Mode of access: Internet via World Wide Web. Available at http://hdl.handle.net/1947/10020. / "October 2009" Includes bibliographic references.

Thesis (M.Phil.) - University of St Andrews, April 2009.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M. Sc.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (p. 143-145). Also available via the World Wide Web.

Thesis (M.S.)--University of North Carolina at Greensboro, 2007. / Title from PDF title page screen. Advisor: Darrell Spells; submitted to the Dept. of Chemistry. Includes bibliographical references (p. 46-47).

The aim of this work was to implement and compare several activity recognition algorithms which could be used in a smart home environment and would be able to determine the current activity of an observed subject (virtual agent) in the smart home using only data gathered by elementary observations of the environment. Such algorithms are useful in several areas, for example to improve behavior of various virtual agents, making them more aware of actions of the other agents. The algorithms used in this thesis are based on Dynamic Bayesian Networks and have ability to determine whether the observed activity has been completed or just interrupted. An easily extensible 3D interactive simulator of a smart home environment was created to meet the needs of activity recognition and used to gather data for the learning and testing phases of the algorithms. The test subjects were human-controlled virtual agents.

M.Sc. / A Smart Card looks like a normal plastic card that we use every day, but its capabilities and advantages are huge. Inside the card there is a small microprocessor capable of doing operations on data. With memory available on the card, data can be stored in a safe and secure location. This card can be used for various applications and is a big improvement on all of its predecessors. These applications can be anything from SIM cards in a cell phone to credit cards and cards used for access control. The Smart Card offers us better security and offline identification because of its own embedded microprocessor. The combination of Smart Cards with biometrics for security reasons will be a logical step and the ideal way to identify the person as the true owner of the card. This dissertation will investigate the use of contact Smart Cards in the University environment, more specifically as a University student card. The Smart Card will be combined with a fingerprint to enforce better security. The main purpose is to use the Smart Card and the biometric property for access control at various places on campus.

Electrochromic smart windows offer a viable route to reducing the consumption of buildings energy, which represents about 30% of the worldwide energy consumption. Smart windows are far more compelling than current static windows in that they can dynamically modulate the solar spectrum depending on climate and lighting conditions or simply to meet personal preferences. The latest generation of smart windows relies on nominally transparent metal oxide nanocrystal materials whose chromism can be electrochemically controlled using the plasmonic effect. Plasmonic electrochromic materials selectively control the near infrared (NIR) region of the solar spectrum, responsible for solar heat, without affecting the visible transparency. This is in contrast to conventional electrochromic materials which block both the visible and NIR and thus enables electrochromic devices to reduce the energy consumption of a building or a greenhouse in warm climate regions due to enhancements of both visible lighting and heat blocking. Despite this edge, this technology can benefit from important developments, including low-cost solution-based manufacturing on flexible substrates while maintaining durability and coloration efficiency, demonstration of independent control in the NIR and visible spectra, and demonstration of self-powering capabilities. This thesis is focused on developing low-temperature and all-solution processed plasmonic electrochromic devices and dual-band electrochromic devices. We demonstrate new device fabrication approaches in terms of materials and processes which enhance electrochromic performance all the while maintaining low processing temperatures. Scalable fabrication methods are used to highlight compatibility with high throughput, continuous roll-to-roll fabrication on flexible substrates. In addition, a dualband plasmonic electrochromic device was developed by combining the plasmonic layer with a conventional electrochromic ion storage layer. This enables independent control of the transmittance of NIR and visible spectra and is done without time- and energyintensive synthesis and processing methods. We have fabricated self-powered smart windows by integrating the plasmonic and dual-band devices with organic photovoltaic mini-modules and introduced static color bias with the help of photonic crystals to explore a few possibilities of multi-platform building integration.

