Non-obstructive authentication in AAL environments

Ambient Assisted Living environments projects arise as technological responses of the scientific community to problems associated with the population-ageing phenomenon. In theory, these environments should allow de-localization of healthcare services delivery and management to the home, thus containing the economic and social costs associated with old age. The VirtualECare project is one of those environments, enhanced with proactive techniques for a better user experience, focused on elderly chronic patients, through the ability of constant learning and adaption based in user interaction and its contexts. This learning and, consequently, adaption needs, however, unequivocally user identification, especially in multi-user environments. Traditional identification techniques and methodologies are not suitable for these scenario since, usually, require user interaction and wireless identification technique (e.g. RFID, Bluetooth) are very exposed to personification. In order to obtain the expected results we needed a more advanced technology. One possible, appropriate and already fairly developed technique is Facial Recognition. In this paper we present the VirtualECare project approach to Facial Recognition authentication techniques its advantages, disadvantages and possible implementations paths

Analysis of key aspects to manage Wireless Sensor Networks in Ambient Assisted Living environments

Wireless Sensor Networks (WSN) based on ZigBee/IEEE 802.15.4 will be key enablers of non-invasive, highly sensitive infrastructures to support the provision of future ambient assisted living services. This paper addresses the main design concerns and requirements when conceiving ambient care systems (ACS), frameworks to provide remote monitoring, emergency detection, activity logging and personal notifications dispatching services. In particular, the paper describes the design of an ACS built on top of a WSN composed of Crossbow's MICAz devices, external sensors and PDAs enabled with ZigBee technology. The middleware is integrated in an OSGi framework that processes the acquired information to provide ambient services and also enables smart network control. From our experience, we consider that in a future, the combination of ZigBee technology together with a service oriented architecture may be a versatile approach to AAL services offering, both from the technical and business points of view

An open platform for seamless sensor support in healthcare for the Internet of things

Population aging and increasing pressure on health systems are two issues that demand solutions. Involving and empowering citizens as active managers of their health represents a desirable shift from the current culture mainly focused on treatment of disease, to one also focused on continuous health management and well-being. Current developments in technological areas such as the Internet of Things (IoT), lead to new technological solutions that can aid this shift in the healthcare sector. This study presents the design, development, implementation and evaluation of a platform called Common Recognition and Identification Platform (CRIP), a part of the CareStore project, which aims at supporting caregivers and citizens to manage health routines in a seamless way. Specifically, the CRIP offers sensor-based support for seamless identification of users and health devices. A set of initial requirements was defined with a focus on usability limitations and current sensor technologies. The CRIP was designed and implemented using several technologies that enable seamless integration and interaction of sensors and people, namely Near Field Communication and fingerprint biometrics for identification and authentication, Bluetooth for communication with health devices and web services for wider integration with other platforms. Two CRIP prototypes were implemented and evaluated in laboratory during a period of eight months. The evaluations consisted of identifying users and devices, as well as seamlessly configure and acquire vital data from the last. Also, the entire Carestore platform was deployed in a nursing home where its usability was evaluated with caregivers. The evaluations helped assess that seamless identification of users and seamless configuration and communication with health devices is feasible and can help enable the IoT on healthcare applications. Therefore, the CRIP and similar platforms could be transformed into a valuable enabling technology for secure and reliable IoT deployments on the healthcare sector.This research work was supported under the European Framework Program FP7 Research for the Benefit of SMEs, project FP7-SME-2012-315158-CareStore. The authors would also like to acknowledge the work of all the members of the CareStore team, without whom this work would not be possible

