This research investigates adoption and integration of a range of building environmental systems in healthcare facilities in India. Based on detailed case studies of eight selected healthcare facilities developed at different times in India, this research traces the evolution of hospital designs in a specific geographic context through the lens of adoption of building environmental systems over the internal shell and external skins of healthcare buildings in India. By documenting and analyzing changes in building designs over time, the research develops a comparative understanding of trends of adoption of environmental technologies and their impacts on building form and performance.

Before the recent advances in sensing, actuation, computing and communication technologies, the integration between the digital and the physical environment was limited. Humans linked those two worlds by collecting data about the physical environment before feeding it into the digital environment, and by changing the state of the physical environment based on the state of the digital environment. The incorporation of computing, communication, sensing, and actuation technologies into everyday physical objects has empowered the vision of the Internet of Things (IoT). Things can autonomously collect data about the physical environment, exchange information with other things, and take actions on behalf of humans. Application domains that can benefit from IoT include smart buildings, smart cities, smart water, smart agriculture, smart animal farming, smart metering, security and emergencies, retail, logistics, industrial control, and health care. For decades, building automation, intelligent buildings, and more recently smart buildings have received a considerable attention in both academia and industry. We use the term smart built environments (SBE) to describe smart, intelligent, physical, built, architectural spaces ranging from a single room to a whole city. Legacy SBEs were often closed systems operating their own standards and custom protocols. SBEs evolved to Internet-connected systems leveraging the Internet technologies and services (e.g., cloud services) to unleash new capabilities. IoT-enabled SBEs, as one of the various applications of the IoT, can change the way we experience our homes and workplaces significantly and make interacting with technology almost inevitable. This can provide several benefits to modern society and help to make our life easier. Meanwhile, security, privacy, and safety concerns should be addressed appropriately. Unlike traditional computing devices, things usually have no or limited input/output (I/O) capabilities. Leveraging the ubiquity of general-purpose computing devices (e.g., smartphones), thing vendors usually provide interfaces for their products in the form of mobile apps or web-based portals. Interacting with different things using different mobile apps or web-based portals does not scale well. Requiring the user to switch between tens or hundreds of mobile apps and web-based portals to interact with different things in different smart spaces may not be feasible. Moreover, it can be tricky for non-domestic users (e.g., visitors) of a given SBE to figure out, without guidance, what mobile apps or web-based portals they need to use to interact with the surrounding. While there has been a considerable research effort to address a variety of challenges associated with the thing-to-thing interaction, human-to-thing interaction related research is limited. Many of the proposed approaches and industry-adopted techniques rely on more traditional, well understood and widely used Human-Computer Interaction (HCI) methods and techniques to support interaction between humans and things. Such techniques have mostly originated in a world of desktop computers that have a screen, mouse, and keyboard. However, SBEs introduce a radically different interaction context where there are no centralized, easily identifiable input and output devices. A desktop computer of the past is being replaced with the whole SBE. Depending on the task at hand and personal preferences, a user may prefer to use one interaction modality over another. For instance, turning lights on/off using an app may be more cumbersome or time-consuming compared to using a simple physical switch. This research focuses on leveraging the recent advances in IoT and related technologies to support user interactions with SBEs. We explore how to support flexible and adaptive multimodal interfaces and interactions while providing a consistent user experience in an SBE based on the current context and the available user interface and interaction capabilities. / PHD / The recent advances in sensing, actuation, computing, and communication technologies have brought several rewards to modern society. The incorporation of those technologies into everyday physical objects (or things) has empowered the vision of the Internet of Things (IoT). Things can autonomously collect data about the physical environment, exchange information with other things, and take actions on behalf of humans. Several application domains can benefit from the IoT such as smart buildings, smart cities, security and emergencies, retail, logistics, industrial control, and health care. For decades, building automation, intelligent buildings, and more recently smart buildings have received considerable attention in both academia and industry. We use the term smart built environments (SBE) to describe smart, intelligent, physical, built, architectural spaces ranging from a single room to a whole city. SBEs, as one of the various applications of the IoT, can change the way we experience our homes and workplaces significantly and make interacting with technology almost inevitable. While there has been a considerable research effort to address a variety of challenges associated with the thing-to-thing interaction, human-to-thing interaction related research is limited. Many of the proposed approaches and industry-adopted techniques to support human-to-thing interaction rely on traditional methods. However, SBEs introduce a radically different interaction context. Therefore, adapting the current interaction techniques and/or adopting new ones is crucial for the success and wide adoption of SBEs. This research focuses on leveraging the recent advances in the IoT and related technologies to support user interactions with SBEs. We explore how to support a flexible, adaptive, and multimodal interaction experience between users and SBEs using a variety of user interfaces and proposed interaction techniques.

