سامانه‌ی هشدار دهنده‌ی وضعیت‌های مجاورتی خطرناک در کارگاه‌های ساختمانی بر پایه‌ی رهگیری افراد و تجهیزات

صنعت ساخت‌وساز و کارگاه‌های ساختمانی به عنوان یکی از پرحادثه‌ترین صنایع در جهان شناخته می‌شود که این امر باعث شده تا توجه پژوهشگران نسبت به استفاده از فنّاوری‌های جدیدی همچون فنّاوری اینترنت اشیاء برای بهبود شرایط ایمنی جلب شود. در این پژوهش، با استفاده از تلفن هوشمند همراه و بهره‌گیری از روش اثر انگشت روی شبکه‌ی وای‌فای و سامانه‌ی موقعیت‌یاب جهانی )جی‌پی‌اس( سامانه‌یی معرفی شده است که با رهگیری افراد، نزدیک شدن آن‌ها را به نقاط خطرناک موجود در کارگاه ساختمانی شناسایی می‌کند و هشدارهای لازم را ارائه می‌دهد. این سامانه، علاوه بر کار کردن در مناطق سرپوشیده و روباز، نقاط قوت دیگری چون سادگی کارکرد، قیمت پایین پیاده‌سازی و دقت بالاتر نسبت به نمونه‌های مشابه را دارد. در این پژوهش به متوسط خطای تشخیص $1/2$ متر دست یافته‌ایمکه خطای قابل قبولی است و نشان از عملکرد صحیح سامانه دارد.

An alarming system for dangerous proximity situations in construction sites based on workers and mobile equipment tracking

The construction industry and workplaces are known as one of the most adventurous and dangerous industries in the world, incurring more occupational fatalities than any other sectors. This has led researchers to pay greater attention to the use of new technologies, such as the Internet of Things (IoT) technology, to improve safety. The IoT is helping many businesses and consumers to be more efficient and effective in daytoday operations and tasks. It would only be logical to assume that there must be a way that the IoT could do the same for highrisk industries such as the construction industry. In this study, using a smartphone and fingerprint technique on the WiFi network and the Global Positioning System (GPS), a system has been introduced to detect people approaching dangerous places by tracking them and to provide the necessary warnings. The system consists of three software products the first of which is responsible for performing calculations on the cloud server. The second one is installed on the mobile phones of site managers to record the necessary information in the system database. The third software is installed on the mobile phones of workers and has the task of tracking them and receiving the system warnings. In addition, this system is working in indoors and outdoors areas and has other advantages such as ease of operation, low implementation cost, and higher accuracy than other similar systems. In this study, an average detection error of 1.2 meters has been achieved, which is an acceptable error and indicates the correct operation of the system. Using the proposed IoT system in a construction site’s safety management system will provide realtime data on critical safety functions. As a result, it also reduces the accidents of the construction site and the costs around incidents, injuries, and workers’ compensation.