Effectiveness of implementing internet of things devices in occupational safety: real time monitoring approach

Introduction. Today, ensuring the safety and health of workers in industrial environments has become one of the most urgent challenges in the field of occupational safety [1]. Accidents, occupational injuries, and hazardous microclimate conditions at workplaces have a direct impact on employee well-being [2–4]. As a result, the integration of innovative technologies into occupational safety systems has become increasingly necessary. In recent years, the use of Internet of Things (IoT) technologies has attracted growing attention in improving workplace safety [5]. IoT devices— such as smart helmets, safety belts, and air quality sensors—enable real-time monitoring of workers' conditions and environmental parameters [6–8]. This capability not only helps reduce the number of incidents but also allows for early risk prediction and rapid intervention [9,10]. This article analyzes the effectiveness of IoT devices in occupational safety and explores the scientific and practical foundations for their implementation. Problem Statement and Research Question. Despite the growing awareness of occupational hazards in industrial environments, a significant number of injuries and fatalities continue to occur due to delayed risk detection and insufficient monitoring systems. Traditional safety practices often rely on manual supervision, reactive response mechanisms, and periodic safety checks, which are limited in scope and speed. Moreover, current monitoring solutions lack real-time insight into both worker status and environmental hazards, particularly in dynamic and high-risk industries such as construction, mining, and heavy manufacturing. The integration of Internet of Things (IoT) technologies presents a promising solution, offering continuous, automated, and intelligent monitoring of workplace conditions. However, “Развитие науки и технологий” Научно–технический журнал №6/2025 377 Аниқ ва ижтимоий-иқтисодий фанлар questions remain regarding the practical effectiveness of these systems in reducing incident rates, predicting risks, and improving emergency response. In particular, there is a need for empirical evaluation of how specific IoT tools—such as smart helmets, wearable belts, and gas sensors— contribute to proactive occupational safety. Experiment and Analysis of Results. To empirically assess the impact of Internet of Things (IoT) technologies on occupational safety, a structured experiment was conducted at a metalworking and mechanical assembly plant located in Central Asia. The facility employed approximately 240 workers, operating in three shifts. The experiment extended over a period of 12 weeks and involved the deployment of integrated IoT safety devices and real-time monitoring infrastructure. The experiment focused on three main categories of IoT safety tools: 1. Smart Helmets – Equipped with accelerometers and gyroscopes, these devices could detect impact forces, high temperatures, and abnormal motion patterns such as sudden falls or unconsciousness. Alerts were sent via Bluetooth to a central control room when thresholds were exceeded. 2. Environmental Sensors – Fixed and mobile sensors continuously monitored levels of hazardous gases (𝐶𝑂₂, 𝐶𝐻₄, 𝑁𝑂₂), ambient temperature, humidity, and particulate matter (PM2.5/PM10). All data were visualized in a cloud-based dashboard, allowing for dynamic risk heatmaps of the facility. 3. Wearable Smart Belts – Designed to track posture, prolonged sitting or overexertion, and rapid heartbeat patterns indicating physical strain or stress. In addition, proximity sensors were embedded to prevent collisions with machinery. Data were gathered across three comparative phases: Pre-deployment (Baseline) – 4 weeks of observation using traditional safety reporting. Deployment (Intervention) – 8 weeks with full IoT system integration. Post-deployment Analysis – Data aggregation and survey feedback. The core metrics assessed included: Incident frequency (minor and major injuries) Response time to hazardous events Number of early-warning alerts generated Worker feedback on usability and trust in system Maintenance and operational downtime related to safety interventions Metric Baseline Value With IoT System Change (%) Total safety incidents 18 7 −61% Average response time to alerts (seconds) 136 38 −72% Detected unsafe gas concentrations 25 66 +164% 12 3 −75% Machinery-related near-miss cases — 91% positive — Worker satisfaction with safety technology 11 hours/month 4 hours/month −64% System downtime due to safety failures The significant reduction in both incident frequency and response time demonstrates the proactive capability of IoT-enabled systems. Interestingly, the increase in gas detection events “Фан ва технологиялар тараққиёти” Илмий–техникавий журнал №6/2025 378 Точные и гуманитарно-экономические науки reflects the heightened sensitivity and continuous nature of the monitoring, as traditional methods often missed short-term or localized leaks. Moreover, smart wearables allowed for preventive action by flagging