The phenomenon called “The Internet of Things” makes it possible for organizations in the public and private-sector to handle resources better, enhance their performances, and to establish new ways of developing business models. Connected devices can contribute valuable knowledge through real-time updates and help with monitoring and/or to analyze how people and resources behave through the value-chain. This paper aims to investigate how current Smart Environments in public settings are functioning with the data collection in mind, and the integrity behind it. We also shed some light on how prepared they are for the new GDPR Law. Our goal is to come up with knowledge about how organizations and companies are working with integrity and data gathering, when they are transforming their public environment into a Smart Public Environment.

The smart environments and the connected human seems to be the future of wireless communications. The development of new frequency bands in the millimeter range will allow us to create high data rate communications which will led to the Wireless Body Environment Networks. In this kind of scenarios, it is expected that the user and the environment will interact. In order to develop such new applications, it is necessary to first study the propagation mechanisms and then, the communication channel underlying body centric environments. This thesis treats of channel models for 60 GHz Body Area Networks and more particularly of three kinds of scenarios: (i) the communication between an external base station and a worn node (off-body); (ii) the communication between two worn nodes (on-body); the communication between an external base station and a hand-held device (near-body). An indoor off-body channel model is numerically proposed and implemented. The model is based on the IEEE 802.11ad indoor standard channel at 60 GHz and a fast computation solution of the scattering of a plane wave by a circular cylinder. The model is developed for two orthogonal polarizations and the communications performances are studied. The on-body propagation is studied for two different configurations: line-of-sight and non-line-of-sight communications on the body. These scenarios led to different solutions for the channel knowing as, respectively, Norton’s equations and creeping formulations. These solutions are obtained using simplified geometries which has been experimentally validated. Further, in order to improve the propagation on the human body, a technique using metallic plates has been proposed. This technique has been theoretically studied using Milligton’s equations and experimentally assessed on a flat phantom with the properties of the human skin. The proposed method allows to save up to 20 dB. Finally, the near-body communication scenario has been introduced and studied. The near-body region is extended from 5 to 30 cm away of the user body which corresponds to the arm’s reach and models a handheld device. A numerical algorithm has been proposed to model indoor near-body environments. Also, a special has been given to statistical body shadowing. It has been shown that the fading follows a Two-Wave Diffuse Power distribution. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

The efficient designs of Wireless Sensor Network protocols and intelligent Machine Learning algorithms, together have led to the advancements of various systems and applications for Smart Environments. By definition, Smart Environments are the typical physical worlds used in human daily life, those are seamlessly embedded with smart tiny devices equipped with sensors, actuators and computational elements. Since human user is a key component in Smart Environments, human motion activity patterns have key importance in building sensor network systems and applications for Smart Environments. Motivated by this, in this thesis my work is focused on human motion activity-aware sensor networks for Smart Environments. The main contributions of this thesis are in two important aspects: (i) Designing event activity context-aware sensor networks for efficient performance optimization as well as resource usage; and (ii) Using binary motion sensing sensor networks' collective data for device-free real-time tracking of multiple users. Firstly, I describe the design of our proposed event activity context-aware sensor network protocols and system design for Smart Environments. The main motivation behind this work is as follows. A sensor network, unlike a traditional communication network, provides high degree of visibility into the environmental physical processes. Therefore its operation is driven by the activities in the environment. In long-term operations, these activities usually show certain patterns which can be learned and effectively utilized to optimize network design. In this thesis I have designed several novel protocols: (i) ActSee for activity-aware radio duty-cycling, (ii) EAR for activity-aware and energy balanced routing, and (iii) ActiSen complete working system with protocol suites for activity-aware sensing/ duty-cycling/ routing. Secondly, I have proposed and designed FindingHuMo (Finding Human Motion), a Machine Learning based real-time user tracking algorithm for Smart Environments using Sensor Networks. This work has been motivated by increasing adoption of sensor network enabled Ubiquitous Computing in key Smart Environment applications, like Smart Healthcare. Our proposed FindingHuMo protocol and system can perform device-free tracking of multiple (unknown and variable number of) users in the hallway environments, just from non-invasive and anonymous binary motion sensor data.