Internet of Things Architectures for Enhanced Living Environments

Ambient Assisted Living (AAL) is an emerging multidisciplinary research area that aims to create an ecosystem of different types of sensors, computers, mobile devices, wireless networks, and software applications for enhanced living environments and occupational health. There are several challenges in the development and implementation of an effective AAL system, such as system architecture, human-computer interaction, ergonomics, usability, and accessibility. There are also social and ethical challenges, such as acceptance by seniors and the privacy and confidentiality that must be a requirement of AAL devices. It is also essential to ensure that technology does not replace human care and is used as a relevant complement. The Internet of Things (IoT) is a paradigm where objects are connected to the Internet and support sensing capabilities. IoT devices should be ubiquitous, recognize the context, and support intelligence capabilities closely related to AAL. Technological advances allow defining new advanced tools and platforms for real-time health monitoring and decision making in the treatment of various diseases. IoT is a suitable approach to building healthcare systems, and it provides a suitable platform for ubiquitous health services, using, for example, portable sensors to carry data to servers and smartphones for communication. Despite the potential of the IoT paradigm and technologies for healthcare systems, several challenges to be overcome still exist. The direction and impact of IoT in the economy are not clearly defined, and there are barriers to the immediate and ubiquitous adoption of IoT products, services, and solutions. Several sources of pollutants have a high impact on indoor living environments. Consequently, indoor air quality is recognized as a fundamental variable to be controlled for enhanced health and well-being. It is critical to note that typically most people occupy more than 90% of their time inside buildings, and poor indoor air quality negatively affects performance and productivity. Research initiatives are required to address air quality issues to adopt legislation and real-time inspection mechanisms to improve public health, not only to monitor public places, schools, and hospitals but also to increase the rigor of building rules. Therefore, it is necessary to use real-time monitoring systems for correct analysis of indoor air quality to ensure a healthy environment in at least public spaces. In most cases, simple interventions provided by homeowners can produce substantial positive impacts on indoor air quality, such as avoiding indoor smoking and the correct use of natural ventilation. An indoor air quality monitoring system helps the detection and improvement of air quality conditions. Local and distributed assessment of chemical concentrations is significant for safety (e.g., detection of gas leaks and monitoring of pollutants) as well as to control heating, ventilation, and HVAC systems to improve energy efficiency. Real-time indoor air quality monitoring provides reliable data for the correct control of building automation systems and should be assumed as a decision support platform on planning interventions for enhanced living environments. However, the monitoring systems currently available are expensive and only allow the collection of random samples that are not provided with time information. Most solutions on the market only allow data consulting limited to device memory and require procedures for downloading and manipulating data with specific software. In this way, the development of innovative environmental monitoring systems based on ubiquitous technologies that allow real-time analysis becomes essential. This thesis resulted in the design and development of IoT architectures using modular and scalable structures for air quality monitoring based on data collected from cost-effective sensors for enhanced living environments. The proposed architectures address several concepts, including acquisition, processing, storage, analysis, and visualization of data. These systems incorporate an alert management Framework that notifies the user in real-time in poor indoor air quality scenarios. The software Framework supports multiple alert methods, such as push notifications, SMS, and e-mail. The real-time notification system offers several advantages when the goal is to achieve effective changes for enhanced living environments. On the one hand, notification messages promote behavioral changes. These alerts allow the building manager to identify air quality problems and plan interventions to avoid unhealthy air quality scenarios. The proposed architectures incorporate mobile computing technologies such as mobile applications that provide ubiquitous air quality data consulting methods s. Also, the data is stored and can be shared with medical teams to support the diagnosis. The state-of-the-art analysis has resulted in a review article on technologies, applications, challenges, opportunities, open-source IoT platforms, and operating systems. This review was significant to define the IoT-based Framework for indoor air