This study aims to enhance elderly fall detection systems by using the YOLO (You Only Look Once) object detection algorithm with pose estimation, improving both accuracy and efficiency. Utilizing YOLOv7-W6-Pose’s robust real-time object detection and pose estimation capabilities, the proposed system can effectively identify falls in video feeds by using a webcam and process them in real-time on a high-performance computer equipped with a GPU to accelerate object detection and pose estimation algorithms. YOLO’s single-stage detection mechanism enables quick processing and analysis of video frames, while pose estimation refines this process by analyzing body positions and movements to accurately distinguish falls from other activities. Initial validation was conducted using several free videos sourced online, depicting various types of falls. To ensure real-time applicability, additional tests were conducted with videos recorded live using a webcam, simulating dynamic and unpredictable conditions. The experimental results demonstrate significant advancements in detection accuracy and robustness compared to traditional methods. Furthermore, the approach ensures data privacy by processing only skeletal points derived from pose estimation, with no personal data stored. This approach, integrated into the NeuroPredict platform developed by our team, advances fall detection technology, supporting better care and safety for older adults.

Number of people 65+ is increasing all over the word, accompanied by illness, disability, vulnerability and dependence, thus potentially putting enormous stress on healthcare and long-term care costs. Creating an enabling environment that allows people with care needs to live at their homes as long as possible remains the main challenge of the long-term care system. Our paper presents RO-SmartAgeing system, an IoT-based system for remote monitoring of older people heath. Its functions and advantages for elderly are underlined.

In the context of a fast aging population and of its increasing need for healthcare and assistance, ubiquitous usage of Internet of Things (IoT)-based smart applications can mitigate the consequential social burden. Connected sensors and devices inside the seniors' home produce a significant amount of data about them and their daily activities. IoT and Big Data Analytics (BDA) are an important mean to derive knowledge and support for improving the life conditions for the older adults by increasing the role of Information and Communication Technology (ICT) for accomplish this goal. IoT analytics can aid in personalizing applications that benefit both elderly people and the ever-growing industries that need adapt their offer to the consumer's profiles. This paper presents a new platform that enables innovative analytics on IoT captured data from smart residences of elderly people. A solution based on the use of fog nodes and cloud system is suggested in order to afford data-driven services and to manage the complexity and provision of the necessary resources for online and offline data processing, storage, and analysis. The requirements and the design of the platform architecture are underlined. We propose an architecture of a platform based on fog computing nodes coupled with cloud computing that offers an efficient near real time processing of the big data resulted from IoT system that provides insights and data processing and analysis facilities into cloud. This integrated design has an important impact on time sensitive applications by addressing the latency issues of cloud.

Global ageing enforces health systems to meet the increasing demands of silver digital patients - elderly empowered by ICT. Big Data provides support for a better management of seniors' health and healthcare. Cloud computing enables Big Data operations with provision of large storage and processing power. This paper underlines opportunities brought by these approaches to health services targeting seniors. Pursuing the directions established by the National Strategy on Digital Agenda for Romania regarding the Big Data integration in health system, an emphasis is put on the perspectives brought by Big Data in expanding the results of some recent research projects.