La Maison Intelligente est une résidence équipée de technologie informatique qui assiste ses habitant dans les situations diverses de la vie domestique en essayant de gérer de manière optimale leur confort et leur sécurité par action sur la maison. La détection des situations anormales est un des points essentiels d'un système de surveillance à domicile. Ces situations peuvent être détectées en analysant les primitives générées par les étages de traitement audio et par les capteurs de l'appartement. Par exemple, la détection de cris et de bruits sourds (chute d'un objet lourd) dans un intervalle de temps réduit permet d'inférer l'occurrence d'une chute. Le but des travaux de cette thèse est la réalisation d'un contrôleur intelligent relié à tous les périphériques de la maison capable de réagir aux demandes de l'habitant (par commande vocale) et de reconnaître des situations à risque ou détresse. Pour accomplir cet objectif, il est nécessaire de représenter formellement et raisonner sur des informations, le plus souvent temporelles, à des niveaux d'abstraction différents. Le principale défi est le traitement de l'incertitude, l'imprécision, et incomplétude, qui caractérisent les informations dans ce domaine d'application. Par ailleurs, les décisions prises par le contrôleur doivent tenir compte du contexte dans lequel une ordre est donné, ce qui nous place dans l'informatique sensible au contexte. Le contexte est composé des informations de haut niveau tels que la localisation, l'activité en cours de réalisation, la période de la journée. Les recherches présentées dans ce manuscrit peuvent être divisés principalement en trois axes: la réalisation des méthodes d'inférence pour acquérir les informations du contexte(notamment, la localisation de l'habitant y l'activité en cours) à partir des informations incertains, la représentation des connaissances sur l'environnement et les situations à risque, et finalement la prise de décision à partir des informations contextuelles. La dernière partie du manuscrit expose les résultats de la validation des méthodes proposées par des évaluations amenées à la plateforme expérimental Domus. / A smart home is a residence featuring ambient intelligence technologies in order to help its dwellers in different situations of common life by trying to manage their comfort and security through the execution of actions over the effectors of the house. Detection of abnormal situations is paramount in the development of surveillance systems. These situations can be detected by the analysis of the traces resulting from audio processing and the data provided by the network of sensors installed in the smart home. For instance, detection of cries along with thuds(fall of a heavy object) in a short time interval can help to infer that the resident has fallen. The goal of the research presented in this thesis is the implementation of an intelligence controller connected with the devices in the house that is able to react to user's commands(through vocal interfaces) and recognize dangerous situations. In order to fulfill this goal, it is necessary to create formal representation and to develop reasoning mechanism over informations that are often temporal and having different levels of abstraction. The main challenge is the processing the uncertainty, imprecision, and incompleteness that characterise this domain of application. Moreover, the decisions taken by the intelligent controller must consider the context in which a user command is given, so this work is made in the area of Context Aware Computing. Context includes high level information such as the location of the dweller, the activity she is making, and the time of the day. The research works presented in this thesis can be divided mainly in three parts: the implementation of inference methods to obtain context information(namely, location and activity) from uncertain information, knowledge representation about the environment and dangerous situations, and finally the development of decision making models that use the inferred context information. The last part of this thesis shows the results from the validation of the proposed methods through experiments performed in an experimental platform, the Domus apartment.

