and ideas, fostering a dynamic exchange of knowledge and technological advancements.

One of the standout exhibits was the Plant Disease Identifying Robot, developed by Team PHYTODETECT, consisting of Rahul Prasant S, Arikaran K, Elakkiya T, Srimathi S S, and myself. Our project aimed to revolutionize agricultural health monitoring by integrating artificial intelligence (AI), computer vision, and robotics to detect plant diseases with precision and efficiency.

Plant health plays a crucial role in ensuring high crop yields, yet traditional disease detection methods are often slow and prone to errors. Our robot addresses this challenge by using high-resolution cameras, sensors, and AI algorithms to analyze plant conditions in real-time. The system captures images, processes them through machine learning models trained on extensive plant disease datasets, and identifies early signs of infection. In addition, infrared and thermal sensors help detect plant stress that may not be visible to the human eye. The robot classifies plants as healthy, infected, or at risk and provides farmers with real-time recommendations for appropriate treatment. GPS and GIS technology enable the robot to navigate fields autonomously, ensuring thorough and efficient monitoring.

The benefits of this technology are substantial. Early detection prevents widespread crop damage, AI-powered analysis enhances accuracy, and targeted pesticide application supports sustainable farming practices. Additionally, the system reduces the dependency on manual labor and offers valuable data insights to aid in better farm management. Despite its advantages, the technology faces challenges such as high initial costs, the need for advanced AI training, and adaptation to various crop types and environmental conditions. Future enhancements may include integrating Internet of Things (IoT) technology for real-time disease monitoring, refining AI models for improved accuracy, and developing cost-effective versions suitable for small and medium-scale farmers.

The enthusiastic response at Project Expo 2025 reaffirmed the potential of our Plant Disease Identifying Robot to transform precision agriculture. The event provided an excellent platform to showcase our innovation and gather valuable feedback for further development. Encouraged by this experience, we remain committed to advancing sustainable and efficient farming solutions through technological innovation.

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