An IoT based Virtual Coaching System (VSC) for Assisting Activities of Daily Life

Nowadays aging of the population is becoming one of the main concerns of theworld. It is estimated that the number of people aged over 65 will increase from 461million to 2 billion in 2050. This substantial increment in the elderly population willhave significant consequences in the social and health care system. Therefore, in thecontext of Ambient Intelligence (AmI), the Ambient Assisted Living (AAL) has beenemerging as a new research area to address problems related to the aging of the population. AAL technologies based on embedded devices have demonstrated to be effectivein alleviating the social- and health-care issues related to the continuous growing of theaverage age of the population. Many smart applications, devices and systems have beendeveloped to monitor the health status of elderly, substitute them in the accomplishment of activities of the daily life (especially in presence of some impairment or disability),alert their caregivers in case of necessity and help them in recognizing risky situations.Such assistive technologies basically rely on the communication and interaction be-tween body sensors, smart environments and smart devices. However, in such contextless effort has been spent in designing smart solutions for empowering and supportingthe self-efficacy of people with neurodegenerative diseases and elderly in general. Thisthesis fills in the gap by presenting a low-cost, non intrusive, and ubiquitous VirtualCoaching System (VCS) to support people in the acquisition of new behaviors (e.g.,taking pills, drinking water, finding the right key, avoiding motor blocks) necessary tocope with needs derived from a change in their health status and a degradation of theircognitive capabilities as they age. VCS is based on the concept of extended mind intro-duced by Clark and Chalmers in 1998. They proposed the idea that objects within theenvironment function as a part of the mind. In my revisiting of the concept of extendedmind, the VCS is composed of a set of smart objects that exploit the Internet of Things(IoT) technology and machine learning-based algorithms, in order to identify the needsof the users and react accordingly. In particular, the system exploits smart tags to trans-form objects commonly used by people (e.g., pillbox, bottle of water, keys) into smartobjects, it monitors their usage according to their needs, and it incrementally guidesthem in the acquisition of new behaviors related to their needs. To implement VCS, thisthesis explores different research directions and challenges. First of all, it addresses thedefinition of a ubiquitous, non-invasive and low-cost indoor monitoring architecture byexploiting the IoT paradigm. Secondly, it deals with the necessity of developing solu-tions for implementing coaching actions and consequently monitoring human activitiesby analyzing the interaction between people and smart objects. Finally, it focuses on the design of low-cost localization systems for indoor environment, since knowing theposition of a person provides VCS with essential information to acquire information onperformed activities and to prevent risky situations. In the end, the outcomes of theseresearch directions have been integrated into a healthcare application scenario to imple-ment a wearable system that prevents freezing of gait in people affected by Parkinson\u2019sDisease

Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications

Nowadays, the availability of the location information becomes a key factor in today’s communications systems for allowing location based services. In outdoor scenarios, the Mobile Terminal (MT) position is obtained with high accuracy thanks to the Global Positioning System (GPS) or to the standalone cellular systems. However, the main problem of GPS or cellular systems resides in the indoor environment and in scenarios with deep shadowing effect where the satellite or cellular signals are broken. In this paper, we will present a review over different technologies and concepts used to improve indoor localization. Additionally, we will discuss different applications based on different localization approaches. Finally, comprehensive challenges in terms of accuracy, cost, complexity, security, scalability, etc. are presente

Visible Light Communication Cyber Security Vulnerabilities For Indoor And Outdoor Vehicle-To-Vehicle Communication

