## 4 General Description of Adopted IoT-Based System for the Forest Fire Monitoring
### The Choice of Environmental Parameters for the Forest Fire Risk Prediction and Detection
On the other hand, long-range 3 GPP technologies such as GSM, UMTS, and LTE can provide Narrowband Internet of Things (NB-IoT) functionality [90] with the extended coverage, but also require higher end-device complexity, which consumes more power and license for frequency spectrum utilization. It is worth mentioning that substantial financial resources are needed for the additional optical infrastructure, microwave links, or base stations if the forest area of interest lacks cellular or Wi-Fi coverage. The analysis of cellular networks coverage in the area of interest, in NP Golija, shows that the existing networks do not offer complete coverage. Due to the low economic interest of cellular network operators and the strict environmental conditions that must be met in the protected areas of NP Golija, the setting additional base stations in the area present an issue. A hybrid solution comprised large-scale WSN connected to a cellular network via a corresponding gateway seems to be a good trade-off between the aforementioned conflicting requirements. Nevertheless, this network setup still requires dense WSN deployment with limited inter-sensor distance and satisfactory cellular radio conditions at gateway locations. Long-range wide-area network (LoRaWAN) technology [60; 91; 92; 93] presents a good candidate for this kind of application, since it supports both large coverage, which decreases the number of required sensor nodes, and low power consumption, which prolongs their lifetime. Moreover, LoRaWAN standard utilizes unlicensed industrial, scientific, and medical (ISM) frequency low band with favorable radio conditions [94] and is based on open protocols [93]. Hence, the application of LoRaWAN allows for customization and large-scale deployment without dependence on regulator or standardization body. The considered application demands low data rate, low power consumption of sensor nodes, and long-range communication. Under these conditions, LoRaWAN technology seems to be the most appropriate solution for wireless connectivity of sensor nodes [60; 92; 93], in comparison to short-range and other long-range alternatives. Additionally, in LoRaWAN networks, each sensor can be served by multiple gateways in the area. With LoRaWAN, each uplink packet sent by the end-device will be received by all gateways within reach. This arrangement significantly reduces the packet error rate (since the chances that at least one gateway will receive the message are very high) and allows for low-cost geolocation. The LoRaWAN technology also supports high security, which is of great importance for the considered application. The concept of the forest fire detection using LoRaWAN sensor networks is introduced in [95] and subsequently experimented in laboratory conditions [81] and verified in a real network deployment scenario [60; 96]. These LoRaWAN forest fire monitoring systems gather environmental data collected from LoRa sensor nodes via the LoRa gateway to the corresponding application server where the main data processing is carried out. The fire estimation procedure is based on the 30-30-30 rule, which is not the most efficient method, since a forest fire sometimes depends on the area where it is placed and its topography [97]. Fuzzy logic and its analytic hierarchy process (AHP) method [98] can be used here to enhance real-time environmental data analysis. Fuzzy theory is applied when analyzing the causation of uncertain factors, which corresponds to this specific use case. Seminal works [70] in this area developed fuzzy logic algorithms that estimate the probability and direction of fire based on the status of membership functions that utilize measured sensor data. Combined analysis of measured and historical data can significantly increase forest fire prediction and detection accuracy.