Assisting a search and rescue mission for lost people using a UAV

Search and rescue (SAR) missions on land are nowadays still being executed on foot or by manned aircraft, including planes and helicopters. Both methods demand a significant amount of time and are not cost-efficient. This is particular significant when considering that the main challenge in such operations is the time needed to react and to take the required action.

New developments in unmanned aerial vehicle (UAV) technology could help tackle such a problem with the use of drones and aerial photography. This study exploited this technology, combined with shortest-path and object-detection algorithms, to seek to reduce the mission duration and the risk of the injury of the parties involved.

In preparation for devising a solution to the aforementioned problem, existing research on UAV/drone technology and SAR missions on land was studied carefully. Particular attention was given to research focusing on lost persons living with dementia. Models and prototypes were formulated prior to development, on the basis of this research.

An Android mobile application was developed to simplify the communication between a DJI drone and the operator, by making use of the DJI Mobile Software Development Kit (SDK). Given the time constraint to search for a lost individual with dementia during such an SAR mission, a shortest-path algorithm was implemented to aid the operator in the drone navigation from one waypoint to another, depending on prioritisation and the probability of finding the lost person. An object-detection algorithm received the images captured by the drone to detect persons at multiple points throughout the route. A separate Android mobile application was developed to efficiently gather data on the SAR mission, including personal information and locations that would be potentially vital during a SAR mission. Both mobile applications used the same Firebase Realtime Database to collect and utilise the mission information.

Figure 1. Architecture diagram of the SAR mobile application
Figure 2. Prototypes of the mobile applications
Student: Michael Azzopardi
Course: B.Sc. IT (Hons.) Software Development
Supervisor: Dr Conrad Attard