Integrated Management of Energy, Wellbeing and Health in the Next Generation of Smart Homes
Integrated Management of Energy, Wellbeing and Health in the Next Generation of Smart Homes
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DOI：
10.3390/s19030481
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发表时间：
2019-02-01
期刊：
影响因子：
3.9
通讯作者：
Bouabdallah, Ahmed
中科院分区：
文献类型：
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作者：
Jaouhari, Saad E. L.;Palacios-Garcia, Emilio Jose;Bouabdallah, Ahmed
这一贡献提出了下一代智能家居的实现，其中异构数据，来自多个传感器（医疗，健康，能源，上下文等）。和家用设备（智能冰箱、智能电视等），需要管理、安全和可视化。作为第一步，它只关注能源和健康数据。然而，它旨在为管理任何类型的信息奠定基础，以实现与房屋的智能交互，其中可能包括人工智能和机器学习。这些数据是使用位于智能家居内部的中央物联网网关安全收集的。对于电子健康部分，提供了一组可能的用例，沿着植入的当前进度。在这方面，主要想法是将下一代智能家居与外部医疗实体联系起来，以便在检测到异常的情况下提供快速干预，并能够提供基本医疗服务，例如针对特定健康问题与医生进行远程咨询。这一愿景非常有希望，特别是在难以获得医疗服务的农村地区。至于能源部分，其目的是收集智能家居内用户的能源消耗，这些能源可以从不同的来源（热，水，天然气或电力）提供，并使用先进的算法来预测和管理本地能源消耗和生产（如果有的话）。这种方法结合了从智能电表收集的数据、智能能源设备的运行信息（智能插头的状态）、用户请求和外部网络信号（如能源价格）。通过使用接受这种输入参数的家庭能量管理系统，可以根据不同的目标（例如，最小化能量成本和最大化用户的舒适度）。
This contribution proposes an implementation for next generation smart homes, where heterogeneous data, coming from multiple sensors (medical, wellbeing, energy, contextual, etc.) and house equipment (smart fridge, smart TV, etc.), need to be managed, secured and visualized. As a first step, it focuses only on energy and health data. However, it aims to lay the foundations to manage any type of information towards the development of smart interactions with the house, which might include artificial intelligence and machine learning. These data are securely collected using a central Web of Things gateway, located inside the smart home. For the e-health part, a set of possible use-cases is provided, along with the current progress of the implantation. In this regard, the main idea is to link the next generation smart homes with external medical entities in order to provide, first, quick intervention in the event of an abnormality being detected, and to be able to provide basic medical services such as remote consultations with a doctor for a particular health issue. This vision can be very promising, particularly in rural areas, where access to medical services is difficult. As for the energy part, the aim is to collect users' energy consumption inside the smart home, which can be supplied from different sources (heat, water, gas, or electricity), and to enable the use of advanced algorithms to predict and manage local energy consumption and production (if any). This approach combines data collected from smart meters, operational information of the smart energy devices (the status of smart plugs), user's requests and external network signals such as energy prices. By using a home energy management system that accepts such input parameters, the operation of in-home devices and appliances can be optimally controlled according to different objectives (e.g., minimizing energy costs and maximizing user's comfort level).