**3.2 Detection of people**

Manual counting of people takes long time to identify and to rescue them. To facilitate the identification of people in MPCS, this study proposes the application of Wi-Fi scanners and smartphones for automatic detection of people. According to the Bangladesh Telecommunication Regulatory Commission (BTRC), 156 million people subscribed mobile phone at the beginning in 2019 in Bangladesh where penetration rate of smartphone is satisfactory. For detecting people in MPCS, all participants turned on Wi-Fi/hotspot of their smartphones. Wi-Fi has a total inquiry time of as little as 8 ms. This allows detection of devices every second, allowing people with using Wi-Fi who stays in the range of a detector at a much quicker rate. In this controlled experiment, the number of participants was captured for each 5-minutes. There were 90 participants who joined the experiment. At the beginning of the experiment, all participants turned-off Wi-Fi/hotspot of their smartphones. In each five minutes, few new participants


**Table 1.**

*An example of inbuilt index of the community people.*

turned-on Wi-Fi/hotspot of their smartphones and were detected. For each time interval, the number of detected people was increased with the increase of active devices as observed. **Figure 5** shows the detection of people during the experiment.

#### **3.3 Index of missing people**

Wi-Fi scanners can identify the MAC address of the smartphones that has turned on Wi-Fi [22]. People come to the shelters while evacuation order is issued by the disaster management authority. The people who were in the shelter turned on Wi-Fi/hotspot and detected. In every five minutes, few new people were detected. A new index of people was developed with SSID/MAC. A SSID is simply a wireless network name to distinguish it from other networks in neighbourhood [27]. MAC addresses are unique identifiers defined by IEEE as a communication protocol for wireless Wi-Fi connection [26]. The inbuilt index (**Table 1**) and new index were compared that produced an index of missing people. An example of index of missing people is shown in **Table 2**.

In inbuilt index, there were 90 registered participants. While evacuation order was issued, participants started to come into the shelter and Wi-Fi scanner detected people by MAC/SSID and developed a new index. After that the inbuilt index and new index were compared that produced the index of missing people as shown in **Table 2**. The number of missing people was decreased with time as shown in **Figure 6**. At the beginning of the experiment more than 50 participants were detected as missing people. For every five minutes, few new people were detected and missing people were decreased. At a certain time, there were no missing people that meant all participants were detected and rescued. The search and rescue operation will be stopped at red line. The index of the missing people is required to be updated continuously in order to observe the newly arrived people in the shelter. The updating of index notifies the list of the missing people. The index of missing people should be displayed in a bigger screen. The family members can easily identify the missing people and contact with them. The evacuation and rescue team of the MPCS can rescue the missing people.

From the index of missing people, phone calls could be made to confirm the location of people and they would be requested to take shelter in MPCS. From phone call, we could identify the current status such as age, disability, and other burdens that prevent themselves from evacuation. Beside more information could be provided about the MPCSs to him/her for taking shelter there.

**47**

*Disaster Resilient Rescue of Coastal Community on Cyclone Warning*

**Figure 6** shows the number of missing people in different time stamp. There were 90 registered participants. In the very beginning of experiment, 52 participants were detected as missing people. Later, missing people were recorded as 39, 38, 25, 19, 15, and 0 with elapsing of time and increasing the participants. While reaching zero, all community people were rescued in the MPCS. The proposed method of detecting the missing people is an efficient method as it can detect 100% of participants. In **Figure 6**, the red line was drawn as the demarcation of search

**Name Address SSID MAC Mobile No.**

Y 11:3A:09:3B:8D:22 017xxxxxxxx

The evacuation decision and destination are influenced by many factors, e.g., distance of MPCS, facilities in MPCS, access road, weather condition, crowdedness, socioeconomic condition, psychological, physical, cultural and personal factors etc. Level of education and household income affect the access to radio, television and online newspapers. However, the ownership of radio and television, listening to cyclone warning, improper understanding of signals, late warnings, sudden change in signals, and issuance of premature evacuation order are the obstacles to successful evacuation [3, 28]. Signals are hoisted for seaports and people cannot understand the signals outside the port areas and evacuation becomes uncertain in that cases [5]. Past experience on the failure of warning known as false alarm effect, disbelief on existing warning signals, hampering income earning activity with pro-active evacuation responses, missing the target position and weaker condition

Lack of killas and public transport discourage community people to evacuate. In some cases, people avoid evacuation due to over age, perceived level of risk, fear of

and rescue operation. This is the end point of rescue operation.

of cyclone demotivated people for evacuation [5, 6, 29].

*DOI: http://dx.doi.org/10.5772/intechopen.94315*

X House # 32, BRTC

*Detection of people in the MPCS.*

**Table 2.**

**Figure 5.**

Road, Patharghata, Barguna-8720.

*An example of index of missing people in MPCS at a certain time.*

*Disaster Resilient Rescue of Coastal Community on Cyclone Warning DOI: http://dx.doi.org/10.5772/intechopen.94315*

**Figure 5.** *Detection of people in the MPCS.*


#### **Table 2.**

*Natural Hazards - Impacts, Adjustments and Resilience*

Patharghata, Barguna-8720.