quality supervision. The research leads to the development and design of cost-effective solutions based on open-source technologies that support Wi-Fi communication and incorporate several advantages such as modularity, scalability, and easy installation. The results obtained are auspicious, representing a significant contribution to enhanced living environments and occupational health. Particulate matter (PM) is a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air. Moreover, it is considered the pollutant that affects more people. The most damaging particles to health are ≤PM10 (diameter 10 microns or less), which can penetrate and lodge deep within the lungs, contributing to the risk of developing cardiovascular and respiratory diseases as well as lung cancer. Taking into account the adverse health effects of PM exposure, an IoT architecture for automatic PM monitoring was proposed. The proposed architecture is a PM real-time monitoring system and a decision-making tool. The solution consists of a hardware prototype for data acquisition and a Web Framework developed in .NET for data consulting. This system is based on open-source and technologies, with several advantages compared to existing systems, such as modularity, scalability, low-cost and easy installation. The data is stored in a database developed in SQL SERVER using .NET Web services. The results show the ability of the system to analyze the indoor air quality in real-time and the potential of the Web Framework for the planning of interventions to ensure safe, healthy, and comfortable conditions. Associations of high concentrations of carbon dioxide (CO2) with low productivity at work and increased health problems are well documented. There is also a clear correlation between high levels of CO2 and high concentrations of pollutants in indoor air. There are sufficient reasons to monitor CO2 and provide real-time notifications to improve occupational health and provide a safe and healthy indoor living environment. Taking into account the significant influence of CO2 for enhanced living environments, a real-time IoT architecture for CO2 monitoring was proposed. CO2 was selected because it is easy to measure and is produced in quantity (by people and combustion equipment). It can be used as an indicator of other pollutants and, therefore, of air quality in general. The solution consists of a hardware prototype for data acquisition environment, a Web software, and a smartphone application for data consulting. The proposed architecture is based on open-source technologies, and the data is stored in a SQL SERVER database. The mobile Framework allows the user not only to consult the latest data collected but also to receive real-time notifications in poor indoor air quality scenarios, and to configure the alerts threshold levels. The results show that the mobile application not only provides easy access to real-time air quality data, but also allows the user to maintain parameter history and provide a history of changes. Consequently, this system allows the user to analyze in a precise and detailed manner the behavior of air quality. Finally, an air quality monitoring solution was implemented, consisting of a hardware prototype that incorporates only the MICS-6814 sensor as the detection unit. This system monitors various air quality parameters such as NH3 (ammonia), CO (carbon monoxide), NO2 (nitrogen dioxide), C3H8 (propane), C4H10 (butane), CH4 (methane), H2 (hydrogen) and C2H5OH (ethanol). The monitoring of the concentrations of these pollutants is essential to provide enhanced living environments. This solution is based on Cloud, and the collected data is sent to the ThingSpeak platform. The proposed Framework combines sensitivity, flexibility, and measurement accuracy in real-time, allowing a significant evolution of current air quality controls. The results show that this system provides easy, intuitive, and fast access to air quality data as well as relevant notifications in poor air quality situations to provide real-time intervention and improve occupational health. These data can be accessed by physicians to support diagnoses and correlate the symptoms and health problems of patients with the environment in which they live. As future work, the results reported in this thesis can be considered as a starting point for the development of a secure system sharing data with health professionals in order to serve as decision support in diagnosis.Ambient Assisted Living (AAL) é uma área de investigação multidisciplinar emergente que visa a construção de um ecossistema de diferentes tipos de sensores, microcontroladores, dispositivos móveis, redes sem fios e aplicações de software para melhorar os ambientes de vida e a saúde ocupacional. Existem muitos desafios no desenvolvimento e na implementação de um sistema AAL, como a arquitetura do sistema, interação humano-computador, ergonomia, usabilidade e acessibilidade. Existem também problemas sociais e éticos, como a aceitação por parte dos utilizadores mais vulneráveis e a privacidade e confidencialidade, que devem ser uma exigência de todos os dispositivos AAL. De facto, também é essencial assegurar que a tecnologia