## 7 Results
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Metric** & **Zigbee** & **SD (\%)** & **LoRaWAN** & **SD (\%)** & **WiFi** & **SD (\%)** & **BLE** & **SD (\%)** \\ \hline Transmission rate (Kbps) & 250 & NA & 27 & NA & 165,000 & NA & 25,000 & NA \\ Delay end-to-end (s) & 2.81 & 1.14 & 3.92 & 1.13 & 3.04 & 1.14 & 3.50 & 1.15 \\ Retransmissions & 1.82 & 1.14 & 2.63 & 1.24 & 2.55 & 1.14 & 2.21 & 1.14 \\ Channel retries & 2.04 & 1.10 & 2.84 & 1.20 & 3.33 & 1.11 & 2.61 & 1.06 \\ Disconnection nodes (\%) & 0.89 & 1.09 & 2.15 & 1.22 & 2.83 & 1.22 & 1.06 & 1.23 \\ Packet loss (\%) & 9.00 & 1.13 & 12.0 & 1.08 & 10.0 & 1.19 & 11.00 & 1.20 \\ Available routes (\%) & 65 & 1.11 & 74 & 1.21 & 65 & 1.22 & 83 & 1.14 \\ Overhead (\%) & 33 & 1.04 & 40 & 1.08 & 45 & 1.10 & 38 & 1.20 \\ Resilience (s) & 3.20 & 1.20 & 2.80 & 1.11 & 3.50 & 1.21 & 2.90 & 1.22 \\ Energy consumption (J) & 3.05 & 1.17 & 3.80 & 1.14 & 5.10 & 1.18 & 4.70 & 1.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Nodes under the collaborative scheme. so it has a higher probability of collisions. Another important metric is resilience, in this case BLE and LoRa have the best response times, since after a failure they return to a normal operating state in a shorter time than WiFi and ZigBee. In the collaborative scheme specified in Table 3, which consists of sharing resources and functions only if the sensor has availability, the sensor priorities are over the network priorities. In comparison with the results of Table 2, the end-to-end delay increases; however, the ZigBee remains the fastest. Following this trend, retransmissions as well as lost packets increase. Because the retransmissions increased in all the protocols, it is expected that the percentage of overhead will also increase, since more packets are sent. Finally, it is important to mention that in critical applications where safety becomes a priority, two characteristics of the network are of high importance: resilience and availability. However, Table 3 shows that the resilience time increased with respect to the configuration of Table 2, therefore in collaborative scheme, it will take more time to achieve a normal operating state after a failure, a key factor in critical systems. On the other hand, the energy consumption directly affects the availability, most of the sensors are battery powered, i.e., the more energy they consume the faster the battery will run out. In this aspect, the collaborative scheme is better, since it consumes less energy, being ZigBee the protocol with the lowest consumption. These Figures 8 and 9 show random measurements (11 for each wireless technology). These figures are intended to show the intensity of the received signal. In this way, we can see under which scheme we can determine if a signal is sufficient to establish a wireless connection when other technologies and diverse environmental situations are present. Then, each of these measurements helps us to know the strength with which the devices listen or could hear the signal at that specific point. Likewise, we observe that for both schemes, WiFi is the technology with higher RSSI levels (in dBm), which shows that there are areas of very low signal coverage, while the technology that exhibits the best levels (very good coverage) presents is LoRa, possibly because its operating frequency is different and faces fewer collisions. The position of each measurement was performed in a uniformly distributed manner throughout the area of the university campus, where the sensors were located. For the cooperative scheme shown in Figure 8, the average RSSI value in dBm for BLE is \(-90.36\), for ZigBee it is \(-85.36\), for WiFi it is \(-99.09\) and for LoRa it is \(-68.36\). For the collaborative scheme shown in Figure 9, the average RSSI value in dBm for BLE is \(-92.73\), for ZigBee it is \(-87.91\), for WiFi it is \(-100.73\) and for LoRa it is \(-71.82\). We can then state that both schemes differ between 8 and 10% with the cooperative scheme being less interfering.