<![CDATA[Oil palm plantation security officers face serious risks including occupational accidents, physical assaults during Fresh Fruit Bunch (FFB) theft incidents, and communication limitations in vast and remote field areas. Existing surveillance systems remain manual, lacking real-time position tracking, anomaly detection, and visual verification capabilities. This research develops an IoT-Based Smart Helmet Prototype integrating a GPS NEO-M8N module for real-time location tracking, an IMU MPU6050 sensor for four-level impact classification (NONE/LOW/MEDIUM/HIGH), and dual OV3660 cameras on two ESP32-S3 CAM WROOM N16R8 microcontrollers for simultaneous front and rear RTSP video streaming. All data is transmitted over a 4G modem to a VPS running Mosquitto MQTT broker, MediaMTX media server, Redis cache, Node.js REST API, and a Next.js web dashboard with interactive Leaflet mapping. Functional testing at the Institut Teknologi Sawit Indonesia (ITSI) Experimental Plantation demonstrated a GPS coordinate error of less than 0.0015%, IMU impact classification consistency of 98% across 50 trials, streaming latency of 3–5 seconds via HLS, MQTT average latency of 28 ms, and panic button response under 1 second. The system provides a viable IoT solution for improving field security monitoring in oil palm plantations.]]>
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