Enviro-Alert Helmet: A Wearable Internet of Things Solution for Safety, Hazard Detection, and Rapid Response
Ensuring worker safety in hazardous industrial environments is an ongoing challenge, with many risks such as extreme temperatures, toxic gases, excessive noise, and poor visibility posing serious threats to workers' health and well-being. This paper presents the design and implementation of a smart helmet aimed at improving worker safety through continuous, real-time monitoring of both environmental and physiological parameters. The helmet is equipped with advanced sensors such as for temperature and humidity, and for heart rate and pulse oximetry, providing a comprehensive solution for worker health surveillance. A Wi-Fi module enables seamless data transmission to a central monitoring system or mobile application, offering remote access for supervisors to track worker conditions in real-time. The proposed system continuously collects and transmits data, ensuring that any environmental or physiological anomaly triggers immediate alerts, notifying both the worker and designated personnel. These alerts are designed to be non-intrusive yet effective, enabling swift intervention before conditions escalate into dangerous territory. The results demonstrate that the system is both reliable and accurate, capable of detecting hazardous changes such as elevated temperatures, abnormal heart rates, and the presence of toxic gases. By providing timely alerts and facilitating early intervention, this IoT-enabled smart helmet significantly enhances workplace safety, offering a cost-effective and scalable solution for mitigating risks and safeguarding workers' health in high-risk environments.
Authors
- R. Reddy (ORCID: https://orcid.org/0000-0001-5025-9131)
- Chiranthana M Reddy
- R Vinay
- Kenneth Aaron Fernandez
- Jefferson Randy D'Costa
- V Brunda
Publication Details
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1109/idciot64235.2025.10915040
- Citations
- 2
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 2.61