não substitua o cuidado humano e seja usada como um complemento essencial. A Internet das Coisas (IoT) é um paradigma em que os objetos estão conectados à Internet e suportam recursos sensoriais. Tendencialmente, os dispositivos IoT devem ser omnipresentes, reconhecer o contexto e ativar os recursos de inteligência ambiente intimamente relacionados ao AAL. Os avanços tecnológicos permitem definir novas ferramentas avançadas e plataformas para monitorização de saúde em tempo real e tomada de decisão no tratamento de várias doenças. A IoT é uma abordagem adequada para construir sistemas de saúde sendo que oferece uma plataforma para serviços de saúde ubíquos, usando, por exemplo, sensores portáteis para recolha e transmissão de dados e smartphones para comunicação. Apesar do potencial do paradigma e tecnologias IoT para o desenvolvimento de sistemas de saúde, muitos desafios continuam ainda por ser resolvidos. A direção e o impacto das soluções IoT na economia não está claramente definido existindo, portanto, barreiras à adoção imediata de produtos, serviços e soluções de IoT. Os ambientes de vida são caracterizados por diversas fontes de poluentes. Consequentemente, a qualidade do ar interior é reconhecida como uma variável fundamental a ser controlada de forma a melhorar a saúde e o bem-estar. É importante referir que tipicamente a maioria das pessoas ocupam mais de 90% do seu tempo no interior de edifícios e que a má qualidade do ar interior afeta negativamente o desempenho e produtividade. É necessário que as equipas de investigação continuem a abordar os problemas de qualidade do ar visando a adoção de legislação e mecanismos de inspeção que atuem em tempo real para a melhoraria da saúde e qualidade de vida, tanto em locais públicos como escolas e hospitais e residências particulares de forma a aumentar o rigor das regras de construção de edifícios. Para tal, é necessário utilizar mecanismos de monitorização em tempo real de forma a possibilitar a análise correta da qualidade do ambiente interior para garantir ambientes de vida saudáveis. Na maioria dos casos, intervenções simples que podem ser executadas pelos proprietários ou ocupantes da residência podem produzir impactos positivos substanciais na qualidade do ar interior, como evitar fumar em ambientes fechados e o uso correto de ventilação natural. Um sistema de monitorização e avaliação da qualidade do ar interior ajuda na deteção e na melhoria das condições ambiente. A avaliação local e distribuída das concentrações químicas é significativa para a segurança (por exemplo, deteção de fugas de gás e supervisão dos poluentes) bem como para controlar o aquecimento, ventilação, e sistemas de ar condicionado (HVAC) visando a melhoria da eficiência energética. A monitorização em tempo real da qualidade do ar interior fornece dados fiáveis para o correto controlo de sistemas de automação de edifícios e deve ser assumida com uma plataforma de apoio à decisão no que se refere ao planeamento de intervenções para ambientes de vida melhorados. No entanto, os sistemas de monitorização atualmente disponíveis são de alto custo e apenas permitem a recolha de amostras aleatórias que não são providas de informação temporal. A maioria das soluções disponíveis no mercado permite apenas a acesso ao histórico de dados que é limitado à memória do dispositivo e exige procedimentos de download e manipulação de dados com software proprietário. Desta forma, o desenvolvimento de sistemas inovadores de monitorização ambiente baseados em tecnologias ubíquas e computação móvel que permitam a análise em tempo real torna-se essencial. A Tese resultou na definição e no desenvolvimento de arquiteturas para monitorização da qualidade do ar baseadas em IoT. Os métodos propostos são de baixo custo e recorrem a estruturas modulares e escaláveis para proporcionar ambientes de vida melhorados. As arquiteturas propostas abordam vários conceitos, incluindo aquisição, processamento, armazenamento, análise e visualização de dados. Os métodos propostos incorporam Frameworks de gestão de alertas que notificam o utilizador em tempo real e de forma ubíqua quando a qualidade do ar interior é deficiente. A estrutura de software suporta vários métodos de notificação, como notificações remotas para smartphone, SMS (Short Message Service) e email. O método usado para o envio de notificações em tempo real oferece várias vantagens quando o objetivo é alcançar mudanças efetivas para ambientes de vida melhorados. Por um lado, as mensagens de notificação promovem mudanças de comportamento. De facto, estes alertas permitem que o gestor do edifício e os ocupantes reconheçam padrões da qualidade do ar e permitem também um correto planeamento de intervenções de forma evitar situações em que a qualidade do ar é deficiente. Por outro lado, o sistema proposto incorpora tecnologias de computação móvel, como aplicações móveis, que fornecem acesso omnipresente aos dados de qualidade do ar e, consequentemente, fornecem soluções completas para análise de dados. Além disso, os dados são armazenados e podem ser partilhados com equipas médicas para ajudar no diagnóstico. A análise do estado da arte resultou na elaboração de um artigo de