Year: 2025
Type: article
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.
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4414349665
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