Development of an Internet of Things-Based Animal Trap Using Motion Sensors and Camera:  A Case Study on Rat Traps

Armand Maulana; Ahmad Rofiq Hakim; Abdullah Hanif

doi:10.59934/jaiea.v5i3.2554

Authors

Armand Maulana Politeknik Negeri Samarinda
Ahmad Rofiq Hakim Politeknik Negeri Samarinda
Abdullah Hanif Politeknik Negeri Samarinda

DOI:

https://doi.org/10.59934/jaiea.v5i3.2554

Keywords:

ESP32-Cam, Firebase, Internet of Things, Infrared Motion Sensor, NodeMCU ESP8266

Abstract

This research aims to develop and implement an Internet of Things (IoT)-based rat trap utilizing dual infrared motion sensors and an ESP32-CAM module. The system integrates infrared sensors calibrated as automated triggers for a servo-driven hatch door, with the ESP32-CAM providing remote visual validation, managed by a NodeMCU ESP8266 as the primary microcontroller. Telemetry data, real-time push notifications, and manual overrides are synchronized seamlessly through the Firebase Realtime Database and a custom Android application. Evaluated via black-box testing using white lab rats as test objects, the empirical results demonstrate that all integrated components operate effectively. The conditional automation sequence, including the 5-minute sensor masking and timeout safeguards, executed successfully without system failure. Furthermore, system integration proved highly stable, exhibiting an average control and data telemetry latency of 1–3 seconds, while mobile push notifications were delivered in less than 3 seconds. These findings confirm that the multi-sensor and camera infrastructure can be utilized optimally to deliver a responsive, reliable, and modern pest control solution.

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