revisão sobre as tecnologias, aplicações, desafios, plataformas e sistemas operativos que envolvem a criação de arquiteturas IoT. Esta revisão foi um trabalho fundamental na definição das arquiteturas propostas baseado em IoT para a supervisão da qualidade do ar interior. Esta pesquisa conduz a um desenvolvimento de arquiteturas IoT de baixo custo com base em tecnologias de código aberto que operam como um sistema Wi-Fi e suportam várias vantagens, como modularidade, escalabilidade e facilidade de instalação. Os resultados obtidos são muito promissores, representando uma contribuição significativa para ambientes de vida melhorados e saúde ocupacional. O material particulado (PM) é uma mistura complexa de partículas sólidas e líquidas de substâncias orgânicas e inorgânicas suspensas no ar e é considerado o poluente que afeta mais pessoas. As partículas mais prejudiciais à saúde são as ≤PM10 (diâmetro de 10 micrómetros ou menos), que podem penetrar e fixarem-se dentro dos pulmões, contribuindo para o risco de desenvolver doenças cardiovasculares e respiratórias, bem como de cancro do pulmão. Tendo em consideração os efeitos negativos para a saúde da exposição ao PM foi desenvolvido numa primeira fase uma arquitetura IoT para monitorização automática dos níveis de PM. Esta arquitetura é um sistema que permite monitorização de PM em tempo real e uma ferramenta de apoio à tomada de decisão. A solução é composta por um protótipo de hardware para aquisição de dados e um portal Web desenvolvido em .NET para consulta de dados. Este sistema é baseado em tecnologias de código aberto com várias vantagens em comparação aos sistemas existentes, como modularidade, escalabilidade, baixo custo e fácil instalação. Os dados são armazenados numa base de dados desenvolvida em SQL SERVER e são enviados com recurso a serviços Web. Os resultados mostram a capacidade do sistema de analisar em tempo real a qualidade do ar interior e o potencial da Framework Web para o planeamento de intervenções com o objetivo de garantir condições seguras, saudáveis e confortáveis. Associações de altas concentrações de dióxido de carbono (CO2) com défice de produtividade no trabalho e aumento de problemas de saúde encontram-se bem documentadas. Existe também uma correlação evidente entre altos níveis de CO2 e altas concentrações de poluentes no ar interior. Tendo em conta a influência significativa do CO2 para a construção de ambientes de vida melhorados desenvolveu-se uma solução de monitorização em tempo real de CO2 com base na arquitetura de IoT. A arquitetura proposta permite também o envio de notificações em tempo real para melhorar a saúde ocupacional e proporcionar um ambiente de vida interior seguro e saudável. O CO2 foi selecionado, pois é fácil de medir e é produzido em quantidade (por pessoas e equipamentos de combustão). Assim, pode ser usado como um indicador de outros poluentes e, portanto, da qualidade do ar em geral. O método proposto é composto por um protótipo de hardware para aquisição de dados, um software Web e uma aplicação smartphone para consulta de dados. Esta arquitetura é baseada em tecnologias de código aberto e os dados recolhidos são armazenados numa base de dados SQL SERVER. A Framework móvel permite não só consultar em tempo real os últimos dados recolhidos, receber notificações com o objetivo de avisar o utilizador quando a qualidade do ar está deficiente, mas também para configurar alertas. Os resultados mostram que a Framework móvel fornece não apenas acesso fácil aos dados da qualidade do ar em tempo real, mas também permite ao utilizador manter o histórico de parâmetros. Assim este sistema permite ao utilizador analisar de maneira precisa e detalhada o comportamento da qualidade do ar interior. Por último, é proposta uma arquitetura para monitorização de vários parâmetros da qualidade do ar, como NH3 (amoníaco), CO (monóxido de carbono), NO2 (dióxido de azoto), C3H8 (propano), C4H10 (butano), CH4 (metano), H2 (hidrogénio) e C2H5OH (etanol). Esta arquitetura é composta por um protótipo de hardware que incorpora unicamente o sensor MICS-6814 como unidade de deteção. O controlo das concentrações destes poluentes é extremamente relevante para proporcionar ambientes de vida melhorados. Esta solução tem base na Cloud sendo que os dados recolhidos são enviados para a plataforma ThingSpeak. Esta Framework combina sensibilidade, flexibilidade e precisão de medição em tempo real, permitindo uma evolução significativa dos atuais sistemas de monitorização da qualidade do ar. Os resultados mostram que este sistema fornece acesso fácil, intuitivo e rápido aos dados de qualidade do ar bem como notificações essenciais em situações de qualidade do ar deficiente de forma a planear intervenções em tempo útil e melhorar a saúde ocupacional. Esses dados podem ser acedidos pelos médicos para apoiar diagnósticos e correlacionar os sintomas e problemas de saúde dos pacientes com o ambiente em que estes vivem. Como trabalho futuro, os resultados reportados nesta Tese podem ser considerados um ponto de partida para o desenvolvimento de um sistema seguro para partilha de dados com profissionais de saúde de forma a servir de suporte à decisão no diagnóstico

