# IoT-Based Intelligent Modeling of Smart Home Environment for Fire Prevention and Safety
## 2 Related Work  
In the last few years, sensors have been widely used for fire detection [14; 15; 16; 17; 18; 19]. [PERSON] et al. [14] proposed a work for fire detection in mines by using wireless sensor networks called WMSS. For determining the hazardous factor in the mines, they used gas sensors and designed a wireless sensor network which collects and analyses the gas level in mines. The work proposed in [15] used Zigbee-based wireless sensors for fire detection in forests. They used temperature sensors to establish the intensity of fire in a forest. They used a CC2430 chip in their hardware design for network nodes. Similarly, [PERSON] et al. [16] also designed a framework for forest fire detection. In their work, they used a model for fire detection using different clustering schemes and communication protocols. They performed the simulation for validation and evaluation of their work. [PERSON] et al. [17] implemented a work for forest fire detection. They used multi-sensor and wireless IP cameras to avoid false alarms. Their system also connected to the internet via gateways for uploading the data to the cloud. A work proposed in [18] for forest fire detection was based on a ZigBee wireless sensor network in China. A work for forest fire detection is proposed in [19]. [PERSON] proposed a work for WSN [20]. South Koreans [21] also designed a system for fire detection in their mountains. They named their system FFSS (Forest fire Surveillance system). They developed their system by using WSN, middleware, and web applications. Network nodes (i.e., temperature sensors and humidity sensors) collect measurements and send them to the sink node. Afterwards, the sink node transmits that data to the cloud via a transceiver (gateway). Later, by using a formula, the fire risk level is determined in the middleware program. After detecting the fire, FFSS is activated automatically. TinyOS is used as an operating system for network nodes. Similarly, few other systems utilize the WSN for early fire detection. Few of them use IP-based cameras and mixed multi-sensors [22] on wireless mesh network to detect a fire efficiently. They use these three parameters to make an efficient system to identify and verify fire. A software application exists, which selects the closest IP base camera. When sensors sense a fire, they send the information to the central server where the software program selects the nearest camera. That camera takes pictures of the location and send them back to the main sink. Alarm decision is made on the basis of the sensor's information and selected images. Also, a clustering-based forest fire detection system was proposed in [23]. The proposed method uses advanced communication protocols. The proposed work consists of four major parts: (i) an approach for sensor deployment, (ii) the use of WSN for fire detection, (iii) intra-clustering protocols, and (iv) an inter-clustering communication protocol. Another work was proposed by [PERSON], [PERSON], [PERSON], and [PERSON] [24] for disaster detection, including the fire event. This method can quickly adapt the routing work state on the basis of the threat of possible failure. In [25], researchers proposed a protocol for the adaptation of the Context-Aware Routing Protocol (CAR) to WSN and named it SCAR. Energy, colocation with sink, and their connectivity was evaluated in SCAR. For the delivery of data packets to the sink, delivery probability and forecasted values were combined on the basis of previous knowledge of SCAR parameters. In this system, buffer space and delivery probability are exchanged periodically with neighbor nodes. An order list of neighbors is sorted by delivery probability, which is kept by each node. [PERSON] et al. [26] proposed a work to create a model for fire detection. They performed a simulation by analyzing sensors data and geographic information. To differentiate from the existing work, they used topography of the environment under study. Energy and time factors are an unavoidable requirement that should be satisfied efficiently.