## 3 Materials and Methods  
This section presents the monitoring system of sensors, routers, and concentrators with its technical specifications. In addition, real photos of some installations of the nodes and their power supply are shown. The technical description of each type of system device is provided. Finally, we present the methodology of the experiment and the analyses carried out on the information of the vital signs metrics measured for each person during the experiments. The connection between sensors, security, and the activities of the elderly population is multifaceted:  
Sensor System for Monitoring: The sensor system collects data from various sensors, including motion, pressure, temperature, humidity, noise, light, gyroscope, and air quality sensors. These sensors are designed to monitor the home environment and the elderly individual's vital signs while being unobtrusive and comfortable for the user. Security and Privacy: The work emphasizes the need for non-invasiveness and respect for the privacy of the elderly. The data collected by the sensor network must be securely transmitted and stored to protect the individual's sensitive health information. Ensuring data security and privacy is crucial in healthcare applications, especially when dealing with sensitive data from vulnerable populations. Activities of the Elderly: The sensor system aims to capture data related to the activities of the elderly in their homes. It tracks sleep patterns, movement, noise levels, and air quality to identify anomalies and provide personalized recommendations for improving sleep quality. By understanding the person's daily activities, the system can offer relevant and targeted suggestions to enhance their well-being. Wireless Sensor Network (WSN) and Communication Protocols: The work highlights the importance of using WSNs and communication protocols to efficiently collect and transmit data from the sensors. The system uses wireless communication to transmit the collected data to a central hub or concentrator node, where it is processed and analyzed. The use of efficient communication protocols is crucial for optimizing data transmission and reducing energy consumption. Energy-Saving Algorithm: The proposed energy-saving algorithm is integrated into the sensor system to optimize power consumption. It allows the system to be proactive or reactive, depending on the level of change in the measured parameters. Proactive mode ensures continuous monitoring when parameters show high variability, while reactive mode conserves energy by collecting data only on demand when the parameters are stable. The impact of this work lies in its potential to revolutionize remote monitoring systems for elderly individuals, particularly in the context of sleep monitoring and healthcare assistance. By using WSNs and intelligent algorithms, the system can efficiently collect and analyze data, providing real-time feedback and personalized recommendations to improve sleep quality and overall health. The non-invasive nature of the system allows elderly \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Algorithm** & **Type** & **Impacting Metrics** & **Global Consumption Reduction** \\ \hline Sleep-Scheduler [42] & Sleep-based & Energy efficiency, latency & 40–60\% \\ Energy-Aware Tree-Based & & Network lifetime, energy & 15–40\% \\ Routing [43] & Tree-based & efficiency & \\ Distributed Collaborative & Energy efficiency, routing & 50\% \\ Routing [44] & Collaborative & efficiency & \\ Multi-Objective Optimized & Energy efficiency, network & 30–50\% \\ Routing [45] & Multi-objective & lifetime & \\ Adaptive Clustering with & & Energy efficiency, QoS, network & 30–50\% \\ QoS [46] & Cluster-based & lifetime & \\ Adaptive compression [47] & Threshold-based & Energy efficiency, latency & 50–60\% \\ QoI-aware [48] & Sleep-based & Energy efficiency, latency & 50\% \\ Our work & Reactive mode based & Energy efficiency, latency & 50\% \\ \hline \hline \end{tabular}
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