SMART CROP PROTECTION SYSTEM

This project presents Smart Crop Protection, a real-time monitoring system that leverages computer vision and IoT to safeguard agricultural fields.An ESP32-CAM module is used to capture a continuous video stream of the crop environment, which is then processed on a laptop using a YOLO-based object detection model.The system is trained to identify specific objects such as healthy marigold flowers, diseased or damaged ones, and unauthorized human intruders.Upon detection of a threat or anomaly, the system instantly triggers an alert to the user through the Blynk IoT platform.This setup ensures timely notifications and enables proactive crop management with minimal human intervention.The proposed solution offers a cost-effective and scalable approach to crop surveillance, combining edge device streaming, AI-based object classification, and real-time mobile alerts to enhance agricultural productivity and security.

Publication Details

Journal
International Research Journal of Modernization in Engineering Technology and Science
Published
2025-09-19
DOI
https://doi.org/10.56726/irjmets75726
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

SMART CROP PROTECTION SYSTEM

International Research Journal of Modernization in Engineering Technology and Science
Smart Agriculture and AI
article

SMART CROP PROTECTION SYSTEM

article en

Abstract

This project presents Smart Crop Protection, a real-time monitoring system that leverages computer vision and IoT to safeguard agricultural fields.An ESP32-CAM module is used to capture a continuous video stream of the crop environment, which is then processed on a laptop using a YOLO-based object detection model.The system is trained to identify specific objects such as healthy marigold flowers, diseased or damaged ones, and unauthorized human intruders.Upon detection of a threat or anomaly, the system instantly triggers an alert to the user through the Blynk IoT platform.This setup ensures timely notifications and enables proactive crop management with minimal human intervention.The proposed solution offers a cost-effective and scalable approach to crop surveillance, combining edge device streaming, AI-based object classification, and real-time mobile alerts to enhance agricultural productivity and security.

International Research Journal of Modernization in Engineering Technology and Science
Openalex Percentile: Top 81%
Smart Agriculture and AI
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