Les bâtiments sont de plus en plus équipés avec des réseaux d’automatisation dédiés, visant à réduire la consommation d’énergie ainsi que d’optimiser le confort. D’un autre côté, nous observons l’arrivée de capteurs et actionneurs liés à l’Internet des objets, pouvant naturellement se connecter à des réseaux IP. Dû à des contraintes d’obsolescence ou imposées par les propriétés physiques des bâtiments, il n’est pas rare que différentes technologies doivent cohabiter. Celles-ci fonctionnant avec des modèles et protocoles différents rend le développement de systèmes d’automatisation globaux compliqué. Les modèles classiques de systèmes distribués ne sont pas adaptés aux problématiques des réseaux de capteurs. Le paradigme du Web des objets est basé sur des ressources et vise quand à lui d’uniformiser la couche applicative entre différents objets à l’aide des technologies du Web, essentiellement HTTP et REST. Dans cette thèse, nous nous basons sur le Web des objets afin de créer un framework dédié au bâtiments intelligents, permettant aux développeurs de concevoir des applications composites sans connaissances des différentes technologies sous-jacentes. Grâce aux technologies Web, nous pouvons offrir des services homogènes tout en profitant des ressources disponibles à l’intérieur du réseau (capteurs et actionneurs), formant un nuage auto-géré. Dans le but de doter les bâtiments d’une plus grande intelligence, l’apprentissage automatique, souvent réservé aux experts, est rendu accessible à travers des interfaces Web cachant la complexité des processus. / Buildings are increasingly equipped with dedicated automation networks, aiming to reduce the energy consumption and to optimize the comfort. On the other hand, we see the arrival of sensors and actuators related to the Internet of Things, which can naturally connect to IP networks. Due to constraints imposed by the obsolescence or physical properties of buildings, it is not uncommon that different technologies have to coexist. These networks operate with different models and protocols, making the development of global automation systems difficult. Traditional models of distributed systems are not adapted to the context of sensor networks. The paradigm of the Web of Things is resource-based and strives to standardize the application layer of different objects using Web technologies, primarily HTTP and REST. In this thesis, we use the Web of Things to create a framework dedicated to smart buildings, allowing developers to develop composite applications without knowledge of the underlying technologies. By relying on Web technologies, we can provide seamless service while reusing the available resources within the network (sensors and actuators), forming a self-managed cloud. In order to equip the buildings with a higher-level intelligence, machine learning, often reserved for experts, is made accessible through Web interfaces hiding the complexity of the process.

Indiana University-Purdue University Indianapolis (IUPUI) / Energy management has become a major concern in the past two decades with the increasing energy prices, overutilization of natural resources and increased carbon emissions. According to the department of Energy the industrial sector solely consumes 22.4% of the energy produced in the country [1]. This calls for an urgent need for the industries to design and implement energy efficient practices by analyzing the energy consumption, electricity data and making use of energy efficient equipment. Although, utility companies are providing incentives to consumer participating in Demand Response programs, there isn’t an active implementation of energy management principles from the consumer’s side. Technological advancements in controls, automation, optimization and big data can be harnessed to achieve this which in other words is referred to as “Smart Manufacturing”. In this research energy management techniques have been designed for two SEU (Significant Energy Use) equipment HVAC systems, Compressors and load shifting in manufacturing environments using control and optimization. The addressed energy management techniques associated with each of the SEUs are very generic in nature which make them applicable for most of the industries. Firstly, the loads or the energy consuming equipment has been categorized into flexible and non-flexible loads based on their priority level and flexibility in running schedule. For the flexible loads, an optimal load scheduler has been modelled using Mixed Integer Linear Programming (MILP) method that find carries out load shifting by using the predicted demand of the rest of the plant and scheduling the loads during the low demand periods. The cases of interruptible loads and non-interruptible have been solved to demonstrate load shifting. This essentially resulted in lowering the peak demand and hence cost savings for both “Time-of-Use” and Demand based price schemes. The compressor load sharing problem was next considered for optimal distribution of loads among VFD equipped compressors running in parallel to meet the demand. The model is based on MILP problem and case studies was carried out for heavy duty (>10HP) and light duty compressors (<=10HP). Using the compressor scheduler, there was about 16% energy and cost saving for the light duty compressors and 14.6% for the heavy duty compressors HVAC systems being one of the major energy consumer in manufacturing industries was modelled using the generic lumped parameter method. An Electroplating facility named Electro-Spec was modelled in Simulink and was validated using the real data that was collected from the facility. The Mean Absolute Error (MAE) was about 0.39 for the model which is suitable for implementing controllers for the purpose of energy management. MATLAB and Simulink were used to design and implement the state-of-the-art Model Predictive Control for the purpose of energy efficient control. The MPC was chosen due to its ability to easily handle Multi Input Multi Output Systems, system constraints and its optimal nature. The MPC resulted in a temperature response with a rise time of 10 minutes and a steady state error of less than 0.001. Also from the input response, it was observed that the MPC provided just enough input for the temperature to stay at the set point and as a result led to about 27.6% energy and cost savings. Thus this research has a potential of energy and cost savings and can be readily applied to most of the manufacturing industries that use HVAC, Compressors and machines as their primary energy consumer.