Patharghata, Barguna-8720

Patharghata, Barguna-8720

Patharghata, Barguna-8720

Patharghata, Barguna-8720

*An example of inbuilt index of the community people.*

X House # 32, BRTC Road,

A House#1, BRTC Road,

B House#2, BRTC Road,

C House#3, BRTC Road,

D House#4, BRTC Road,

turned-on Wi-Fi/hotspot of their smartphones and were detected. For each time interval, the number of detected people was increased with the increase of active devices as observed. **Figure 5** shows the detection of people during the

**Name Address SSID MAC Mobile No.**

Y 11:3A:09:3B:8D:22 017xxxxxxxx

A 7c:a1:77:1e:39:9a 017xxxxxxxx

B a4:50:46:16:51:ed 017xxxxxxxx

C 40:D3:AE:73:01:88 017xxxxxxxx

D 94:B1:0A:92:33:EB 017xxxxxxxx

Wi-Fi scanners can identify the MAC address of the smartphones that has turned on Wi-Fi [22]. People come to the shelters while evacuation order is issued by the disaster management authority. The people who were in the shelter turned on Wi-Fi/hotspot and detected. In every five minutes, few new people were detected. A new index of people was developed with SSID/MAC. A SSID is simply a wireless network name to distinguish it from other networks in neighbourhood [27]. MAC addresses are unique identifiers defined by IEEE as a communication protocol for wireless Wi-Fi connection [26]. The inbuilt index (**Table 1**) and new index were compared that produced an index of missing people. An example of index of miss-

In inbuilt index, there were 90 registered participants. While evacuation order was issued, participants started to come into the shelter and Wi-Fi scanner detected people by MAC/SSID and developed a new index. After that the inbuilt index and new index were compared that produced the index of missing people as shown in **Table 2**. The number of missing people was decreased with time as shown in **Figure 6**. At the beginning of the experiment more than 50 participants were detected as missing people. For every five minutes, few new people were detected and missing people were decreased. At a certain time, there were no missing people that meant all participants were detected and rescued. The search and rescue operation will be stopped at red line. The index of the missing people is required to be updated continuously in order to observe the newly arrived people in the shelter. The updating of index notifies the list of the missing people. The index of missing people should be displayed in a bigger screen. The family members can easily identify the missing people and contact with them. The

evacuation and rescue team of the MPCS can rescue the missing people.

be provided about the MPCSs to him/her for taking shelter there.

From the index of missing people, phone calls could be made to confirm the location of people and they would be requested to take shelter in MPCS. From phone call, we could identify the current status such as age, disability, and other burdens that prevent themselves from evacuation. Beside more information could

**46**

experiment.

**Table 1.**

**3.3 Index of missing people**

ing people is shown in **Table 2**.

*An example of index of missing people in MPCS at a certain time.*

**Figure 6** shows the number of missing people in different time stamp. There were 90 registered participants. In the very beginning of experiment, 52 participants were detected as missing people. Later, missing people were recorded as 39, 38, 25, 19, 15, and 0 with elapsing of time and increasing the participants. While reaching zero, all community people were rescued in the MPCS. The proposed method of detecting the missing people is an efficient method as it can detect 100% of participants. In **Figure 6**, the red line was drawn as the demarcation of search and rescue operation. This is the end point of rescue operation.

The evacuation decision and destination are influenced by many factors, e.g., distance of MPCS, facilities in MPCS, access road, weather condition, crowdedness, socioeconomic condition, psychological, physical, cultural and personal factors etc. Level of education and household income affect the access to radio, television and online newspapers. However, the ownership of radio and television, listening to cyclone warning, improper understanding of signals, late warnings, sudden change in signals, and issuance of premature evacuation order are the obstacles to successful evacuation [3, 28]. Signals are hoisted for seaports and people cannot understand the signals outside the port areas and evacuation becomes uncertain in that cases [5]. Past experience on the failure of warning known as false alarm effect, disbelief on existing warning signals, hampering income earning activity with pro-active evacuation responses, missing the target position and weaker condition of cyclone demotivated people for evacuation [5, 6, 29].

Lack of killas and public transport discourage community people to evacuate. In some cases, people avoid evacuation due to over age, perceived level of risk, fear of

**Figure 6.** *Detection of missing people in the MPCS.*

robbery, belief on fate, false sense of secured house and embankment. Some people believe cyclones come as punishment from god and stay home is safe by praying to god. In conservative societies women cannot leave their houses without husbands' permission, and putting men and women under the same roof affects women's status in their family and society. This fatalistic attitude makes the people in great danger. Women also desire separate facilities and sufficient water supply as they hold more dependent members like children and adults [1, 9].

Super cyclone SIDR (2007) caused 3460 death tolls [1, 9]. Strong disaster management committees, construction of MPCSs, and monitoring cells decrease death tolls in recent cyclones, e.g., eight death tolls in cyclone Fani. Reduced death tolls do not indicate successful evacuation of all vulnerable people. Despite the dynamic efforts of GoB, evacuation of people has become difficult and most of the respondents did not evacuate in some cases of cyclones, e.g., Amphan. Successful evacuation depends on evacuation preparation, order and timing, and rescue operation before cyclones landfall. If the warning become location specific and order is given within 2–3 hours before cyclone landfalls then evacuation will be effective [9]. The evacuation prior to cyclone landfall is considered as one of the best practices to minimise death tolls from a catastrophe by moving people from exposed areas to the safer places and MPCSs, temporarily.

Though there are several man-made and natural factors that discourages selfevacuation of community people, disaster management authorities are responsible to encourage and rescue them into MPCSs. This study developed an easier search and rescue operation that could be implemented in the coastal zone of disasterprone countries like Bangladesh. This investigation emphasises on the evacuation and rescuing of vulnerable community people earlier a cyclone hits an area to reduce death tolls to zero.
