# LoRaWAN Network for Fire Monitoring in Rural Environments
## 1 Introduction  
Forest fires are continuous threats during summer seasons. In the decade from 2008 to 2018, there was an average of \(\approx\)70,000 fires per year in the regions of Europe, the Middle East, and North Africa [1]. In 2018, the number of forest fires in Portugal, Spain, France, Italy, and Greece, which are some of the countries most affected by wildfires, was 26,434 [1]. These fires cause insecurity and large amount of material and, sometimes, even personal damage. Furthermore, the environment is affected by the CO\({}_{2}\) emitted by the fires and the amount of time required for reforestation may expand for more than 60 years [2]. Lightning strikes, accidents, negligence acts, and intentional acts are the principal causes of forest fires in several of these countries [3]. Figure 1 shows the number of wildfires in Europe, the Middle East, and North Africa in 2018 [1], while Figure 2 shows the burned hectares by wildfires in Europe, the Middle East, and North Africa in 2018 [1]. Both prevention and extinction measures are part of the plan against forest fires designed by the government of Spain. The preventive measures include specialized teams that evaluate the state of the forests and propose different actions to improve it, such as upkeeping the firebreaks. The fire extinction measures include the use of aerial vehicles, the use of the SIMIF (Meteorological Information System for Forest Fires, originally in Spanish, _\"Sistema de Informacion Meteorologica para Incendios Forestales\"_) system for environmental monitoring regarding forest fires, which includes prediction and fire alert functionalities, GPS, data and, voice communication systems for the deployed forces and the use of satellite images. Some regions developed their fire detection and prevention system such as the SIGIF (Integrated Forest Fire Management System, originally in Spanish, _\"Sistema Integrado de Gestion de Incendios Forestales\"_) provided by the Generalitat Valenciana (Spanish Government) [4]. It provides information on the environment from the Spanish Meteorology Agency (AEMET) and the meteorological observatories of the region. It also shows the areas with emergency alerts and the locations where lightning landed. Several environmental parameters are evaluated so as to identify the risks of new fires and prevent them. Temperature, humidity, precipitations and, wind speed are some of the commonly monitored parameters. These parameters are considered to produce an index that indicates the risk of forest fires, such as the Haines index [5]. This index determines with an integer from 2 to 6 the likelihood of a fire behaving in an erratic manner or becoming large. Moisture and stability are evaluated and assigned a value between 1 and 3. The sum of those values results in the Haines index, where value 2 is related to low potential of fire growth or erratic behavior and, the value 6 indicates a high potential. Figure 1: Number of wildfires in Europe, the Middle East, and North Africa in 2018. Figure 2: Burned hectares by wildfires in Europe, the Middle East, and North Africa in 2018. Deploying WSN on forest terrains may present some difficulties. The absence of power sources leads to the need for using batteries and alternative power sources such as solar panels. Lower-range wireless technologies increase the cost of the system due to the need for a bigger infrastructure. Nonetheless, technologies such as WiFi, Bluetooth or cellular communications can be an option for fire detection systems meant to be deployed closer to inhabited areas such as rural environments [6]. Due to the scale of the areas that need to be covered, long-range wireless technologies are the best solution. LoRa presents itself as a good solution for this type of application as its range is up to several kilometers and it presents a low power consumption. Other LPWAN (Low Power Wide Area Network) technologies such as SigFox, LTE or, 5G could also be applied to WSN systems for rural and forest areas [7].