## 3 Results and Discussion
#### 3.1.1 Intelligent Homes  
Considering the Internet of Things perspective and the growing popularity of smart cities, significant technological advancements have emerged for the monitoring of vital signs and recognition of human activity using sensor networks interconnected through wireless technology using microcontrollers such as ESP8266, ESP32, and ATMega models. Their high level of integration and ease of use have been fundamental in developing smart home health monitoring systems. One study [34] provides an essential framework for the development of healthcare IoT systems since it is important to have the necessary hardware resources to provide time-critical responses to emergencies that may arise when working in the healthcare area. Regarding home care-based systems, a prototype device was developed that could acquire and remotely monitor patients' heart rates and blood oxygen saturation [35]. A dependable patient management system using IoT technology allows healthcare professionals to monitor hospital and at-home patients by continuously tracking vital signs using sensors. Additionally, it incorporates a camera and AI technology for image analysis, enabling the detection and classification of actions such as standing, bending, and falling [36]. Meanwhile, LI-Care, an e-health monitoring system based on LabVIEW and IoT technology, is aimed at cost-effective health condition diagnosis, tailored to hospitalized patients or those confined to bed at home [37]. [PERSON] et al. have developed an innovative smart mattress system capable of measuring patients' respiration and heart rate by detecting subtle body movements. This is achieved using commercially available, low-cost, plastic optical fibers embedded within the mattress. The system's design facilitates its large-scale production and deployment for overnight sleep monitoring [29]. Another group has developed a cyber-physical system-based home robotic system combined with artificial intelligence (AI), intelligent wearable sensors, and remote sensing. The system was implemented using a Raspberry Pi Pico (Raspberry Pi Ltd., Cambridge, UK) and sensing modules to measure patients' SPO2, heart rate, and body temperature, with features like fall detection and GPS location detection [33]. A novel non-contact respiration detection method has been proposed, incorporating remote interaction capabilities. The authors have established a three-tier architecture, encompassing IoT, intelligent terminal (IT), and cloud components, which facilitate data acquisition, signal transmission, remote interaction, and diagnosis [38]. A household monitoring system has also been developed for the tracking of multiple physiological signals, aiming to facilitate health management for elderly, weak, and chronically ill individuals in the comfort of their homes [39]. Another group has explored the use of assistive health systems to improve the quality of life of elderly individuals living at home [40]. The authors introduce a comprehensive, unobtrusive system for the in-home health monitoring of elderly individuals, using a range of sensors to collect data non-intrusively while preserving privacy. This ensures continuous health monitoring with full living space coverage [41]. Other authors have proposed a novel home-based monitoring (HM) concept using spatiotemporal visual learning (STVL-HM). The system collects data from wearable sensors and smart devices in the home [42]. Moreover, an innovative RFID-based approach for accurate and continuous respiration monitoring in mobile users has been presented; this methodology effectively addresses challenges such as body movement and phase ambiguity [43]. The SMARTCARE system is an IoT solution that combines home automation systems with medical monitoring devices [44].