# Outside Dynamic Evacuation Routes to Escape a Wildfire: A Prototype App for Forest Firefighters
## 2 State of the Art
### Wireless Sensor Network for Monitoring Wildfires  
Wireless sensor network (WSN) technology is implemented due to the need to cover complex surfaces, where wired networks are expensive and not very scalable. For example, in [17], the design and construction of a dynamic monitoring system for a wireless sensor network that operates under the IEEE 802.15.4 (ZigBee) protocol is described. The system allows interactive communication with the entire network and manages data control by implementing tree and mesh topologies and achieving extensive communication coverage. Likewise, in [18], the implementation and experimental validation of an ISA100.11a simulation model for industrial wireless sensor networks (IWSN) are presented, obtaining a high simulation precision by integrating the software stack running on the field devices into the NS3 simulator.  
The literature review describes various WSN applications for supporting or monitoring fires from different perspectives, especially when it comes to monitoring the spread of wildfires. For example, [PERSON] et al. [19] described a network of simulated sensors used in OMNeT++ programming language to create a mechanism for the early detection of forest fires. A graphical user interface (GUI) displays real-time temperature monitoring and its respective alert settings in an emergency. [PERSON] et al. [20] designed and implemented a low-cost and energy-consuming WSN for forest fire monitoring, using a Microchip PIC18F4685 MCU and an ISM Si4432 band transceiver from Silicon Laboratories. They detailed the basic functional principles of the system and the results of the energy consumption measurement. [PERSON] et al. [21] analyzed a WSN that collects data on temperature, humidity, smoke, and oxygen levels at various points in a wooded environment, to verify the quality of the information and the sensing time, to help authorities reduce the loss of life and housing in the event of a forest fire. The node's location is made through satellite communication to reduce coverage holes and ensure the lowest latency range. This node communicates to a monitoring station with its location and sends alerts considering the configured variables' thresholds. However, to reduce the damage caused by wildfires and take more effective preventive measures, many researchers have worked on mathematical models to simulate the wildfire spread, taking into account environmental and geographic variables depending on the study area. [PERSON] [22] defined a fire prediction model assuming that it spreads over a surface with adequate continuous fuel and considering the effects of wind, humidity, and slope on heat transfer, among other factors. Although most simulators use this model to predict fire behavior, it does not consider fire in the treetops, which makes it obsolete for a forest with a high density of vegetation. The proposed prototype is based on conditions that consider heterogeneous terrain, fuel, and climate. The detailed fire prediction model for this job is described in [14]; this tool's core is the cellular automata (CA) and graphical information system (GIS) provided by the Google Maps API, allowing for a simulation that considers the type and density of the vegetation in a specific area.