## 2 Related Work
### Cooperative Networks  
Cooperative networks are designed to share resources and perform specific activities with all network elements. All implementations use strict rules and protocols, meaning that a network member must be strongly compromised. Nodes are prioritized over the network. Cooperative networks provide significant benefits for telecommunications companies since sharing resources allows infrastructures to be joined that increase the network's coverage radius [45].  
In cooperative wireless networks, wireless agents can increase their adequate quality of service (measured by bit error rates, block error rates or outage probability) by cooperating. In a cooperative communication system, each wireless user is assumed to transmit data and act as a cooperative agent for another user [46]. Cooperation allows trade-offs in code rates and transmission power. In addition, more power is needed because each user, when in cooperative mode, is transmitting to both users. On the other hand, the reference transmission power for both users will be reduced due to diversity. In cooperative communication, each user transmits both his bits and some information to his partner; we might think this causes a system's loss of speed. However, the spectral efficiency of each user improves because, due to the cooperation's diversity, the channel's code rates can increase [47]. This communication type can be highlighted using protocols such as Zigbee, where the user or end device can function as an available node to represent the user and relay part. Each of these devices has independent fading paths due to the qualities it gains within cooperative networks.  
[PERSON] et al. [48] discuss the use of WSNs for wildfire monitoring. The forest environment presents challenges for WS such as wide coverage areas and the shadowing effect caused by trees. To address these challenges, the authors propose a new methodology for designing and optimizing WSN based on energy conservation and transmission quality. Cooperative communication is a promising solution for enhancing WSN lifetime by allowing multiple nodes to share resources and transmit data. The authors use reinforcement learning with opponent modeling to optimize a cooperative communication protocol based on RSSI and node energy consumption. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay and energy consumption.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Reference** & **Monitoring** & **Wireless** & **Measured Parameters** & **Experiment** & **Vital Sign** \\  & **System** & **Technology Used** & **Time** & **Analysis** \\ \hline
[36] & Wearable & Bluetooth Low & Heart rate, & & 1 day & No \\
[37] & In-home & ZigBee & Activity, fall detection & 1 year & No \\
[38] & In-home & ZigBee & Activity, sleep, & & \\  & & & medication adherence & 3 months & No \\
[39] & Wearable & Wi-Fi & Gait, fall risk & 1 week & No \\
[40] & In-home & Wi-Fi & Activity, sleep & 6 months & No \\
[41] & In-home & ZigBee & Blood pressure, heart & 6 months & Yes \\  & & & rate, activity & & \\
[42] & In-home & Bluetooth Low & Blood pressure, heart & 1 year & Yes \\  & & Energy & rate, weight & & \\
[43] & In-home & ZigBee & Activity, heart rate, & & \\  & & & respiration rate & & \\
[44] & In-home & Bluetooth Low & & & \\  & & Energy & Activity, sleep, gait & 3 months & Yes \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of related works and current paper references on monitoring of older people with wireless sensor networks