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.