Holistic System Design for Distributed National eHealth Services

publishedVersio

System for monitoring and supporting the treatment of sleep apnea using IoT and big data

[EN] Sleep apnea has become in the sleep disorder that causes greater concern in recent years due to its morbidity and mortality, higher medical care costs and poor people quality of life. Some proposals have addressed sleep apnea disease in elderly people, but they have still some technical limitations. For these reasons, this paper presents an innovative system based on fog and cloud computing technologies which in combination with IoT and big data platforms offers new opportunities to build novel and innovative services for supporting the sleep apnea and to overcome the current limitations. Particularly, the system is built on several low-power wireless networks with heterogeneous smart devices (i.e, sensors and actuators). In the fog, an edge node (Smart IoT Gateway) provides IoT connection and interoperability and pre-processing IoT data to detect events in real-time that might endanger the elderly's health and to act accordingly. In the cloud, a Generic Enabler Context Broker manages, stores and injects data into the big data analyzer for further processing and analyzing. The system's performance and subjective applicability are evaluated using over 30 GB size datasets and a questionnaire fulfilled by medicals specialist, respectively. Results show that the system data analytics improve the health professionals' decision making to monitor and guide sleep apnea treatment, as well as improving elderly people's quality of life. (C) 2018 Elsevier B.V. All rights reserved.This research was supported by the Ecuadorian Government through the Secretary of Higher Education, Science, Technology, and Innovation (SENESCYT) and has received funding from the European Union's "Horizon 2020'' research and innovation program as part of the ACTIVAGE project under Grant 732679 and the Interoperability of Heterogeneous IoT Platforms project (INTER-IoT) under Grant 687283.Yacchirema-Vargas, DC.; Sarabia-Jácome, DF.; Palau Salvador, CE.; Esteve Domingo, M. (2018). System for monitoring and supporting the treatment of sleep apnea using IoT and big data. Pervasive and Mobile Computing. 50:25-40. https://doi.org/10.1016/j.pmcj.2018.07.007S25405

IoT-Based Applications in Healthcare Devices

The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic

Internet of things in health: Requirements, issues, and gaps

Background and objectives: The Internet of Things (IoT) paradigm has been extensively applied to several sectors in the last years, ranging from industry to smart cities. In the health domain, IoT makes possible new scenarios of healthcare delivery as well as collecting and processing health data in real time from sensors in order to make informed decisions. However, this domain is complex and presents several tech- nological challenges. Despite the extensive literature about this topic, the application of IoT in healthcare scarcely covers requirements of this sector. Methods: A literature review from January 2010 to February 2021 was performed resulting in 12,108 articles. After filtering by title, abstract, and content, 86 were eligible and examined according to three requirement themes: data lifecycle; trust, security, and privacy; and human-related issues. Results: The analysis of the reviewed literature shows that most approaches consider IoT application in healthcare merely as in any other domain (industry, smart cities…), with no regard of the specific requirements of this domain. Conclusions: Future effort s in this matter should be aligned with the specific requirements and needs of the health domain, so that exploiting the capabilities of the IoT paradigm may represent a meaningful step forward in the application of this technology in healthcare.Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía P18-TPJ - 307

