Research Information System
16th International Congresses on Social, Humanities, Administrative, and Educational Sciences in a Changing World, Ürgenç, Uzbekistan, 11 - 13 June 2025, pp.1317-1319, (Summary Text)
Occupational accidents and diseases pose serious health and safety
risks, particularly for individuals working in high-risk sectors such as
underground mining, construction, and heavy industry. To reduce and prevent
these risks, an effective Occupational Health and Safety (OHS) system is
essential. However, existing systems are often too costly, complex to install,
and lack flexibility, making them difficult to implement widely in small and
medium-sized enterprises. In this context, the proposed study introduces a
low-cost, portable, modular OHS monitoring system based on the principles of
electronics engineering and built upon a Wireless Sensor Network (WSN)
architecture. The system is designed to detect three critical elements: a Hall
Effect sensor and pressure sensors to detect whether the worker is wearing a
safety helmet; piezoelectric sensors and load cells integrated into the foot
area to detect the use of safety boots; and a triaxial MEMS accelerometer to
monitor the worker’s mobility. Analog and digital data collected from these
sensors are processed by a low-power, high-performance microcontroller (such as
STM32 or Arduino Nano 33 IoT) and wirelessly transmitted to a central control
unit using Wi-Fi modules. In the control unit, embedded system software
analyzes the data in real time and presents it to the employer or OHS
specialist through a user-friendly interface. Additionally, to enhance energy
efficiency, the sensors operate on an event-driven basis—transmitting data only
when specific conditions occur—thereby extending battery life. The system
achieves over 95% accuracy in helmet and boot detection, while its motion
tracking capabilities provide effective results for real-time work monitoring.
Compared to traditional systems, this structure offers a cost-effective and
sustainable engineering alternative. As the system is designed as an
open-source platform in both hardware and software, it can be easily adapted to
different sectors and applications. It can also be expanded with additional
sensor modules—such as gas detectors (e.g., MQ-135), temperature-humidity
sensors (DHT22), and volatile organic compound (VOC) monitors. Future work aims
to enhance the system with cloud-based data analytics, risk scoring via machine
learning algorithms, and the integration of emergency alert mechanisms. In
conclusion, this study demonstrates that a low-cost, flexible, and highly
applicable OHS monitoring system can be developed through electronics
engineering-based approaches, thereby offering a significant contribution to
the digitalization of occupational safety practices.