## 4 General Description of Adopted IoT-Based System for the Forest Fire Monitoring
### Overall System Description  
Considering the previous discussion, we here propose the IoT-based system for the real-time prevention, detection, and tracking of forest fire in the area of interest, which also supports the continuous collection of all necessary meteorological parameters (temperature, relative humidity, wind speed, rainfall) needed for the forest fire susceptibility assessment in a long-term and short-term manner (by using existing data already used for the forest fire susceptibility assessment described in Section 2 and the result shown in Section 3). The first part of the system in an IoT-based sensor network consists of a large number of sensor nodes that measure the local meteorological parameters (temperature, relative humidity, wind speed, rainfall) and the concentration of chemical gases (oxygen, carbon monoxide, and carbon dioxide) that are responsible for forest fire ignition. These sensor nodes are equipped with sensors and are dispersed in the area of interest. Sensor nodes should be deployed with the decreasing node density as the forest fire susceptibility decreases, considering the results of analysis with fuzzy AHP method presented in Section 3. As evident from this analysis, less than 0.5% of the total NP Golija area belongs to the very high forest fire susceptibility class, while around 24% and 70% of the total NP Golija area belong to the high and medium forest fire susceptibility classes, respectfully. The low and very low forest fire susceptibility classes cover much less percentage of total NP Golija area. In order to ensure proper operational conditions for the proposed system, the relative number of sensor nodes deployed in the same surface area must be dependent on the forest fire susceptibility classes, in the ratio 5:3:2:1:1 for the very high, high, medium, low, and very low susceptibility classes, respectfully. The planned deployment of a sensor node enables a priori knowledge of their location, even without a GPS module. As discussed before, each sensor node can be additionally equipped with a GPS module, which increase flexibility in sensor node deployment and operation, but at the cost of the increased power consumption and network cost. The location of sensor nodes should be carefully chosen in the areas in which there are the most favorable conditions for the fire outbreak (i.e., in the areas covered with pines and other coniferous trees, near the roads and picnic areas, on the slopes facing south, etc.). The sensor nodes are equipped with LoRa radio interface modules in order to establish bidirectional communication with the LoRaWAN gateways deployed in the area. The required number of LoRaWAN gateways must be defined through radio planning process so that the proper radio and service coverage is achieved (the coverage of gateways is partially overlapped in order to enable multiple reception of sensor nodes messages for the border regions in order). Each sensor node periodically performs measurements and employs the fuzzy AHP method described in Section 2.4 adopted to analyze the complex environmental changes in order to calculate two output variables, i.e., forest fire risk estimation and fire outbreak detection, for the real-time fire prevention and detection purpose, respectively. If the percentage of the estimated forest fire risk is high, the node will send this information with its location or ID towards the central element of the system (i.e., to the cloud server), which will log this event and notify the emergency team through its corresponding web platform. If the percentage of fire outbreak occurrence is also high, the node will send the same information to the server but this time with the additional fuzzified input of all meteorological variables in order to enable creation of appropriate database inputs of such occurrences for the sake of further improvements of the system. Additionally, an optional real-time task might be realized based on the aforementioned data.