Inferring Complex Activities for Context-aware Systems within Smart Environments

The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results

Smart Outdoors: a proposal for a public park in Campo de Ourique

Assistive technology-based innovation is a promising idea that aims to achieve and improve the well-being of humans. Currently, the focus of technology has changed, seeking to serve specific populations, especially the elderly, reducing the barriers they face on a daily basis when conducting outdoor activities. Most research carried out in an assisted environment is concentrated mainly in private spaces, such as homes, nursing homes and others. This research aims to propose design solutions based on the concept of an assisted environment on a city scale. By doing so, the elderly population can experience and live in collective and public environments (specifically in a public park) independently. In this context, interviews with specialists and observation studies were developed to understand the problems and needs of this specific population. Interviews were targeted to obtain insight from experts regarding the use of technology to solve the elderly’s problems in cities. However, the results did not give adequate insight to use within the study. Next, observations were also carried out in a public park in Campo Ourique, Lisbon to acquire insight from the field to observe/witness the problems of the elderly from a first-person point of view. The observation results showed the difficulties that the population in question faced. Consequently, design solution ideas were proposed to design a smart public park which might overcome the problems that were found in the literature and in the user observations. During the observations, it was seen that the elderly population is very active and highly values an outdoor space to spend time. In this sense, the design proposal could improve and facilitate the lives of the elderly, seeking as much as possible to reduce the barriers that were both observed and reported by experts throughout the interviews. Due to COVID-19, the study had limited access to the users and an evaluation phase could not be done. However, as a future work, user studies will continue to discover more about the elderly’s problems and eventually the scenarios and proposed solutions will be evaluated by them. Furthermore, applicability, usability and feasibility of the proposed ideas will be tested by more users (i.e., experts, stakeholders).A inovação baseada em tecnologia assistiva ainda é uma ideia promissora que visa alcançar e melhorar o bem-estar dos humanos. Atualmente, o foco da tecnologia mudou, buscando atender populações específicas, principalmente os idosos, reduzindo as barreiras que eles enfrentam no dia a dia na realização de atividades ao ar livre. A maioria das pesquisas realizadas em ambiente assistido concentra-se principalmente em espaços privados, como residências, asilos e outros. A pesquisa tem como objetivo propor soluções de design baseadas no conceito de ambiente assistido à escala da cidade, onde a população idosa pode vivenciar e viver os ambientes coletivos e públicos (especificamente num parque público) de forma independente. Nesse sentido, foram desenvolvidas entrevistas com especialistas e estudos de observação para entender os problemas e necessidades dessa população específica. As entrevistas foram direcionadas para obter insights de especialistas sobre o uso de tecnologia para resolver os problemas dos idosos nas cidades. No entanto, os resultados não forneceram percepções adequadas para serem usadas no estudo. Em seguida, foram também realizadas observações num parque público do Campo D’Ourique, em Lisboa, para obter insights do campo para observar / testemunhar os problemas dos idosos do ponto de vista da primeira pessoa. Os resultados da observação evidenciaram as dificuldades enfrentadas pela população em questão. Consequentemente, ideias de soluções de design foram propostas para projetar um parque público inteligente que pudesse superar os problemas que foram encontrados na literatura e nas observações do usuário. Durante as observações, percebeu-se que a população idosa é muito ativa e valoriza muito um espaço ao ar livre para passar o tempo. Nesse sentido, a proposta do projeto poderia melhorar e facilitar a vida dos idosos, buscando ao máximo reduzir as barreiras que foram observadas e relatadas pelos especialistas ao longo das entrevistas. Devido ao COVID-19, o estudo limitou-se ao acesso aos usuários e não foi possível realizar a fase de avaliação. No entanto, como um trabalho futuro, os estudos de usuários continuarão a descobrir mais sobre os problemas dos idosos e, eventualmente, os cenários e as soluções propostas serão avaliados por eles. Além disso, a aplicabilidade, usabilidade e viabilidade das ideias propostas serão testadas por mais usuários (ou seja, especialistas, partes interessadas)