People in Europe are living longer than ever before, and the age distribution of the population is changing rapidly. According to demographic trends, the population of older people (those aged 65 years or more) in the EU will increase significantly, rising from 90.5 million at the start of 2019 to reach 129.8 million by 2050. This tendency has led to an increase in the demand for additional care and services for the elderly. A dramatic growth in modern technologies has accelerated the development of smart medical devices that provide more convenience to people with degenerating physical and cognitive abilities. Smart grids are advanced electrical systems utilizing digital technology to monitor, control, and optimize the distribution and use of electricity. This system is applicable alongside the Internet of Things (IoT) to establish an advanced and optimized structure in wellness and health sector, like telemedicine, smart hospitals, and modern medical devices. The Smart Grid Architecture Model (SGAM) is a reference structure, considering all aspects of interoperability layers with the smart grid plane, including zones and domains. This study introduces a new way to use SGAM together with IoT, allowing digital medical devices to connect with online services to assess how these devices help elderly people in terms of energy use, cost savings, and overall health benefits. The results provided a detailed analysis of the benefit-cost ratio and net present value of using digital healthcare devices, demonstrating that long-term financial benefits outweigh the initial investment. The energy consumption of the devices improved through applying the new simplified model. Reduction of overall energy and electricity usage obtain by employing energy-saving management features. Using these devices regularly can boost both mental and physical health and enhance the quality of life for European aged populations.

Smart Grid and Medical Devices for Elderly Care in Europe: Benefits, Remote Monitoring, and Energy Management

AGHAJANI, AZAD
2024/2025

Abstract

People in Europe are living longer than ever before, and the age distribution of the population is changing rapidly. According to demographic trends, the population of older people (those aged 65 years or more) in the EU will increase significantly, rising from 90.5 million at the start of 2019 to reach 129.8 million by 2050. This tendency has led to an increase in the demand for additional care and services for the elderly. A dramatic growth in modern technologies has accelerated the development of smart medical devices that provide more convenience to people with degenerating physical and cognitive abilities. Smart grids are advanced electrical systems utilizing digital technology to monitor, control, and optimize the distribution and use of electricity. This system is applicable alongside the Internet of Things (IoT) to establish an advanced and optimized structure in wellness and health sector, like telemedicine, smart hospitals, and modern medical devices. The Smart Grid Architecture Model (SGAM) is a reference structure, considering all aspects of interoperability layers with the smart grid plane, including zones and domains. This study introduces a new way to use SGAM together with IoT, allowing digital medical devices to connect with online services to assess how these devices help elderly people in terms of energy use, cost savings, and overall health benefits. The results provided a detailed analysis of the benefit-cost ratio and net present value of using digital healthcare devices, demonstrating that long-term financial benefits outweigh the initial investment. The energy consumption of the devices improved through applying the new simplified model. Reduction of overall energy and electricity usage obtain by employing energy-saving management features. Using these devices regularly can boost both mental and physical health and enhance the quality of life for European aged populations.
2024
2025-10-20
Smart Grid and Medical Devices for Elderly Care in Europe: Benefits, Remote Monitoring, and Energy Management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12075/23343