Autonomous cycle of data analysis tasks for scheduling the use of controllable load appliances using renewable energy

International Conference on Computational Science and Computational Intelligence, 15/12/2021-17/12/2021, Estados Unidos.With the arrival of smart edifications with renewable energy generation capacities, new possibilities for optimizing the use of the energy network appear. In particular, this work defines a system that automatically generates hours of use of the controllable load appliances (washing machine, dishwasher, etc.) within these edifications, in such a way that the use of renewable energy is maximized. To achieve this, we are based on the hypothesis that depending on the climate, a prediction can be made of how much energy will be generated and, according to the behavior of the users, the energy demand required by these appliances. Following this hypothesis, we build an autonomous cycle of data analysis tasks composed of three tasks, two tasks for estimating the required load (demand) and the renewable energy produced (supply), coupled with a scheduling task to generate the plans of use of appliances. The results indicate that it is possible to carry out optimal scheduling of the use of appliances, but that they depend on the quality of the predictions of supply and demand.European CommissionAgencia Estatal de InvestigaciónJunta de Comunidades de Castilla-La Manch

A semi-supervised learning approach to study the energy consumption in smart buildings

IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021), 05/12/2021-07/12/2021.In this work, we use the semi-supervised LAMDA-HSCC algorithm for characterizing the energy consumption in smart buildings, which can work with labeled and unlabeled data. Particularly, it uses the LAMDA-RD approach for the clustering problem and the LAMDA-HAD approach for the classification problem. Additionally, this algorithm uses three submodels for merging, partition groups (classes/cluster) and migrating individuals from a group to another. For the performance evaluation, several datasets of energetic consumption are used, with different percent of labeled data, showing very encouraging results according to two metrics in the semi-supervised context.European CommissionAgencia Estatal de InvestigaciónJunta de Comunidades de Castilla-La Manch

Audio feature engineering for occupancy and activity estimation in smart buildings

The occupancy and activity estimation are fields that have been severally researched in the past few years. However, the different techniques used include a mixture of atmospheric features such as humidity and temperature, many devices such as cameras and audio sensors, or they are limited to speech recognition. In this work is proposed that the occupancy and activity can be estimated only from the audio information using an automatic approach of audio feature engineering to extract, analyze and select descriptors/variables. This scheme of extraction of audio descriptors is used to determine the occupation and activity in specific smart environments, such that our approach can differentiate between academic, administrative or commercial environments. Our approach from the audio feature engineering is compared to previous similar works on occupancy estimation and/or activity estimation in smart buildings (most of them including other features, such as atmospherics and visuals). In general, the results obtained are very encouraging compared to previous studies.European Commissio

Verification of the emergence in an architecture for multi-robot systems (AMEB)

This article analyzes the emerging behavior of a multi-robot system managed by an architecture structured in three layers: the first provides local support to the robot, manages its processes of action, perception and communication, as well as its behavioral aspect, which considers the reactive, cognitive and social aspects of the robot. In addition, it introduces an affective component that influences its behavior and the way it relates to the environment and to the other individuals in the system, based on an emotional model that takes into account fourArticle history:Received 12 September 2018Accepted 08 November 2018A Gil, pertenece al Laboratorio de Prototipos en la Universidad Nacional Experimental del Táchira y a Tepuy R+D Group. Artificial Intelligence Software Development. Mérida, Venezuela (email: [email protected])basic emotions. The second provides support to the collective processes of the system, based on the concept of emerging coordination. The latter is responsible for knowledge management and learning processes, both individually and collectively, in the system. In this article the metrics are defined to verify the emergency in the system, by means of the use of a method of verification of emergent behaviors based on Fuzzy Cognitive Maps

Emergent coordination in multi-robot systems

En la naturaleza se encuentran sociedades de seres vivos que coordinan sus acciones de forma no centralizada. Por ejemplo, en las colonias de hormigas ocurren procesos emergentes, que combinan las acciones de los individuos en función de un objetivo común. En este trabajo, se describe una capa de gestión que facilita los procesos de coordinación emergente en los sistemas multirobots. Esta capa en particular permite la aparación de la emergencia y la autoorganización en el sistema. En conjunto con las capas de gestión individual y de gestión del conocimiento, manejan los procesos necesarios para el funcionamiento del sistema multirobot.In nature there are societies of living beings that coordinate their actions in a non-centralized way. For example, emergent processes that combine the actions of individuals in the achievement of a common goal occur in ant colonies. This paper describes a management layer that facilitates emerging coordination processes in multi-robot systems, which together with other two layers (one of individual management and another of knowledge management), manage the processes necessary for the operation of the multi-robot system. In particular, this layer allows the appearance of emergency and self-organization in the system. &nbsp