Entwicklung von energieautarken, intelligenten Ladehilfsmitteln am Beispiel des inBin

Das autonome, intelligente Ladehilfsmittel verkörpert die Idee des Internets der Dinge in der Intralogistik in Reinform. Am Beispiel des inBin wird das Energy-Harvesting in der Intralogistik betrachtet und gezeigt, dass ein Behälter mit komplexen logistischen Funktionen unter realistischer Umgebungsbeleuchtung durch Solarzellen betrieben werden kann.

Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

An intelligent portable sensor system in diagnosing stress

Nowadays the stress is a frequent problem in the society. The level of stress could be important in order to recognise health problems later. Electrocardiogram technics allows to supervise the heart condition and the detection of anomalies about the patient. Sometimes the data collection systems by sensors placed on the patient restrict his mobility. Therefore the elimination of wires is a good solution for this trouble. Then the Bluetooth protocol is chosen as way for transmitting and receive data between stations. There are three ECG sensors placed on the right hand, the left hand and the right leg. It is possible to measure the heart signal with this technique. Besides there is an extra sensor in order to measure the temperature of the patient. Depending of the value of these parameters is possible to recognise stress levels. All sensors are connected to a special box with a microcontroller which treat every signal. This module has a Bluetooth part that transmitts wireless the new digital signal to the receiver. This one will be a dongle connected to the computer by Serial Port. A program in the computer has been implemented in order to receive the Bluetooth Data sent from the box and saving the data in a file for subsequent activities. El objetivo principal de este proyecto es el estudio de parámetros como la temperatura corporal y las señales de electrocardiograma para el diagnóstico del estrés. Existen varios estudios que relacionan estos parámetros y sus niveles con posibles casos de estrés y ansiedad. Para este fin usamos unos sensores colocados en el brazo derecho, brazo izquierdo y pierna izquierda. Esto forma el Eindhoven Triangle, que es conocido por dar una señal de electrocardiograma. A su vez también tendremos un sensor de temperatura colocado en un dedo de la mano para medir los grados a los que está el cuerpo en ese momento y así poder detectar ciertas anomalías. Estos sensores están conectados a un modulo que trata las señales analógicas recogidas, las une, y digitaliza para que el modulo transmisor pueda enviar via Bluetooth los datos hacia un receptor colocado en un área cercana. En el módulo hay una electrónica que ayuda a resolver problemas importantes como ruido o interferencias. Este receptor está conectado a un ordenador en el cual he desarrollado una aplicación que implementa el protocolo HCI y cuya funcionalidad es recoger los datos recibidos. Este programa es capaz de crear y gestionar conexiones Bluetooth entre dispositivos. El programa está preparado para que si las conexiones se cortan, se traten en la medida de lo posible los datos recogidos. Los datos se interpretarán y guardarán en un fichero .bin para posteriores usos, como graficaciones y análisis de parámetros. El programa está enteramente hecho en lenguaje Java y tiene un mecanismo de eventos que se activa cada vez que hay datos en el receptor, los recoge y los procesa con el fin de darles un trato posteriormente. Se eligió el formato .bin para los ficheros debido a su pequeño tamaño, ya que aunque sean más laboriosos de usar es mucho más eficiente que un .txt, que en este caso podría ocupar varios megabytes.

PCFinfer : an intelligent product recommendation agent for electronic commerce

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

PCFinfer : an intelligent product recommendation agent for electronic commerce

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

The Brain as a Distributed Intelligent Processing System: An EEG Study

Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

Modeling of Distributed Control Systems in Intelligent Building based on Colored Petri Nets

Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

Sensor-driven agenda for intelligent home care of the elderly

The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.