# Energy Efficient Routing Protocol for an IoT-Based WSN System to Detect Forest Fires
## 1 Introduction  
A wireless sensor network (WSN) is a network of wireless sensor devices that work in a coordinated way and communicate their readings to a base station. Each device is powered by a battery with a limited energy supply [1]. Furthermore, these devices have low computation power, and limited sensing and transmission range. The energy stored in the battery of a node determines the lifespan of the node. The stored energy is used for various node operations such as sensing, processing, and communication. The batteries in sensor nodes are small and usually cannot be replaced or recharged. There are various energy harvesting methods, but they cannot eliminate the need for energy management. Hence, the most challenging job is the organization of the limited battery power by using energy-efficient hardware and software protocols for WSNs [2]. Some of the popular applications of WSNs are surveillance in the military, remote patient monitoring in healthcare, measurement of environmental temperature, humidity, and air pressure, crop monitoring in agriculture, monitoring machines in industries, etc. [3]. The following are the design challenges in WSNs: energy conservation, scalability, localization, security, routing, etc. As sensor nodes are standalone devices that completely depend on their batteries to carry out all activities, many researchers have been working on energy-efficient clustering and routing techniques to reduce energy consumption in sensor nodes. In the work proposed in [4], the authors assessed each node's centrality, energy surplus, and temperature to choose the best cluster head. In [5], the authors proposed a priority-based energy-efficient routing protocol for low-power and lossy networks. The Internet of Things (IoT) is largely dependent on WSNs. Sensors continuously monitor the environment in IoT-based WSNs and alert the base station (BS) immediately if any event is detected. An IoT-based WSN also has a gateway to upload the collected data in IoT Cloud. The BS itself can work as the gateway in some deployments. The data stored in the IoT Cloud can be remotely accessed by users whenever they want. Some of the implementations of IoT-based WSNs are water quality monitoring [6], air pollution monitoring [7; 8; 9], smart agriculture [10; 11], health and environments [12; 13], smart irrigation [14], smart cities and smart buildings [15; 16; 17; 18], smart wearables [19; 20], etc. Forests are one of the most significant and necessary resources on our earth. They purify the air we breathe and the water we drink, avoid corrosion and maintain the balance on earth. However, our forests are rapidly disappearing because of the forest fires caused by man as well as nature. Forest fires affect the safety of human habitation and destroy natural resources [21]. In 1971, a forest fire in Kure, Wester Honshu, Japan, destroyed 340 hectares of forest land. By the middle of 1997, the smoke and haze from forest fires in Indonesia had spread to neighbouring countries such as Malaysia and Singapore. In 1987, the black dragon fire started in China, and 18 million acres of land were affected. Bandipur National Park in India's Karnataka state experienced widespread forest fires in February 2019. The intensity of a forest fire depends on the number of trees in the proximity, and thirsty wood and leaf litter that serve as fuel for the fire. These components are explosive and produce the perfect condition for starting the fire [22]. Recently, researchers have proposed many energy-aware WSN models to detect forest fires. In E-RARP proposed in [23], sensor nodes are randomly deployed in the forest. High residual energy sensor nodes are elected as Cluster Heads (CH). Each CH uses Time Division Multiple Access (TDMA) techniques to collect the data from its members and send them to the Base Station (BS). In FLS [24], the authors used temperature, smoke, light, humidity, and distance as inputs to their fire detection system. The objective of the model proposed in [25] is to determine the behaviour of the fire.