# Energy Efficient Routing Protocol for an IoT-Based WSN System to Detect Forest Fires
## 2 Related Work
An MCS value is used to prevent clusters from growing too big. A TE value is used to ensure that low-energy nodes do not become CHs. If the RE of a node is less than the TE, it is not allowed to participate in the CH selection process. A DE value is used to minimize the transmission of redundant data. Sensor nodes located more than DE meters away from the event are not allowed to report the event. A VP is also used, such as ES-MAC and EE-MAC, to reduce idle listening in CHs. Recently, many researchers have developed very efficient WSN models for forest fire detection. In the work discussed in [41], the authors proposed a system called the Forest Fires Surveillance System (FFSS) to monitor forest fires. This system includes a WSN, a middleware, and a web application. Each node in the WSN is equipped with a thermometer, a humidity sensor, and a smoke detector. The middleware receives the data from the gateway and processes them. The web application provides a GUI to view the information. The WSN architecture discussed in [22], consists of sensor nodes, a router (gateway), and a monitoring host/phone. The sensor nodes collect information on environmental parameters such as humidity, air temperature, atmospheric pressure, wind speed, wind direction, etc. The data are sent to the CH of the cluster. The CH aggregates the data collected from all the sensor nodes and sends it to the Network Coordinator. The network coordinator sends the data to the gateway. The gateway forwards the data to the monitoring host. In [42], the authors demonstrated how a wireless sensor network can be used to keep track of forest fires. The design uses MICA motes that have GPS devices attached to them. The objective here is to measure the temperature, relative humidity, and barometric pressure in the vicinity of the fire. In [43], the authors used the Sliding Window Skylines technique in sensor networks to detect forest fires. Basically, the authors worked on how to avoid unnecessary communication by using a novel data suppression method. The work in [44] used a Location Aided Routing approach to detect forest fires. The novel routing algorithm considers three factors: length of the route between nodes, temperature recorded, and count of packets in node buffers. EEFFL proposed in [45] divides the forest area into three zones: High Active Zone, Medium Active Zone, and Low Active Zone. The model uses a greedy forwarding approach to send data to the BS. Sensors in the high active zone send data to the BS continuously. Sensors in the medium active zone send data to the BS periodically. Sensors from the low active zone avoid transmitting data to the BS. In [46], the authors proposed a hierarchical routing algorithm for fog-enabled sensor networks. The ordinary sensor nodes and the CHs work only to forward the data packets. The routing decisions are taken solely by the fog nodes as they are more powerful in terms of storage, processing, and computation. In the work discussed in [47], the authors proposed a comprehensive framework for the early detection of forest fires, taking into consideration the energy consumption in sensor nodes. The framework modifies the strategies of sensor deployment, clustering, and routing, to respond to forest fires quickly. Table 1 compares the WSN models discussed above based on some parameters. The parameter 'Cluster Formation' denotes whether the model supports cluster formation. The parameter 'Slot Allocation' denotes whether sensor nodes select slots for themselves or slots are allocated by the CH. The parameter 'Communication Technique' denotes whether the communications are single-hop or multi-hop. The parameter 'Energy Consumption' represents the average energy consumption in sensor nodes based on factors such as cluster formation, communication techniques, and the number of control packets exchanged. The parameter 'Application' represents the application area of the proposed WSN model.