Animal Intrusion Detection Using ESP32 Cam and Open CV


Authors : Dr. Arulmurugan L; Pradeep S; Nikhil Raghav V; Bharath Kumar S P

Volume/Issue : Volume 8 - 2023, Issue 10 - October

Google Scholar : https://tinyurl.com/52nm9mwn

Scribd : https://tinyurl.com/yc72bdtu

DOI : https://doi.org/10.5281/zenodo.10049773

Abstract : In forest and agricultural field human and animal conflict is a major problem where enormous amount if resources are lost and human and animal life are endangered. Due to this animal lives are endangered. People lose their crops, cattle and in some extreme cases they lose their lives. In current era of continuously developing IOT sensors and cloud technology, Image processing in remote areas became easy and cheap. To tackle this problem, we have developed a system with cameras and remote cloud server to capture live footage of area to be protected and processing the footage in a live server to detect animal intrusion. For hardware components, we have used ESP32 camera module with Wifi to capture live footages. The captured footage is sent to a remote server or PC for further processing. A yolov5 based pre-trained algorithm is used for object detection. To achieve maximum accuracy the algorithm is trained with thousands of animal photos multiple times until desired accuracy is reached (~98%). The footage is processed and based on the type of animal detected a message or alert is sent to the farmer or forest department from the server and a speaker can be used to scare the animals.

Keywords : Animal Detection, ESP32 CAM, Yolov5.

In forest and agricultural field human and animal conflict is a major problem where enormous amount if resources are lost and human and animal life are endangered. Due to this animal lives are endangered. People lose their crops, cattle and in some extreme cases they lose their lives. In current era of continuously developing IOT sensors and cloud technology, Image processing in remote areas became easy and cheap. To tackle this problem, we have developed a system with cameras and remote cloud server to capture live footage of area to be protected and processing the footage in a live server to detect animal intrusion. For hardware components, we have used ESP32 camera module with Wifi to capture live footages. The captured footage is sent to a remote server or PC for further processing. A yolov5 based pre-trained algorithm is used for object detection. To achieve maximum accuracy the algorithm is trained with thousands of animal photos multiple times until desired accuracy is reached (~98%). The footage is processed and based on the type of animal detected a message or alert is sent to the farmer or forest department from the server and a speaker can be used to scare the animals.

Keywords : Animal Detection, ESP32 CAM, Yolov5.

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