Smart Helmet-Based Proximity Warning System to Improve Occupational Safety on the Road Using Image Sensor and...

Area of Science:

• Occupational Safety and Health
• Human-Computer Interaction
• Embedded Systems

Background:

• Road collisions between workers and heavy machinery are frequent in construction and mining.
• Existing safety measures often lack real-time, direct warnings to both workers and operators.
• The need for an integrated, personal safety system is critical.

Purpose of the Study:

• To develop and evaluate a smart helmet-based proximity warning system (PWS).
• To enhance worker and equipment operator safety by providing timely collision alerts.
• To reduce accidents in high-risk industrial environments.

Main Methods:

• A smart helmet integrated with an Arduino Uno board and a Wi-Fi camera captured site images.
• Object detection algorithms on a smartphone identified heavy-duty trucks and vehicles.
• Visual alerts were delivered via a multi-color LED strip on the helmet, triggered by Bluetooth communication.

Main Results:

• The system successfully detected vehicles and transmitted proximity warnings.
• Performance testing validated the recognition distance based on image pixel size in outdoor settings.
• The smart helmet PWS demonstrated effectiveness in alerting workers and operators.

Conclusions:

• The developed personal proximity warning system (PWS) effectively enhances safety.
• Direct visual warnings enable rapid identification and evacuation from hazardous situations.
• This technology offers a significant advancement in preventing workplace accidents.