# Development of IoT-Based Real-Time Fire Detection System Using Raspberry Pi and Fisheye Camera
## 6 Conclusions  
Forest fires are catastrophic disasters that cause enormous damage worldwide. Depending on how quickly they are detected and dealt with, these vast losses can be reduced. In order to detect forest fires, various studies have been conducted with methods using satellite images and cameras or sensors, but there are few studies on quickly detecting forest fires while monitoring a wide area. In this study, a fisheye camera capable of capturing a wide area in all directions was used, and images captured through Raspberry Pi were continuously transmitted to a database and a function capable of detecting fire in the image was implemented. In addition, the location of the fire on the map was estimated by applying DSM-based GIS analysis. As a result of conducting an experiment on Mt. Bukjeong near Kangwon National University Samcheok Campus, it was confirmed that the position of a moving object can be reasonably estimated with the developed technology. Since it was not possible to experiment with real fire, the point where the target was located was marked with a virtual red color point during the day. At night, a flashlight was assumed to be a fire and detected. If the technology developed in this study is commercialized, it will be possible to quickly detect fire and notify when a fire occurs by monitoring a wide area at a relatively low cost. However, because a large area is displayed in one image, it is difficult to detect a fire that is too far away. It is also necessary to improve the resolution of the image and the accuracy of tracking the location. Since the cost may increase for accurate predictions, an appropriate selection must consider cost and accuracy and, for this purpose,it is necessary to conduct experiments in more diverse environments. In this study, the image was transmitted to the server and the location of the fire was estimated through GIS analysis. The developed device connects to the server, but cannot share data by building a WSN among the devices. In an environment where it is difficult to access the Internet, there is a need to share data between devices, so we plan to conduct additional research by applying WSN in the future. The amount of data transmission can be reduced if fire detection is performed by the device and only the result is transmitted, without transmitting the images. In addition, if combined with various sensors, such as a smoke sensor, heat sensor, and thermal infrared sensor, it is expected that more intuitive fire detection around the device will be possible. It is thought that if the accuracy and practicality are improved by additional research in the future, this will greatly contribute to the field of forest fire detection and prevention.  
Conceptualization, S.-M.K.; formal analysis, C.-H.L.; methodology, S.-M.K.; software, C.-H.L.; writing--original draft, C.-H.L. and W.-H.L.; writing--review and editing, S.-M.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.