BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain.
Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain.
Sensors (Basel). 2021 Jan 1;21(1):236. doi: 10.3390/s21010236.
This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris-Vélib' Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.
本文提出了一个用于智能领土管理的高效的网络物理平台。它是高效的，因为它促进了数据采集和数据管理方法的实施，以及数据表示和仪表板配置。该平台允许使用任何类型的数据源，从多功能物联网传感器的测量值到关系型和非关系型数据库。它也是智能的，因为它包含了一个完整的人工智能套件，用于数据分析；它包括数据分类、聚类、预测、优化、可视化等技术。它还与边缘计算概念兼容，允许智能的分布和智能传感器的使用。智慧城市的概念正在发展和适应新的应用；创建智能社区、区域或领土的趋势越来越流行，而不是以前管理整个特大城市的方法。本文介绍了该平台，并描述了其架构和功能。此外，还在一个案例研究中验证了其运行情况，其中管理了巴黎-Vélib' Métropole 的自行车租赁服务。该平台可以使智能领土能够开发适应性知识管理系统，适应新的要求和使用多种类型的数据，并执行高效的计算和人工智能算法。该平台通过从物联网传感器、数据库、互联网等获取数据的可解释人工智能模型，优化人类专家的决策。该平台的全局智能可以与边缘安装的智能节点协调其决策过程，这些节点将使用最先进的数据处理技术。
