Deepint.net: A Rapid Deployment Platform for Smart Territories.
Juan Manuel Corchado RodríguezPablo ChamosoGuillermo HernándezAgustín San Roman GutierrezAlberto Rivas CamachoAlfonso González-BrionesFrancisco Pinto-SantosEnrique GoyenecheaDavid Garcia-RetuertaMaría Alonso-MiguelBeatriz Bellido HernandezDiego Valdeolmillos VillaverdeManuel Sanchez-VerdejoPablo Plaza-MartínezManuel López-PérezSergio Manzano-GarcíaRicardo S AlonsoRoberto Casado-VaraJavier Prieto TejedorFernando de la PrietaSara Rodríguez-GonzálezJavier Parra-DomínguezMohd Saberi MohamadSaber TrabelsiEnrique Díaz-PlazaJose Alberto Garcia-CoriaTan YigitcanlarPaulo NovaisSigeru OmatuPublished in: Sensors (Basel, Switzerland) (2021)
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.