Editor's Note

The international conference “Disruptive Technologies Tech Ethics and Artificial Intelligence” (DITTET) provides a forum to present and discuss the latest scientific and technical advances and their implications in the field of ethics. It also provides a forum for experts to present their latest research in disruptive technologies, promoting knowledge transfer. It provides a unique opportunity to bring together experts in different fields, academics, and professionals to exchange their experience in the development and deployment of disruptive technologies, artificial intelligence, and their ethical problems. This Special Issue contains extended versions of selected works presented at the 1st International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence (DiTTEt 2021), held in Salamanca (Spain) in September 2021

Taranis: Neural networks and intelligent agents in the early warning against floods

The following article proposes the implementation of a system based on neural networks of CounterPropagation type and intelligent agents for analysis and assessment of the risk of flood caused by rain, in addition to the implementation of agents in mobile devices for the presentation of alerts. Because as is known, natural phenomena have always existed, but in recent years as a result of global warming we have seen that floods are becoming more frequent, which has forced the creation of specialized agencies and intelligent mechanisms to prevent the loss of human lives due to these phenomena

Traffic Optimization Through Waiting Prediction and Evolutive Algorithms

Traffic optimization systems require optimization procedures to optimize traffic light timing settings in order to improve pedestrian and vehicle mobility. Traffic simulators allow obtaining accurate estimates of traffic behavior by applying different timing configurations, but require considerable computational time to perform validation tests. For this reason, this project proposes the development of traffic optimizations based on the estimation of vehicle waiting times through the use of different prediction techniques and the use of this estimation to subsequently apply evolutionary algorithms that allow the optimizations to be carried out. The combination of these two techniques leads to a considerable reduction in calculation time, which makes it possible to apply this system at runtime. The tests have been carried out on a real traffic junction on which different traffic volumes have been applied to analyze the performance of the system

Improving Production in Small and Medium Enterprises

Knowledge management has gained relevance during the last years to improve business functioning. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to detect and predict undesired situations. This article present a multi-agent system aimed at detecting risky situations. The multi-agent system incorporates models for reasoning and makes predictions using case-based reasoning. The models are used to detect risky situations and an providing decision support facilities. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented

An adaptive algorithm for feature selection in pattern recognition

With the most recent advances in bioinformatics, the amount of information available for analysing certain diseases has increased considerably. Specifically, the use of microarrays makes it possible to obtain information on genetic patterns. The analysis of this information requires the use of new computational models and the modification of existing models so that it becomes possible to work with such an elevated amount of data. This study will demonstrate the integration of an expression analysis in a case-based reasoning system that can apply data mining techniques to classify and obtain patterns that have been stored in a case database for leukaemia patients

Mitigation of the Ground Reflection Effect in Real-Time Locating Systems

Real-Time Locating Systems (RTLS) are one of the most promising ap- plications based on Wireless Sensor Networks and represent a currently growing market. However, accuracy in indoor RTLS is still a problem requiring novel solu- tions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radio frequency waves, such as attenuation, diffrac- tion, reflection and scattering. These effects can lead to other undesired problems, such as multipath and the ground reflection effect. This paper presents an innova- tive mathematical model for improving the accuracy of RTLS, focusing on the mitigation of the ground reflection effect by using Artificial Neural Networks

Computer Vision Based Indoor Navigation: A Visual Markers Evaluation

The massive diffusion of smartphones and the exponential rise of location based services (LBS) have made the problem of localization and navigation inside buildings one of the most important technological challenges of the last years. Indoor positioning systems have a huge market in the retail sector and contextual advertising; moreover, they can be fundamental to increase the quality of life for the citizens. Various approaches have been proposed in scientific literature. Recently, thanks to the high performances of the smartphones’ cameras, marker-less and marked-based computer vision approaches have been investigated. In a previous paper, we proposed a technique for indoor navigation using both Bluetooth Low Energy (BLE) and a 2D visual markers system deployed into the floor. In this paper, we present a qualitative performance evaluation of three 2D visual markers suitable for real-time applications

