Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Integrated management of urban wastewater systems: a model-based approach

The main objective pursued in this thesis targets the development and systematization of a methodology that allows addressing management problems in the dynamic operation of Urban Wastewater Systems. The proposed methodology will suggest operational strategies that can improve the overall performance of the system under certain problematic situations through a model-based approach. The proposed methodology has three main steps: The first step includes the characterization and modeling of the case-study, the definition of scenarios, the evaluation criteria and the operational settings that can be manipulated to improve the system’s performance. In the second step, Monte Carlo simulations are launched to evaluate how the system performs for a wide range of operational settings combinations, and a global sensitivity analysis is conducted to rank the most influential operational settings. Finally, the third step consists on a screening methodology applying a multi-criteria analysis to select the best combinations of operational settings.

Knowledge management systems and intellectual capital measurement in portuguese organizations: a case study

This paper presents the results of an exploratory study on knowledge management in Portuguese organizations. The study was based on a survey sent to one hundred of the main Portuguese organizations, in order to know their current practices relating knowledge management systems (KMS) usage and intellectual capital (IC) measurement. With this study, we attempted to understand what are the main tools used to support KM processes and activities in the organizations, and what metrics are pointed by organizations to measure their knowledge assets.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.

Knowledge-based models for adaptive traffic management systems

This paper describes a general approach for real time traffic management support using knowledge based models. Recognizing that human intervention is usually required to apply the current automatic traffic control systems, it is argued that there is a need for an additional intelligent layer to help operators to understand traffic problems and to make the best choice of strategic control actions that modify the assumption framework of the existing systems.

Contribution towards intelligent service management in wearable and ubiquitous devices

