Sezgin Kaçar, Kerem Küçük, Cüneyt Bayılmış, Ahmet Furkan Sönmez

IoT Teknolojilerini Kullanan Afet Sonrası Yönetim Sistemi

Deprem, sel vb. afet olaylarından sonra can ve mal kaybı gibi afetin etkilerini azaltmak için afet bölgesinden doğru ve hızlı bilgi edinilmesi büyük önem arz etmektedir. Bu bilgi afet sonrası yönetim sistemlerinin de etkinliğini arttırmaktadır. Günümüzde nesnelerin interneti teknolojisi akıllı şehir, akıllı ev, enerji yönetimi, trafik optimizasyonu vb. çok geniş uygulama alanına sahiptir. Bu çalışmada nesnelerin interneti teknolojilerini kullanan, bulanık mantık temelli karar destek sistemine sahip bir afet sonrası yönetim sistemi sunulmaktadır. Bu sistem, nesnelerin interneti teknolojilerinden yararlanarak afetten etkilenen hasarlı bina, etkilenen kişi sayısı gibi bilgilerin elde edilmesi ile afet sonrası yönetim sisteminin kurtarma personeli, ekipman, araç vb. kaynakları etkili bir şekilde yönetmesini ve planlamasını amaçlanmaktadır. Önerilen sistemin başarım değerlendirmesi 7 baz istasyonu, 50 WiFi bağlantı noktası ve 10 IoT nesnesi içeren örnek bir senaryo üzerinde sunulmuştur. Bina hasar durumları ile afet bölgesindeki insan yoğunluğuna ait bilgiler bulanık mantık temelli karar destek sistemi ile üç farklı renkte görselleştirilmiş ve sınıflandırılmıştır.

Post-Disaster Management System Using IoT Technologies

It is of great importance to obtain accurate and fast information from the disaster area in order to reduce the effects of disaster such as loss of life and property after a disaster like earthquake, flood, etc. is occurred. This information also increases the effectiveness of post-disaster management systems. Nowadays, internet of things technology has a wide range of applications including smart city, smart home, energy management, traffic optimization and so on. In this study, a post-disaster management system using internet of things technologies that possesses a fuzzy logic based decision support system is presented. This system aims to manage and plan resources of a post-disaster management system such as rescue personal, equipment, vehicles etc. effectively by obtaining information about the number of people and damaged building affected by the disaster. The performance evaluation of the proposed system is presented on an example scenario including 7 base stations, 50 WiFi connection points and 10 IoT objects. The information on the building damage situation and the human density in the disaster area has been visualized and classified in three different colors with fuzzy logic based decision support system.

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