# Open Collaborative Platform for Multi-Drones to Support Search and Rescue Operations
## 1 Introduction  
Recently, the number of catastrophic natural disasters has increased over years due to climate change. Global warming creates warmer and drier conditions which increase the risk of wildfires. According to the Center for Research on Epidemiology of Disasters (CRED) [1], the U.S.A suffered 53% of total economic losses due to record-breaking storms and wildfires in 2020. Moreover, wildfires across the west coast of the U.S.A resulted in USD 10 billion in economic losses, more than 30 loss of lives, and more than 4 million acres of land burned. In the summer of 2021, wildfires resulted in eight lives lost, and hundreds evacuated in Turkey, Greece, Italy, and Spain. According to World Health Organization (WHO) [2], wildfires lead to a deterioration of the air quality and the loss of property, such as crops, resources, animals, and people. In addition, the disasters disrupt transportation, communications, power and gas services, and water supply. One thing that most natural disasters have in common, besides the tremendous loss of life and property, is that they are immediately followed by an almost total loss of the ability to communicate with the outside world. Without any communication, it will not be easy for victims to reach for help and report their locations. Second, search and rescue (SAR) operations face great difficulties in finding victims in large disaster areas such as wildfires. Third, wildfire disaster is often low visibility, unfriendly, inaccessible, or even dangerous for rescue teams. Unmanned aerial vehicles (UAVs) are a good option to provide support to remote sensing and monitoring operations, such as SAR operations, with low operating costs, fast deployment, and agile maneuverability. UAVs have been used to support SAR operations in searching for survivors as early as Hurricane Katrina in 2005 [3]. However, low visibility due to thick smoke or a high level of temperature makes vision-based or thermal-based UAV-supported SAR operations ineffective; and operations often continue overnight making such vision-based SAR operations difficult. In our previous work [4], a Krypto module, named after the flying dog from [PERSON] comic books, is developed to \"sniff\" out wireless signals from any mobile device. Moreover, a drone carrying the module is able to locate any possible survivors. The Krypto module is a low-cost module (i.e., USD 100 or less) with hardware components Raspberry PI, two Wi-Fi cards, GPS Dongle, and Portable Charger. The source code of the Krypto [5] is open source that can be downloaded and installed into Raspberry PI. The module can be easily extended by adding additional sensory devices (e.g., camera, thermos-sensor/camera, etc.,) or connecting to a drone with API for existing sensors information (e.g., via DJI SDK API [6; 7]). Krypto module combined with aerial drones is able to effectively patrol and sense large disaster areas to assist SAR operation. In recent years, the popularity of drones is increased to new heights according to Federal Aviation Administration (FAA). There are more than 310,000 commercial drones and 530,000 recreational drones have been registered with the agency in 2022 [8]. The drone market continues to grow at a rapid pace. Although not all can be participating in SAR operations, many of them have the hardware and software capabilities to assist in SAR operations. In combination with the Krypto module, anyone with drones can support SAR operations by contributing to their findings on any possible survivors. In this paper, we proposed an **Open Collaborative Platform** for multiple drones to assist SAR operations. The open platform allows drones that carry Krypto modules to collaborate in search operations. The aim of the open platform is to manage different drones to collaborate with each other by sharing information and planning search paths/areas to reduce searching time on finding survivors. With the Open Collaborative Platform, anyone can participate in SAR operations and contribute to finding possible survivors.