# Building Fire Evacuation: An IoT-Aided Perspective in the 5G Era
## 3 Review of Current Developments
### Review of the State-of-the-Art Smart Building Fire Evacuation Systems  
The most common design of the detecting unit in smart building fire evacuation systems is to apply sensors to perceive various environmental parameters during the fire emergency, including smoke [27; 28; 29], temperature [30; 31], and other sensor sources [32; 33]. The data communications of these sensors are usually built by Wi-Fi [28; 29], Zigbee [32], and Bluetooth [29; 30; 31]. A comprehensive IoT-based building fire evacuation system was exemplified by [PERSON] et al. [34]. The system enabled the detection of fire occurrence places by monitoring the real-time environment data from multiple smart sensors, including gas leak detector sensors, temperature sensors, electric leak detector sensors, and multi-gas detector sensors. In addition to this, the system was also connected with various actuators, including electric breakers and gas valve breakers, to enable remote cut-off of further fire hazards in buildings. The data transmission of all these sensors was built under the ZigBee environment. Moreover, some solutions consider detecting occupants' situations (e.g., position, flow rates, presence). These states of occupants are also important factors in building evacuations. In order to dynamically direct people to the safest exits and speed up the evacuation process, many researchers have developed smart systems tracking locations of the building occupants. With received signal strength indication (RSSI) through Bluetooth Low Energy (BLE) beacons, many researchers enabled localization of occupants via occupants' mobile phones [28; 29; 30]. In addition, a mobile RFID-based system for localization was proposed by [PERSON] and [PERSON] [35]. A ZigBee-based localization module that identifies people's positions and understands whether they are evacuating was proposed by [PERSON] et al. [36]. The systems described by [PERSON] [37] and [PERSON] et al. [38] both employed purposely deployed RFID beacons to collect personnel localization in buildings. Furthermore, personal localization using Global Positioning System (GPS) and Wi-Fi access points were also mentioned by [PERSON] et al. [39]. In addition to tracking the locations of building occupants, some studies also consider optimizing the evacuation routes according to the personnel density or speed in the evacuation route. The crowd evacuation speed and flow rates are often detected via surveillance cameras [40; 41]. The detection of occupants' presence and/or other behaviors in building areas during the evacuation process was also introduced by several authors [42; 43; 44; 45]. The most typical approach used to count the number of people in a target area is through visual-based cameras. Finally, some studies combine BIM technologies to manage and visualize the collected fire and occupant information in a 3D model [29; 30; 46; 47; 48; 49]. This BIM innovation successfully makes it easier for building managers and firefighters to be aware of the real-time fire environment and evacuation on-site. Furthermore, focusing on intelligent route planning, researchers also propose various intelligent building route planning algorithms considering real-time environmental factors and occupants' situations during the evacuation. By giving information about fire origin, nodes of trapped occupants, and nodes of firefighters, [PERSON] et al. [31] proposed a fire rescue path planning approach based on [PERSON]'s algorithm. The approach enabled finding the optimal path of escape in a short computational time. In the work of [PERSON] [37], an intelligent route planning algorithm was proposed by considering the intensity of the fire. In this way, fire hazards can be considered when planning the evacuation route. In order to suggest evacuees with less crowded paths toward safety exits, a situation-aware route planning system considering evacuees' behaviors during the evacuation (e.g., running, waiting in a queue, herding) was proposed by [PERSON] et al. [43].