# A Cyber-Physical System for Wildfire Detection and Firefighting
## 3 Materials and Methods
### Nuclio Serverless Function
Stabilization at higher altitudes, while a potential solution, relies on staying within radio coverage. Unfortunately, due to line-of-sight limitations, obstructions, and the use of Wi-Fi, the effective range for maintaining reliable communication is often short. This restricted range can impede the timely transmission of critical data, potentially hindering the ability to transmit precise GPS locations of fires identified through AI analysis. Moreover, the irregularities of the terrain in forestry areas pose another significant obstacle to the implementation of Unmanned Ground Vehicles (UGVs) for firefighting purposes. The complex topography often found in such regions makes it challenging for machines to access certain locations, depending on the kind and quality of the vehicle. Then, this limitation may prevent the system from fully capitalizing on the advantages of UGVs in navigating and operating in rugged environments. Finally, the architecture uses sensors that measure humidity, temperature, and CO2 levels to detect fire incidents. For this, the system requires internet connectivity that can be unstable in rural areas due to poor coverage in forested areas. Addressing these limitations will be crucial to ensure the practicality and success of such a system in real-world firefighting scenarios. It entails integrating sensors and robotic vehicles into the proposed architecture that are suitable for the specific operating context. For instance, challenging environments such as rugged terrains in forested areas require vehicles with advanced or extreme capabilities; however,these vehicles may still need to be able to access the entire area. On the other hand, more straightforward scenarios, such as patrolling large urban parks, may have fewer efficiency requirements for vehicles and sensors. Nevertheless, it is essential to carefully address all the above-mentioned limitations in the cyber-physical system's design for wildfire detection and firefighting. ## 6 Conclusions

This paper has presented the successful implementation of a collaborative robotic system for fire detection and suppression, utilizing the UGV platform and integrating IoT and UAV technologies. The system was validated in a simulation environment and demonstrated significant potential for improving the effectiveness and efficiency of firefighting operations by leveraging the strengths of various robotic components and enabling real-time communication and coordination. The integration of the UGV, IoT, and UAV technologies provided better situational awareness and decision-making capabilities in firefighting scenarios. The UGV, equipped with external localization and autonomous navigation, autonomously navigated through rough terrain and adverse weather conditions, identified the fire's location, and built a map to gather valuable information on the fire and surrounding environment. The IoT technology enabled real-time data monitoring for better decision-making by firefighters and provided immediate alerts to the UGV on the start of the fire and its approximate location for immediate action. The UAV technology allowed for aerial reconnaissance and data collection, enhancing the system's ability to identify fires and providing more precise fire location information to the UGV. The real-time communication and coordination capabilities of the system facilitated efficient collaboration between the robotic components and IoT, enabling quick and accurate responses to changing conditions in firefighting scenarios. Overall, the successful implementation of this collaborative robotic system for fire detection and extinguishing represents a significant contribution to the field of robotics and firefighting.