## 3 Proposed Fires Monitoring and Detection Framework
### The Proposed Sensor Deployment Scheme
In the months when the risk of fire is low, such as winter, our proposed scheme keeps the activity of sensor nodes low and therefore the energy consumed is less. Inversely, in the months when the risk of fire is high, such as autumn, our proposed scheme consumes more energy. Figure 9 compares the average fire reaction delay of the proposed scheme against the base scheme for various numbers of nodes in a cluster. Again, the proposed scheme pe

Figure 7: Total energy consumption. cluster size increases. This is because in the case of a fire, in the proposed scheme, a cluster head immediately broadcasts the warming message without any delay. Therefore, the sink station can handle this threat as quickly as possible. More importantly, we can find that the fire reaction delay of our proposed environmentally aware protocols is less than 1 min if the number of nodes in a cluster is less than 10. This indicates that our proposed protocols have the capability to fulfill the minimum requirement of fire early detection within 6 min. Figure 8: Energy Consumption of the proposed and base schemes. Figure 9: Average fire reaction delay of the proposed and base schemes with the various cluster size. #### 4.2.4 Performance Evaluation on the Proposed Overall Framework

Previously, we evaluated each proposed scheme separately. In this subsection, we evaluate the performance of the proposed overall framework, which includes all the three aspects as mentioned earlier. Again, the indicators of the performance of our proposed framework are energy consumption and fire reaction delay. Therefore, we are mainly concentrating on the evaluation of energy consumption and fire reaction delay of our proposed forest fire monitoring and detection system. We compared our framework with two other methods: One is the random-base method which adopts random deployment, flat topology and is without environmentally aware protocols. Another one is regular-base method, which adopts regular deployment, flat topology and is without environmentally aware protocols. Figure 10 gives the comparison of the total energy consumption of the three methods. The proposed framework consumes less energy with the maximum of 3.3 J and the random-base method gives the worst performance with the maximum of 4.8 J. Similar to Figure 7, initially the proposed framework consumes most energy due to the process of clustering. The completion time of clustering is around 10 s after the simulation start. Another interesting finding is that at the beginning of simulation, the random-base method has better performance than the regular-base method. This advantage may be contributed from the non-uniform distribution of the sensor nodes. Figure 11 presents the fires reaction delay of the three methods against different numbers of nodes deployed. It is observed that our proposed framework outperforms another two compared methods. This is because our proposed framework adopted broadcasting mechanisms when a warming message is generated, while the other two methods are without this mechanism. Moreover, initially as the increases of numbers of nodes are deployed, the fire reaction delay is increased. However, when the number of deployed nodes increases to around 110, the average fire reaction delay achieves maximum value at around 178 s. After that, the average fire reaction delays will decrease and trend to smooth, due to the contribution of more sensor nodes being deployed. This result

Figure 10: The total energy consumption of the three compared methods. proposed framework has scalability and can be implemented practically. Meanwhile, the regular-base method has a little better performance than the random-base method due to its features of topology architecture, but in fact, in the forest environment, it is very difficult to deploy a topology in a regular pattern. Most importantly, we can obtain the result that the proposed framework enables a guarantee of the minimum requirement of reaction to a fire within 6 min.