# A Cyber-Physical System for Wildfire Detection and Firefighting
## 1 Introduction
### Proposed CPS for Wildfire Detection  
Building upon this research, our project aims to design, simulate, and implement a Cyber-Physical System (CPS) for wildfire detection using low-cost Internet of Things (IoT) sensors and Robot Operating System (ROS)-based collaborative unmanned robots for fire extinguishing. It is a cutting-edge solution designed to address the increasingly urgent issue of wildfires, which are becoming more frequent and severe due to the effects of climate change. By utilizing low-cost IoT sensors to continuously monitor temperature and humidity, the system is able to detect potential fire hazards at an early stage, such as dry vegetation or other combustible materials, and take appropriate measures to prevent a serious threat. The system also incorporates a smart camera and infrared sensor, enabling real-time detection of flames, which is crucial for quickly identifying and responding to wildfires [12]. Additionally, a Carbon Dioxide (CO\({}_{2}\)) sensor provides real-time monitoring of carbon monoxide in the air, which can help measure the severity of the fire and the level of danger it poses to nearby communities. The data collected by the IoT system is sent to a ground forest fire monitoring and alert station, which is able to visualize the data through a web-based dashboard, allowing for efficient and effective decision-making in response to a wildfire. This system can also trigger appropriate response measures, such as sending alerts to local authorities and emergency services, as well as unmanned systems, for an immediate and coordinated response. The integration of unmanned systems, also known as drones or Unmanned Aerial Vehicles (UAVs), will give the advantage of quickly identifying the exact fire spots after a navigation survey over the wildland and then releasing a ball extinguisher to suppress the fires [13]. In addition, the UAV will transmit the fire spot coordinates to an Unmanned Ground Vehicle (UGV), also called a robot rover, that will empower the overall architecture, by automatically navigating into the forest, reaching the fire spots, and suppressing the fire using water or chemical extinguisher [14]. Our work contributes to the scientific knowledge base by introducing a CPS architecture specifically designed for wildfire detection and firefighting. This architecture is based on the concept of the Internet of Robotic Things (IoRT) [15], integrating a combination of cutting-edge technologies, including IoT sensors, UAVs, and UGVs, while utilizing a set of open-source solutions that are widely popular and accessible to all. This integration enables the development of a scalable wildfire prevention system. The IoRT network, as a specific instantiation of the Internet of Things (IoT) in the context of robotic systems, facilitates seamless collaboration and information exchange between robotic devices and other IoT components. In the context of forestry tasks, this concept holds particular relevance as it allows us to utilize robotic devices to respond to fires detected by the IoT network. One significant advantage of this architecture is its ability to overcome the limitations of existing firefighting systems by integrating and orchestrating heterogeneous robotic systems and user interfaces for data monitoring. In contrast to previous systems that focused on isolated, manually operated approaches [16], our research focuses on the development of a collaborative ecosystem [14] capable of autonomously managing forest fires. To illustrate the practical implementation of this architecture, we have developed a prototype that underwent simulation experiments. While the system development process and simulation procedures are thoroughly described in this study, and the simulation results demonstrate the effectiveness of the proposed architecture, it is important to acknowledge that our CPS system is currently in the developmental phase. As a result, there are certain limitations in evaluating its performance in a real-world environment.