Earticle

In the National Police Agency statistics According to In 2017 alone, children, the disabled and the elderly with dementia are reported missing. There are an average of 100 missing cases per day. In addition, according to data compiled by the National Defense Agency, there are 40,000 to 50,000 fires annually in Korea, Massive loss of life and property will result. Therefore, research on various algorithms for these disaster sites and search methods for missing persons continues, and drone technologies with automated search and analysis features are being developed, particularly using artificial intelligence. As a method of collecting data for searching for missing persons and identifying disaster sites, data such as 360 degree panoramic photos and images can be obtained by attaching aerial video and photography, 3D mapping, and special equipment to drones. Data acquisition aims to extract data analysis elements so that deep learning pattern recognition algorithms can be applied to the latest technology of artificial intelligence. Deep Learning's extraction of elements to search for various missing persons and detect disaster sites is the most important element in unmanned mobile device control technology including AI (Artificial Intelligence) drones. A number of causes of human casualties at the disaster site and the search for missing persons are due to the delay in searching for missing persons and the lack of human error during the inspection and diagnosis of the disaster site.

In this study, we studied the application usefulness of a wired drone system capable of obtaining power and data and communication relay in order to prepare for release of control rights due to power cut off or damage to repeaters in disaster areas due to disasters or because there are no relays in mountainous areas or at an altitude of 150m or higher. In order to temporarily connect the repeater developed using the 800MHz band of LG U+ domestic telecommunications company to nearby available base stations and restore the communication network, it is mounted on a wired drone system that can take off at an altitude of 20m and fly for more than an hour to strengthen canceller characteristics and delay time. For the analysis, a wired drone system and a drone-mounted repeater were manufactured to maintain an altitude of 20m for more than an hour, and a small drone-mounted repeater secured stable communication quality around 500m. Shrinkage was tested. Therefore, as a follow-up study, the evaluation of securing the right to control by linking the wired communication repeater drone system with the disaster drone is proposed.

Statistics of missing persons information system by the National Police Agency indicated a total of 42,390 missing reports of children, intellectually disabled and dementia patients in 2019. Also, according to the date statistics by the National Fire Agency, 40,000 to 50,000 fires broke out annually in Korea, resulting in massive loss of lives and property. For this reason, research on various algorithms on disaster sites and searching methods for missing persons continues, especially drone technology with automatic search and analysis functions are being developed by using artificial intelligence(AI). This study aims at utilizing a drone which is one of many unmanned equipment to collect the most accurate and the largest data in time by minimizing the site damage. To collect the data for searching missing persons and identifying disaster sites, aviation video and photography, 3D mapping, and special equipment can be mounted on drones to take 360-degree panoramic photographs and images. For data acquisition, drone control patterns were studied for searching for missing persons and identifying disaster sites by applying data elements extracted from the researcher's preceding research, so that Deep Learning pattern recognition algorithm can be applied to the latest AI technology. This pattern is the most critical element for unmanned mobile device control technology including AI drones for missing person research and disaster sites. The images for 2D and 3D modeling of videos ad photographs, which were taken by drones by applying Deep Learning elements to drone search patterns, were analyzed based on the production of modeling results and data with PIX4D software. In many cases, the cause of the serious loss of life at the disaster and missing search site is the golden time delay in the search and the Human Error during the inspection/diagnosis of the site. Therefore, there is a need of pattern development of the unmanned drones for the reconnaissance patrol by using Deep Learning elements, in order to compensate for the lack of professional manpower for diagnosis/inspection as well as search equipment. For this reason, we suggest the joint search patterns of aviation drones and floating/underwater drones for the follow-up studies.