Intelligent Mobile Indoor Navigation System for Fire Evacuation Based on Artificial Neural Network
Yazarlar (4)
Doç. Dr. Yasin ORTAKCI Karabük Üniversitesi, Türkiye
Doç. Dr. Ümit Atila Karabük Üniversitesi, Türkiye
Dr. Öğr. Üyesi Emrullah DEMİRAL Karabük Üniversitesi, Türkiye
Prof. Dr. İsmail Rakıp KARAŞ Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (ESCI dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal of Computer Science and Information Security | ||
| Dergi ISSN | 1947-5500 | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 11-2016 |
| Cilt / Sayı / Sayfa | 14 / 11 / 980–996 | DOI | – |
| Makale Linki | https://sites.google.com/site/ijcsis/vol-14-no-11-nov-2016 | ||
| UAK Araştırma Alanları |
Bilgi Sistemleri
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| Özet |
| Today the number of complex and multi-storey buildings, such as skyscrapers, airports and shopping centers, is on the increase with each passing day. In parallel to this, the number of people spending time in such buildings is also on a rapid increase. In these buildings, many people lose their direction, fail to find the places they are seeking or the exits, and thus, they end up with experiencing problems in such cases. Beyond that, it becomes much more difficult for people to exit these buildings under emergency cases, particularly in case of a fire. Congestions occur in certain spots of the building, which then leads to panic and confluence. In the fire, some victims cannot even find an escape route and lose their lives either by catching the fire or by jumping out of the window. Within this context, a dynamic, intelligent, real-time indoor navigation system for the fire evacuation has been developed, which navigates each user within the building according to their own physical features and varying conditions of the building in the case of a fire. In this system, the positions of the users are tracked by the Radio-Frequency Identification (RFID) Technology. The necessary instructions for guidance to evacuate the users are prepared on a neural network-based module over a server and are sent to the users’ smartphones in a real-time manner. The proposed system navigates the users over their smartphone instantaneously via vocally-visual elements and allows them to be transported to the exit confidently. |
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