Technological Platform to Facilitate the Labor Integration of People with Auditory Impairements

This paper presents a technological platform aimed at obtaining an on-line workspace for exchanging digital contents in an easy, intuitive and accessible manner. The main objective of the platform is to provide facilities to inform, train and evaluate the competencies of disabled people, and more specifically those skills required to facilitate the labor integration of individuals with auditory disabilities. The platform also focuses on providing training processes that facilitate the incorporation of disabled people to labor environments. The platform presented in this paper has been tested in a real environment and the results obtained are promising

Multi-agent System for Tracking and Classification of Moving Objects

In the past, computational barriers have limited the complexity of video and image processing applications but recently, faster computers have enabled researchers to consider more complex algorithms which can deal successfully with vehicle and pedestrian detection technologies. However, much of the work only pays attention to the accuracy of the final results provided by the systems, leaving aside the computational efficiency. Therefore, this paper describes a system using a paradigm of multi-agent system capable of regulating itself dynamically taking into account certain parameters pertaining to detection, tracking and classification, to reduce the computational burden as low as possible at all times without this in any way compromise the reliability of the result

Hear4All: Herramienta de traducción y generación de lenguaje de signos en tiempo real para el aula mediante tecnologías disruptivas

[EN] Traditionally, text-to-speech has helped people overcome decoding difficulties with learning or hearing disabilities. Thanks to technological advances, consuming content in which learners use text and audio is more common. However, sign language allows an improvement in the transfer of knowledge and the integration of students with functional diversity. This tool allows the simultaneous translation into sign language of the teacher or speaker and dynamizes the learning of this by the classmates, improving the possibilities of socialization and exchange. In order to test the functionality of the application, a pilot test was carried out with the students of the Teaching Degree in the Special Educational Needs specialty in five face-to-face sessions. Among the contents that these students must acquire is the knowledge of sign language, valuing the application as very useful for learning and classroom use of this tool. It can also be used to promote communication between professionals in the workplace. In conclusion, we can highlight creating a tool for simultaneous translation into sign language applicable to the educational and socio-labor fields.[ES] Tradicionalmente, la conversión de texto a voz ha ayudado a las personas con problemas de aprendizaje o audición a superar las dificultades de decodificación. Gracias a los avances en la tecnología, consumir contenidos en los que texto y audio sean utilizados por los alumnos es más frecuente. Sin embargo la utilización de lengua de signos permite una mejora en la transferencia de conocimientos y la integración del alumnado con diversidad funcional. Esta herramienta permite la traducción simultánea a lengua de signos del profesor o ponente, así como dinamizar el aprendizaje de este por parte de los compañeros, mejorando las posibilidades de socialización e intercambio. Para probar la funcionalidad de la aplicación, se realizo un pilotaje con los alumnos del Grado de Magisterio en la especialidad de Necesidades Educativas Especiales en cinco sesiones presenciales. Entre los contenidos que estos alumnos deben adquirir esta el conocimiento de la lengua de signos, valorando la aplicación como muy útil para el aprendizaje y el uso en clase de esta herramienta. Además puede utilizarse para fomentar la comunicación entre los profesionales en el ámbito laboral. Como conclusión podemos destacar la creación de una herramienta de traducción simultanea a lengua de signos aplicable al ámbito educativo y socio-laboral.Silva, L.; Alonso Correa, IP.; Sánchez San Blas, H.; Sales Mendes, A.; Bermejo Gil, B.; Pérez Robledo, F.; Lozano Murcielago, A.... (2022). Hear4All: Herramienta de traducción y generación de lenguaje de signos en tiempo real para el aula mediante tecnologías disruptivas. Editorial Universitat Politècnica de València. 1152-1162. https://doi.org/10.4995/INRED2022.2022.159161152116