Deepint.net: A Rapid Deployment Platform for Smart Territories.

Juan M Corchado,Fernando De La Prieta,Sigeru Omatu,Enrique Díaz-Plaza,Diego Valdeolmillos Villaverde,Manuel Sanchez-Verdejo,Francisco Pinto-Santos,Saber Trabelsi,Guillermo Hernández,Pablo Chamoso,Javier Parra-Domínguez,Pablo Plaza-Martínez,Mohd Saberi Mohamad,Agustín San Roman Gutierrez,Ricardo S Alonso,Beatriz Bellido Hernandez,María Alonso-Miguel,Jose Alberto Garcia-Coria,Enrique Goyenechea,Paulo Nováis ,Tan Yiğitcanlar ,Alfonso González‐Briones ,Javier Prieto ,Manuel J López‐Pérez ,Sergio Manzano ,David Garc­ía-Retuerta ,Sara Rodríguez González ,Alberto Rivas ,Roberto Casado‐Vara

doi:10.3390/s21010236

Abstract

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.

Highlights

A smart city (SC) is an environment that uses innovative technologies to make networks and services more flexible, effective, and sustainable with the use of information, digital and telecommunication technologies, improving the city operations for the benefit of its citizens
The platform helps the users select and use the most adequate combination of mathematical models; dynamic data assimilation and neurosymbolic artificial intelligence systems are capable of working with knowledge and data; they adapt to new time constraints and can explain why a certain decision has been taken
The SC concept emerged as the integration of the urban environment with information and communication technologies (ICTs), attracting the interest of all major sectors in presenting solutions or developments that would make up a SC [22]

Summary

Introduction

A smart city (SC) is an environment that uses innovative technologies to make networks and services more flexible, effective, and sustainable with the use of information, digital and telecommunication technologies, improving the city operations for the benefit of its citizens. Most experts agree on the fact that such population densities promote sustainable economic growth, which explains the increased mobility of the population from rural to urban areas The downside of these advantages is the rise of uncontrollable sociological phenomena, such as urban violence and unhealthy crowding. The platform is equipped with the vast majority of the required connectors, facilitating its integration Such is the added value of the data that cities/territories and users and companies in all sectors have been interested in AI-based data analysis and visualization methodologies. The platform helps the users select and use the most adequate combination of mathematical models; dynamic data assimilation and neurosymbolic artificial intelligence systems are capable of working with knowledge and data; they adapt to new time constraints and can explain why a certain decision has been taken.

Smart Territory Platforms and the Edge Computing Approach

Case Study

Findings

Pareto Optimal Location Algorithm