Technology is becoming pervasive and the current interfaces are not adequate for the interaction with the smart environments of the ubiquitous computing era. Recently, researchers have started to address this issue introducing the concept of natural user interface, which is mainly based on gestural interactions. Many issues are still open in this emerging domain and, in particular, there is a lack of common guidelines for coherent implementation of gestural interfaces. This research investigates gestural interactions between humans and smart environments. It proposes a novel framework for the high-level organization of the context information. The framework is conceived to provide the support for a novel approach using functional gestures to reduce the gesture ambiguity and the number of gestures in taxonomies and improve the usability. In order to validate this framework, a proof-of-concept has been developed. A prototype has been developed by implementing a novel method for the view-invariant recognition of deictic and dynamic gestures. Tests have been conducted to assess the gesture recognition accuracy and the usability of the interfaces developed following the proposed framework. The results show that the method provides optimal gesture recognition from very different view-points whilst the usability tests have yielded high scores. Further investigation on the context information has been performed tackling the problem of user status. It is intended as human activity and a technique based on an innovative application of electromyography is proposed. The tests show that the proposed technique has achieved good activity recognition accuracy. The context is treated also as system status. In ubiquitous computing, the system can adopt different paradigms: wearable, environmental and pervasive. A novel paradigm, called synergistic paradigm, is presented combining the advantages of the wearable and environmental paradigms. Moreover, it augments the interaction possibilities of the user and ensures better gesture recognition accuracy than with the other paradigms.

The development of system architectures and applications for smart homes and ambient assisted living has been the main activity of a number of academic and industrial research projects around the world. Existing system architectures for smart environments usually employ different architectural styles in a multi-layer logical architecture to support the integration and interoperation of heterogeneous hardware and software technologies, which are subsequently used to provide two major functionalities: monitoring and assistance. It is also usual among existing architectures that the database management system is the most common but the least exploited architectural component, existing in the periphery of the system and devoted exclusively for data storage and retrieval. However, database technology has advanced and matured considerably over the years, and, as a result, current database management systems can be and do more. This thesis considers the hypothesis of several features of modern database management systems being employed to address functional (e.g. well-being and security monitoring, automated control, data processing) and non-functional (e.g. interoperability, extensibility, data security and privacy) requirements of smart environments, i.e. the database management system serves as a platform for smart environments. The scope of this thesis is therefore to investigate the possibility of using different features supported by database management systems to create a database-centric system architecture for the development of smart home environments and ambient assisted living. The thesis also investigates the development of applications for health monitoring and assistance: 1) a serious game for fall prevention that assists people in practicing Tai Chi at home, and 2) a non-intrusive home-based method for sleep assessment. These features are explored in this thesis to address general functional aspects of smart environments, such as monitoring, processing, coordination and control of various types of events in a given environment. Extensibility and security features and cross-platform capabilities of database management systems are employed to accommodate non-functional, but still technical, properties of smart environments, including interoperability, extensibility, portability, scalability, security and privacy. Heterogeneous technologies are integrated into the system using programming language and platform independent software resource adapters. Interoperation among integrated technologies is mediated in an active database. The feasibility of the proposed database-centric system architecture was pragmatically investigated with the development of a "smart bedroom'' demonstrator and with the implementation of a number of short-term and long-term types of services to support active aging, aging in place and ambient assisted living. In the proposed architecture, active in-database processing maintains sensitive data within the database. This increases data security and independence from external software applications for data analysis. Changes in the system are managed during runtime, which improves flexibility and avoids system downtime. The proposed system architecture was evaluated taking into account different application scenarios and heterogeneous computing platforms. As a conclusion, modern database management systems support features that can be successfully employed in a database-centric system architecture to effectively and efficiently address functional and non-functional requirements of smart environments.