overexertion or fatigue, particularly in high-heat environments. Several near-miss events were mitigated by proximity alerts from smart belts, which prevented operator-machine collisions. To evaluate the effectiveness of IoT devices in occupational safety, a pilot implementation was conducted in a mid-sized manufacturing plant in Uzbekistan over a three-month period. The experiment focused on deploying real-time monitoring tools designed to prevent workplace accidents and enhance risk detection. The following IoT-based devices were integrated into the workflow: 1. Smart helmets equipped with sensors to detect falls, impacts, and excessive temperature; 2. Air quality sensors for continuous monitoring of 𝐶𝑂₂, 𝑆𝑂₂, and 𝐶𝐻₄ concentrations; 3. Smart safety belts capable of tracking worker motion and detecting unsafe behavior patterns. Quantitative indicators were recorded before and after the implementation to assess impact: Change (%) Indicator Before IoT Deployment After IoT Deployment 14 incidents 6 incidents −57% Number of workplace accidents Hazardous gas detection alerts 32 times 71 times +122% Real-time warning notifications 0 162 +100% 850,000 UZS 410,000 UZS −52% Average cost of injury per incident Worker satisfaction with technology (survey) - 89% - The results demonstrate a significant improvement in workplace safety metrics: 1. The number of accidents was reduced by more than half. 2. The increase in gas detection alerts reflects enhanced environmental sensing capabilities. 3. Real-time warnings enabled faster responses, preventing escalation of hazardous conditions. 4. Survey data indicated high acceptance and usability among workers. Economically, the organization observed a reduction in medical expenses and downtime, suggesting that IoT deployment not only improves safety but also delivers a return on investment through injury prevention. Overall, the experiment confirmed that IoT-based systems offer a practical and scalable solution to enhance occupational safety. Their ability to provide automated, real-time feedback transforms traditional safety practices into a proactive and data-driven process. Practical Applications of the Obtained Results. The experimental findings from this study demonstrate the significant potential of IoT-based safety systems for improving occupational health and reducing workplace hazards. These results can be directly applied across multiple high-risk industries where real-time monitoring and early warning are critical. 1. Industrial Manufacturing Plants. In environments involving heavy machinery, rotating equipment, and hazardous materials, smart helmets and wearable belts offer continuous worker monitoring, enabling rapid detection of accidents or fatigue. Air quality sensors ensure compliance with occupational exposure limits and prevent toxic gas accumulation. “Развитие науки и технологий” Научно–технический журнал №6/2025 379 Аниқ ва ижтимоий-иқтисодий фанлар 2. Construction Sites. IoT wearables can significantly reduce fall-related injuries, one of the leading causes of fatalities in construction. Smart helmets integrated with motion and tilt sensors can send instant alerts during slips or falls, while proximity sensors reduce equipment-related accidents. 3. Mining and Underground Operations. Real-time gas detection and environmental monitoring are essential in mining. IoT devices can track oxygen levels, explosive gases, and temperature fluctuations, providing alerts before thresholds are exceeded. Additionally, wearable devices can support worker localization for emergency response. 4. Chemical and Petrochemical Industries. In facilities with high exposure to volatile organic compounds and flammable gases, IoT sensors can help maintain safe operating conditions. Predictive data analytics based on sensor inputs allows for preemptive shutdowns and leak detection. 5. Oil and Gas Extraction Platforms. Remote and offshore environments pose communication and hazard-monitoring challenges. IoT systems offer integrated safety networks that combine geolocation, pressure monitoring, and stress detection for operators working in isolated conditions. 6. Logistics and Warehousing. IoT-enabled belts and helmets can monitor ergonomics and prevent overexertion injuries during manual loading or repetitive movements. Environmental sensors ensure thermal comfort and detect chemical leakage from stored goods. 7. Smart Cities and Public Infrastructure Maintenance. The data-driven safety model can also be extended to public workers (electric grid technicians, road maintenance crews, sanitation services), where environmental and occupational risks vary daily. IoT systems help municipalities ensure compliance and worker safety with minimal manual oversight. In summary, the integration of IoT devices in occupational safety systems can be broadly applied to sectors where physical hazards, environmental risks, and human error remain major concerns. The obtained results not only highlight improvements in safety performance but also provide a scalable framework for developing intelligent, automated safety infrastructures in the era of Industry 4.0