Hoy en día asistimos a un creciente interés por parte de la sociedad hacia el cuidado de la salud. Esta afirmación viene apoyada por dos realidades. Por una parte, el aumento de las prácticas saludables (actividad deportiva, cuidado de la alimentación, etc.). De igual manera, el auge de los dispositivos inteligentes (relojes, móviles o pulseras) capaces de medir distintos parámetros físicos como el pulso cardíaco, el ritmo respiratorio, la distancia recorrida, las calorías consumidas, etc. Combinando ambos factores (interés por el estado de salud y disponibilidad comercial de dispositivos inteligentes) están surgiendo multitud de aplicaciones capaces no solo de controlar el estado actual de salud, también de recomendar al usuario cambios de hábitos que lleven hacia una mejora en su condición física. En este contexto, los llamados dispositivos llevables (weareables) unidos al paradigma de Internet de las cosas (IoT, del inglés Internet of Things) permiten la aparición de nuevos nichos de mercado para aplicaciones que no solo se centran en la mejora de la condición física, ya que van más allá proponiendo soluciones para el cuidado de pacientes enfermos, la vigilancia de niños o ancianos, la defensa y la seguridad, la monitorización de agentes de riesgo (como bomberos o policías) y un largo etcétera de aplicaciones por llegar. El paradigma de IoT se puede desarrollar basándose en las existentes redes de sensores inalámbricos (WSN, del inglés Wireless Sensor Network). La conexión de los ya mencionados dispositivos llevables a estas redes puede facilitar la transición de nuevos usuarios hacia aplicaciones IoT. Pero uno de los problemas intrínsecos a estas redes es su heterogeneidad. En efecto, existen multitud de sistemas operativos, protocolos de comunicación, plataformas de desarrollo, soluciones propietarias, etc. El principal objetivo de esta tesis es realizar aportaciones significativas para solucionar no solo el problema de la heterogeneidad, sino también de dotar de mecanismos de seguridad suficientes para salvaguardad la integridad de los datos intercambiados en este tipo de aplicaciones. Algo de suma importancia ya que los datos médicos y biométricos de los usuarios están protegidos por leyes nacionales y comunitarias. Para lograr dichos objetivos, se comenzó con la realización de un completo estudio del estado del arte en tecnologías relacionadas con el marco de investigación (plataformas y estándares para WSNs e IoT, plataformas de implementación distribuidas, dispositivos llevables y sistemas operativos y lenguajes de programación). Este estudio sirvió para tomar decisiones de diseño fundamentadas en las tres contribuciones principales de esta tesis: un bus de servicios para dispositivos llevables (WDSB, Wearable Device Service Bus) basado en tecnologías ya existentes tales como ESB, WWBAN, WSN e IoT); un protocolo de comunicaciones inter-dominio para dispositivos llevables (WIDP, Wearable Inter-Domain communication Protocol) que integra en una misma solución protocolos capaces de ser implementados en dispositivos de bajas capacidades (como lo son los dispositivos llevables y los que forman parte de WSNs); y finalmente, la tercera contribución relevante es una propuesta de seguridad para WSN basada en la aplicación de dominios de confianza. Aunque las contribuciones aquí recogidas son de aplicación genérica, para su validación se utilizó un escenario concreto de aplicación: una solución para control de parámetros físicos en entornos deportivos, desarrollada dentro del proyecto europeo de investigación “LifeWear”. En este escenario se desplegaron todos los elementos necesarios para validar las contribuciones principales de esta tesis y, además, se realizó una aplicación para dispositivos móviles por parte de uno de los socios del proyecto (lo que contribuyó con una validación externa de la solución). En este escenario se usaron dispositivos llevables tales como un reloj inteligente, un teléfono móvil con sistema operativo Android y un medidor del ritmo cardíaco inalámbrico capaz de obtener distintos parámetros fisiológicos del deportista. Sobre este escenario se realizaron diversas pruebas de validación mediante las cuales se obtuvieron resultados satisfactorios. ABSTRACT Nowadays, society is shifting towards a growing interest and concern on health care. This phenomenon can be acknowledged by two facts: first, the increasing number of people practising some kind of healthy activity (sports, balanced diet, etc.). Secondly, the growing number of commercial wearable smart devices (smartwatches or bands) able to measure physiological parameters such as heart rate, breathing rate, distance or consumed calories. A large number of applications combining both facts are appearing. These applications are not only able to monitor the health status of the user, but also to provide recommendations about routines in order to improve the mentioned health status. In this context, wearable devices merged with the Internet of Things (IoT) paradigm enable the proliferation of new market segments for these health wearablebased applications. Furthermore, these applications can provide solutions for the elderly or baby care, in-hospital or in-home patient monitoring, security and defence fields or an unforeseen number of future applications. The introduced IoT paradigm can be developed with the usage of existing Wireless Sensor Networks (WSNs) by connecting the novel wearable devices to them. In this way, the migration of new users and actors to the IoT environment will be eased. However, a major issue appears in this environment: heterogeneity. In fact, there is a large number of operating systems, hardware platforms, communication and application protocols or programming languages, each of them with unique features. The main objective of this thesis is defining and implementing a solution for the intelligent service management in wearable and ubiquitous devices so as to solve the heterogeneity issues that are presented when dealing with interoperability and interconnectivity of devices and software of different nature. Additionally, a security schema based on trust domains is proposed as a solution to the privacy problems arising when private data (e.g., biomedical parameters or user identification) is broadcasted in a wireless network. The proposal has been made after a comprehensive state-of-the-art analysis, and includes the design of a Wearable Device Service Bus (WDSB) including the technologies collected in the requirement analysis (ESB, WWBAN, WSN and IoT). Applications are able to access the WSN services regardless of the platform and operating system where they are running. Besides, this proposal also includes the design of a Wearable Inter-Domain communication Protocols set (WIDP) which integrates lightweight protocols suitable to be used in low-capacities devices (REST, JSON, AMQP, CoAP, etc...). Furthermore, a security solution for service management based on a trustworthy domains model to deploy security services in WSNs has been designed. Although the proposal is a generic framework for applications based on services provided by wearable devices, an application scenario for testing purposes has been included. In this validation scenario it has been presented an autonomous physical condition performance system, based on a WSN, bringing the possibility to include several elements in an IoT scenario: a smartwatch, a physiological monitoring device and a smartphone. In summary, the general objective of this thesis is solving the heterogeneity and security challenges arising when developing applications for WSNs and wearable devices. As it has been presented in the thesis, the solution proposed has been successfully validated in a real scenario and the obtained results were satisfactory.

National Program Plan for Intelligent Vehicle-Highway Systems (IVHS).

Mode of access: Internet.

Smart highways: challenges facing DOT's intelligent vehicle highway systems program.

Mode of access: Internet.

Developing freeway and incident management systems using the national ITS architecture.

Performing organizations: Mitretek Systems and PB Farradyne, Inc.