RAPID ACCESS TO PEOPLE TRAPPED IN COLLAPSED BUILDINGS AFTER AN AFTER AN EARTHQUAKE


DOI:
https://doi.org/10.5281/zenodo.15714580Abstract
According to the earthquake zone map, it is known that 92% of our country is located within earthquake-prone areas and that 95% of our population lives under the threat of earthquakes. Earthquakes can cause various harmful effects on both living and non-living entities. These statistics indicate a significant risk for people living in our country. After an earthquake, survivors are often found in natural voids within damaged or collapsed buildings. The chances of survival for disaster victims decrease rapidly over time. In urban search and rescue operations, the first 72 hours—also known as the “golden hours”—are the most critical.
As a team, our experience during the February 6th earthquake showed us how crucial it is to reach people trapped under debris as quickly as possible. This painful experience made us realize the absence of a system that could save lives in emergencies. After an earthquake, it is vital for search and rescue teams to access information such as the trapped individuals' phone numbers, emergency contacts, chronic illnesses, necessary medications, the floor and apartment they live in, and the building layout as soon as possible. The earlier the rescue efforts begin from the first minute, the more lives can be saved from under the rubble.
In this project, we have designed an artificial intelligence-based system that allows immediate access to people and their information in the building/house during an earthquake with the press of a single button.
At the end of the post-earthquake search phase, rescue operations begin. The sooner the search process is completed, the faster the rescue operations can start. To facilitate this, we used the MPU6050 accelerometer in our system. This sensor detects earthquakes and, through software we developed, transmits the data via a portable modem to a locally and nationally developed panel that we coded ourselves.
The data includes the floor and side of the building where the person is located, their phone numbers, health status, medications they use regularly, and emergency contact numbers. Authorized personnel who log into the panel can download this information, along with the pre-uploaded building layout and location details, with a single click. This data is then directed to the search and rescue team, allowing them to start the rescue process more quickly.
References
Bloch T., Sacks R., Rabinovitch O., (2016), Interior models of earthquake damaged buildings for search and rescue, Advanced Engineering Informatics, 30(1), 65-76.
Afet ve Acil Durum Yönetimi Başkanlığı (AFAD). Türkiye Deprem Tehlike Haritası ve Deprem Risk Bilgileri. Erişim adresi: https://deprem.afad.gov.tr
Ochoa S.F., Santo R., (2015), Human-centric wireless sensor networks to improve information availability during urban search and rescue activities, Information Fusion, 22, 71-84.
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