Alberto Rivas

New mapping and location applications focus on offering improved usability and services based on multi-modal door to door passenger experiences. This helps citizens develop greater confidence in and adherence to multi-modal transport services. These applications adapt to the needs of the user during their journey through the data, statistics and trends extracted from their previous uses of the application. The My-Trac application is dedicated to the research and development of these user-centered services to improve the multi-modal experience using various techniques. Among these techniques are preference extraction systems, which extract user information from social networks, such as Twitter. In this article, we present a system that allows to develop a profile of the preferences of each user, on the basis of the tweets published on their Twitter account. The system extracts the tweets from the profile and analyzes them using the proposed algorithms and returns the result in a document containing the categories and the degree of affinity that the user has with each category. In this way, the My-Trac application includes a recommender system where the user receives preference-based suggestions about activities or services on the route to be taken.

Increasing user engagement is one of the biggest challenges when a new application is developed. An engaged user is one who finds a product valuable; highly engaged users generate profit. This study focuses on increasing user engagement in a transport application, via a user reputation score feature. The score is to reward application users and activity organisers, as well as to motivate beginners by offering a high reputation score in the first days of use. The algorithms are based on exponential and logarithmic functions, and were first tested on synthetic data. Real-world tests have shown that the algorithms behave as expected, but the COVID-19 pandemic created a disturbance which prevented any user from achieving the maximum score and many users from registering altogether. Data show positive results, although the real number of users is not sufficient to certify a correct behaviour. Further tests will be carried out when transport activities return to normal.

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.

Recommender systems (RSs) play a very important role in web navigation, ensuring that the users easily find the information they are looking for. Today's social networks contain a large amount of information and it is necessary that they employ a mechanism that will guide users to the information they are interested in. However, to be able to recommend content according to user preferences, it is necessary to analyse their profiles and determine their preferences. The present work proposes a job offer RS for a career‐oriented social network. The recommendation system is a hybrid, it consists of a case‐based reasoning (CBR) system and an argumentation framework, based on a multi‐agent system (MAS) architecture. The CBR system uses a series of metrics and similar cases to decide whether a job offer is likely to be recommended to a user. Besides, the argumentation framework extends the system with an argumentation CBR, through which old and similar cases can be obtained from the CBR system. Finally, a discussion process is established amongst the agents who debate using their experience from past cases to take a final decision.

El medio ambiente se constituye en una de las fuentes más necesarias para la pervivencia del hombre, pero también en ese eje necesario para la vida de los demás seres vivos que condicionan la vida. No es de oculto conocimiento que históricamente se han venido haciendo esfuerzo para la protección al medio ambiente pero estos han sido puros pañitos de agua tibia, claro ejemplo de ellos nos demuestra las constantes y significativas afectaciones al Medio ambiente en nuestro país y otros países del sistema interamericano de derechos humanos. Nuestro Departamento del Chocó, como uno de los más biodiversos del Estado colombiano, ha venido sufriendo en carne propia las afectaciones directas al medio ambiente lo que se evidencia en casos como lo ocurrido en el Municipio de Rio Quito, y Unguía, donde se evidencian nocivas afectaciones en nuestro entorno y que de manera clara repercute en la salud humana (mal formaciones en los efectos, contaminación del agua, del aire, erosión del suelo entro otras). Por ello la presente propuesta gira entonces en la viabilidad de reconocer el medio ambiente como un derecho humano de forma autónoma, esto es que se proteja de manera inmediata sin necesidad que para la garantía del mismo se haga para en últimas beneficiar a un individuo de la especie humana.