## 3 Proposed Fires Monitoring and Detection Framework
### The Proposed Sensor Deployment Scheme
Sink station records the number of cluster head and after those nodes which are located within the radius of R\({}_{re}\) received the message sent by cluster head, they will set own active value to 1. That is, these nodes will not be involved in the cluster head selection. According to this process, we can generate other cluster heads in turn, and the number of cluster heads is controlled by sink station. After the number of cluster head reaches \(N\times P\), it ends the cluster head selection. \[\text{R}_{re}=\frac{S}{N\times P\times\pi} \tag{2}\]

where, \(S\) is the area of WSN, \(N\) is the number of sensor node in the network, and \(P\) is the percentage of cluster head. In the process of cluster head selection, we follow the rule that no other cluster heads exist within the reference radius of a cluster head, which may cause a case where within the reference radius of some common nodes, there is no selected cluster head, or having multiple cluster heads in a certain reference radius. For those common nodes with the active value 1, they choose the closest cluster head within its reference radius to attach; the shortest distance is represented by \(d\). For the common nodes with active value 0, at this stage, the clustering threshold \(T_{clu}\) should be calculated based on Formula (3) and we choose the cluster head with the maximum \(T_{clu}\) to attach. That is, to choose the cluster head which has the higher residual energy and shorter distance to join. \[T_{clu}= \begin{array}{c}d\;;\ Active=1\\ \frac{d_{max}}{d}+\frac{E_{cut}}{E_{init}}\;;\ Active=0\end{array}  \tag{3}\]

where, \(d\) is the distance between current node and cluster head, \(d_{max}\) is the maximum distance between any node of the network, \(E_{init}\) is the initial energy of the node, and \(E_{cur}\) is the residual energy of the node. ### The Proposed Intra-Cluster and Inter-Cluster Protocols

In clustered network architecture, it is necessary to specifically design the intra-cluster and inter-cluster communication protocols, especially for our forest-oriented application. In a forest environment, WSN protocols should be designed with cognition capability for environmental conditions such as current season, daily temperature and the level of fire threat at the moment. In the case that there is no fire, or the risk of fire is low, the network should decrease the packet overhead throughout the network and data should be delivered to the sink station along with the path that has less energy consumed. Inversely, in the case that fire spreads time or the probability of a fire happening is high, an energy-efficient scheme will be a less critical target, but the reaction delay to the fire and delivering data to the sink station rapidly is more critical. Therefore, in this subsection, we are going to describe our proposed forest-oriented WSN protocol which can react to the changes of environment and weather conditions. As mentioned earlier in Section 3.2, our proposed network architecture is hierarchical and clustered. Therefore, the proposed protocols in this subsection are targeted at hierarchical clustered WSNs. The proposed clustering protocols are different from the clustering works in the literature. This is because our proposed clustering protocols are designed exclusively for forest fire monitoring and detection systems. Our works are more concentrating on how a hierarchical clustered topology should be employed, operated and used to react to fires as early as possible while maintaining acceptable energy consumption. The proposed clustering protocols can be divided into two parts: (1) intra-cluster protocol, and (2) inter-cluster protocol. The intra-cluster protocol provides the communication within a cluster between common nodes and cluster head. It consists of four phases: (1) initialization phase, (2) non-fire phase, (3) fire threat phase, and (4) damage phase. In each phase, we implemented a set of exchangeable messages and signaling between cluster head and its common nodes in our framework.