Detection of Accidents Related to Fall by Using IoT and Deep Learning Methods

Year 2022, Volume: 8 Issue: 2, 189 - 200, 01.09.2022

Bekir Aksoy Osamah Khaled Musleh Salman Hamdi Sayın İrem Sayın

Abstract

Work accidents in many businesses pose many dangers for employees. Examples of these work accidents include slippery floors, falling materials, harmful substances/gas leaks, protective clothing and equipment not being used in improper ways or not used at all. It is very important to identify these hazards and take the necessary measures for both worker safety and the employer. Among these dangerous situations, the easiest and most frequent accident to prevent is accidents that occur as a result of slipping or falling. Many employees are injured as a result of these accidents that occur due to problems such as a foreign liquid/substance on the working surface, the inability of the worker to establish his own balance or surface inequalities etc. In this study, such situations such as falling, slipping and balance disorders will be determined by IoT and a deep learning-based system in order to recognize such accidents and make necessary arrangements. Deep learning methods that detect movement such as sliding etc. will be evaluated according to the performance evaluation criteria and the method with the most accurate result will be determined. With the results to be obtained from this study, it is aimed to make improvements to prevent these accidents.

Keywords

Deep Learning, Internet of Things (IoT), Sensors, Fall detection

Nesnelerin İnterneti ve Derin Öğrenme Yöntemleri Kullanılarak Düşmeye Bağlı Kazaların Tespiti

Abstract

Birçok işletmede iş kazaları çalışanlar için birçok tehlike oluşturmaktadır. Kaygan zeminler, düşen malzemeler, zararlı maddeler/gaz kaçakları, koruyucu giysi ve ekipmanların uygunsuz kullanılmaması veya hiç kullanılmaması bu iş kazalarına örnek olarak gösterilebilir. Bu tehlikelerin belirlenmesi ve gerekli önlemlerin alınması hem işçi güvenliği hem de işveren açısından oldukça önemlidir. Bu tehlikeli durumlar arasında en kolay ve en sık karşılaşılan kaza, kayma veya düşme sonucu meydana gelen kazalardır. Çalışma yüzeyindeki yabancı bir sıvı/madde, işçinin kendi dengesini kuramaması veya yüzey eşitsizlikleri vb. problemler nedeniyle oluşan bu kazalar sonucunda birçok çalışan yaralanmaktadır. Düşme, kayma ve denge bozuklukları, bu tür kazaların tanınması ve gerekli düzenlemelerin yapılması için IoT ve derin öğrenme tabanlı bir sistem tarafından belirlenecektir. Kayma vb. hareketleri algılayan derin öğrenme yöntemleri performans değerlendirme kriterlerine göre değerlendirilecek ve en doğru sonuca sahip yöntem belirlenecektir. Bu çalışmadan elde edilecek sonuçlar ile bu kazaların önlenmesine yönelik iyileştirmeler yapılması hedeflenmektedir.

Keywords

Derin Öğrenme, Sensörler, Düşme Tespiti, Nesnelerin İnterneti

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