Enrique Sierra

Fuzzy Control For Improving Energy Management Within Indoor Building Environments

Research on energy efficiency in buildings has proved that the design and even the sophisticated facilities such as building energy management systems (BEMS), aiming to improve the indoor environmental conditions while minimizing the energy needs, are not sufficient enough due to users interference. Users are a dynamic part of the building, therefore they should be taken into account in the control strategy. Latest trends in designing intelligent building energy management systems (IBEMS) integrate a man machine interface that could store the users preferences and adapt the control strategy accordingly. The objective of the present paper is to present the advantages of the fuzzy control techniques together with a man machine interface based on a smart card terminal in satisfying the user preferences. A fuzzy controller is developed and the minimization of energy consumption is achieved by the use of a suitable cost function for the whole system. The overall control system including the cost function has been modeled and tested by using the software tool MATLAB/SIMULINK.

Pedagogical Protocols Selection Automatic Assistance

The preliminary results presented in this paper corresponds to a research project oriented to the search of the relationship between the predilection of students concerning learning style and the pedagogical protocols used by the human tutors (professors during the first courses of the Computer Engineering undergraduate Program) by using intelligent systems tools.

Optimizing Building's Environments Performance Using Intelligent Systems

This article describes an intelligent system architecture that based on neural networks, expert systems and negotiating agents technologies is designed to optimize intelligent buildings performance. By understanding a building as a dynamic entity capable of adapting itself not only to changing environmental conditions but also to occupants living habits, high standards of comfort and user satisfaction can be achieved. Results are promising and encourage further research in the field of artificial intelligence applications in building automation systems.

A Multi-agent Intelligent Tutoring System for Learning Computer Programming

In this paper, we consider a multi-agent intelligent tutoring system for the learning of computer programming. It provides a multiple domain learning environment for language learners. The aim of the system is to teach the target domain by using a supporting domain(s) to reinforce the learning of it. The system is strongly built upon a cognitive theory that affirms there are successful knowledge transfers in the learning of knowledge-rich domains like computer programming. To implement it, we chose a multi-agent system because of the features of agents, which provide flexibility for future expansion.

Intelligent Systems Applied to Optimize Building’s Environments Performance

By understanding a building as a dynamic entity capable of adapting itself not only to changing environmental conditions but also to occupant’s living habits, high standards of comfort and user satisfaction can be achieved. An intelligent system architecture integrating neural networks, expert systems and negotiating agents technologies is designed to optimize intelligent building’s performance. Results are promising and encourage further research in the field of AI applications in building automation systems.