Smart Helmet for Monitoring Construction Workers Using IoT-based ESP32 and LoRa

Abstract

Job safety in the construction sector in Indonesia is a pressing issue, with accident rates still high despite conventional efforts to improve them. This research aims to overcome this issue by utilizing the Internet of Things (IoT) through Smart Helmets. The Smart Helmet is equipped with an Inertial Measurement Unit (IMU) sensor to detect falls and monitor worker orientation and movement in realtime. This system uses MongoDB for data storage and Real-Time Locating System (RTLS) with ESP32 and HELTEC LoRa32 V2 for signal transmission. The MPU9250 9DOF sensor is used to obtain data from the IMU, while Sensor Fusion and Kalman Filter are used to increase the accuracy of sensor data measurements. The research design research method is applied through the needs identification, design, implementation and evaluation stages. The results of this research are able to monitor workers' movements and orientation and detect work accidents in the construction sector.