Neste trabalho apresentamos um modelo para ambientes inteligentes baseado em organizações de agentes, onde interações entre entidades são associadas a espaços físicos, pessoas carregam dispositivos e se movimentam entre diferentes espaços físicos e cada espaço físico contém definições de interações (comportamentos definidos por normas) próprias do seu contexto. São definidos três componentes deste modelo: (1) modelo conceitual, (2) linguagem de especificação e (3) ambiente de execução. A separação do modelo nestes três componentes traz como principais conseqüências: (1) a ativação de um ambiente inteligente é feita através de um mecanismo de alto nível, (2) a especificação de um ambiente inteligente é independente do domínio de aplicação e (3) as especificações podem ser executadas em mecanismos diferentes de execução. / We introduce a conceptual model for smart environments based on agent organizations where interactions between entities are associated with physical spaces, people (carrying mobile devices) move between different physical spaces and these physical spaces contain definitions of interactions (behaviors defined by norms) related to each context. This model defines three components: (1) conceptual model, (2) language specification, and (3) execution environment. The separation in these three components brings as main consequences: (1) activation of a smart environment is performed through a high-level mechanism, (2) specification of a smart environment is independent of the application domain, and (3) specifications can be performed on different mechanisms of execution.

Ambient intelligence refers to the vision of computationally augmented everyday environments that are sensitive, adaptive and responsive to humans and intelligently support their daily lives. Ambient ecologies are the infrastructures of ambient intelligence. To enable system developers to frame and manage the dynamic and complex interaction of humans with ambient ecologies consisting of a mixture of physical (real) and virtual (digital) objects, novel interaction paradigms are needed. Traditional interaction paradigms like the WIMP (windows, icon, menus, and pointing devices) paradigm for desktop computing operate in a closed world, unaware of the physical, social and cultural context. They restrict human perception and action to screen, mouse and keyboard with the assumption that human attention will be fully devoted to interaction with the computer. Emerging interaction paradigms for ambient intelligence are typically centered on specific devices, specific computing environments or specific human capabilities. Also, many of them are driven by technological advancements rather than viewing the human agent as their starting point. A principled, theoretical approach centered in the individual human agent, their situation and activities that are comprehensive and integrated while at the same time instrumental in the design of ambient ecologies has been lacking. This thesis introduces egocentric interaction as an approach towards the modeling of ambient ecologies with the distinguishing feature of taking the human agent’s body, situation and activities as center of reference, as opposed to the more common device-centric approaches in facilitating human-environment interaction. Egocentric interaction is encapsulated in a number of assumptions and principles such as situatedness, the proximity principle, the physical-virtual equity principle, perception and action instead of “input” and “output,” and activity-centeredness. A situative space model is proposed based on some of these principles. It is intended to capture what a specific human agent can perceive and not perceive, reach and not reach at any given moment in time. The situative space model is for the egocentric interaction paradigm what the virtual desktop is for the WIMP interaction paradigm: more or less everything of interest to a specific human agent is assumed and supposed to happen here. In addition, the conception and implementation of the easy ADL ecology based on egocentric interaction, comprising of smart objects, a personal activity-centric middleware, ambient intelligence applications aimed at everyday activity support, and a human agent literally in the middle of it all is described. The middleware was developed to address important challenges in ambient intelligence: (1) tracking and managing smart objects; (2) tracking a human agent’s situative spaces; (3) recognizing human activities and actions; (4) managing and facilitating human-environment interaction; and (5) to ease up the development of ambient intelligence applications. The easy ADL ecology was first simulated in immersive virtual reality, and then set up physically as a living laboratory to evaluate: (1) the technological and technical performance of individual middleware components, (2) to perform a user experience evaluation assessing various aspects of user satisfaction in relation to the support offered by the easy ADL ecology, and (3) to use it as a research test bed for addressing challenges in ambient intelligence. While it is problematic to directly compare the “proof-of-concept” easy ADL ecology with related research efforts, it is clear from the user experience evaluation that the subjects were positive with the services it offered. / easy ADL project