We are a dedicated team of diploma students working together on the innovative project “AI Enabled Smart Agro Intrusion Monitoring and Alerting System.”
Our project aims to provide smart security and monitoring solutions for agricultural fields using AI, IoT, motion detection, and mobile technologies. The system is designed to detect intrusions, monitor field activities, and send alerts to farmers in real time, helping to reduce crop damage and improve farm security.
Our team combined expertise in hardware integration, mobile application development, motion software configuration, and testing to successfully develop this smart agriculture solution.
Role: Raspberry Pi & Hardware Engineer
Roll No.: 230810207021
Email: sachinchoudhary2003@gmail.com
Sachin handled the core hardware architecture of the project. He worked on Raspberry Pi integration, sensor connectivity, hardware setup, power management, and device communication. He also managed the physical implementation of the intrusion detection system and ensured smooth interaction between hardware components and the software modules.
Role: App Development & Testing
Roll No.: 230810207009
Email: badalparmar143p@gmail.com
Badal worked on application development, system testing, and feature integration. He contributed to improving system performance, testing alert functionalities, fixing technical issues, and ensuring that the application worked smoothly with the monitoring system. He also assisted in user-side functionality and overall project workflow testing.
Role: Mobile App Developer
Roll No.: 230810207020
Email: dhimanritu62@gmail.com
Ritika focused on designing and developing the mobile application interface for the project. She worked on creating a user-friendly UI, integrating notification features, and improving accessibility for farmers and users. Her contribution helped make the system easier to monitor and control remotely through mobile devices.
Role: Motion Software Configuration
Roll No.: 230810207007
Email: anjalipathania099@gmail.com
Anjali handled the motion detection software configuration and monitoring setup. She worked on configuring motion-based detection, optimizing camera monitoring features, and ensuring accurate intrusion sensing. She also contributed to software calibration and real-time monitoring functionality.
Our vision is to develop smart and affordable agricultural security systems that can help farmers protect crops and monitor their fields efficiently using modern AI and automation technologies. Through this project, we aim to promote the use of intelligent systems in agriculture for better safety, productivity, and innovation.