Light fidelity (Li-Fi), developed from the approach of Visible Light Communication (VLC), is a great replacement or complement to existing radio frequency-based (RF) networks. Li-Fi is expected to be deployed in various environments were, due to Wi-Fi congestion and health limitations, RF should not be used. Moreover, VLC can provide the future fifth generation (5G) wireless technology with higher data rates for device connectivity which will alleviate the traffic demand. 5G is playing a vital role in encouraging the modern applications. In 2023, the deployment of all the cellular networks will reach more than 5 billion users globally. As a result, the security and privacy of 5G wireless networks is an essential problem as those modern applications are in people\u27s life everywhere. VLC security is as one of the core physical-layer security (PLS) solutions for 5G networks. Due to the fact that light does not penetrate through solid objects or walls, VLC naturally has higher security and privacy for indoor wireless networks compared to RF networks. However, the broadcasting nature of VLC caused concerns, e.g., eavesdropping, have created serious attention as it is a crucial step to validate the success of VLC in wild. The aim of this thesis is to properly address the security issues of VLC and further enhance the VLC nature security. We analyzed the secrecy performance of a VLC model by studying the characteristics of the transmitter, receiver and the visible light channel. Moreover, we mitigated the security threats in the VLC model for the legitimate user, by 1) implementing more access points (APs) in a multiuser VLC network that are cooperated, 2) reducing the semi-angle of LED to help improve the directivity and secrecy and, 3) using the protected zone strategy around the AP where eavesdroppers are restricted. According to the model\u27s parameters, the results showed that the secrecy performance in the proposed indoor VLC model and the vehicle-to-vehicle (V2V) VLC outdoor model using a combination of multiple PLS techniques as beamforming, secure communication zones, and friendly jamming is enhanced. The proposed model security performance was measured with respect to the signal to noise ratio (SNR), received optical power, and bit error rate (BER) Matlab simulation results

Low-Cost Indoor Localisation Based on Inertial Sensors, Wi-Fi and Sound

The average life expectancy has been increasing in the last decades, creating the need for new technologies to improve the quality of life of the elderly. In the Ambient Assisted Living scope, indoor location systems emerged as a promising technology capable of sup porting the elderly, providing them a safer environment to live in, and promoting their autonomy. Current indoor location technologies are divided into two categories, depend ing on their need for additional infrastructure. Infrastructure-based solutions require expensive deployment and maintenance. On the other hand, most infrastructure-free systems rely on a single source of information, being highly dependent on its availability. Such systems will hardly be deployed in real-life scenarios, as they cannot handle the absence of their source of information. An efficient solution must, thus, guarantee the continuous indoor positioning of the elderly. This work proposes a new room-level low-cost indoor location algorithm. It relies on three information sources: inertial sensors, to reconstruct users’ trajectories; environ mental sound, to exploit the unique characteristics of each home division; and Wi-Fi, to estimate the distance to the Access Point in the neighbourhood. Two data collection protocols were designed to resemble a real living scenario, and a data processing stage was applied to the collected data. Then, each source was used to train individual Ma chine Learning (including Deep Learning) algorithms to identify room-level positions. As each source provides different information to the classification, the data were merged to produce a more robust localization. Three data fusion approaches (input-level, early, and late fusion) were implemented for this goal, providing a final output containing complementary contributions from all data sources. Experimental results show that the performance improved when more than one source was used, attaining a weighted F1-score of 81.8% in the localization between seven home divisions. In conclusion, the evaluation of the developed algorithm shows that it can achieve accurate room-level indoor localization, being, thus, suitable to be applied in Ambient Assisted Living scenarios.O aumento da esperança média de vida nas últimas décadas, criou a necessidade de desenvolvimento de tecnologias que permitam melhorar a qualidade de vida dos idosos. No âmbito da Assistência à Autonomia no Domicílio, sistemas de localização indoor têm emergido como uma tecnologia promissora capaz de acompanhar os idosos e as suas atividades, proporcionando-lhes um ambiente seguro e promovendo a sua autonomia. As tecnologias de localização indoor atuais podem ser divididas em duas categorias, aquelas que necessitam de infrastruturas adicionais e aquelas que não. Sistemas dependentes de infrastrutura necessitam de implementação e manutenção que são muitas vezes dispendiosas. Por outro lado, a maioria das soluções que não requerem infrastrutura, dependem de apenas uma fonte de informação, sendo crucial a sua disponibilidade. Um sistema que não consegue lidar com a falta de informação de um sensor dificilmente será implementado em cenários reais. Uma solução eficiente deverá assim garantir o acompanhamento contínuo dos idosos. A solução proposta consiste no desenvolvimento de um algoritmo de localização indoor de baixo custo, baseando-se nas seguintes fontes de informação: sensores inerciais, capazes de reconstruir a trajetória do utilizador; som, explorando as características dis tintas de cada divisão da casa; e Wi-Fi, responsável pela estimativa da distância entre o ponto de acesso e o smartphone. Cada fonte sensorial, extraída dos sensores incorpora dos no dispositivo, foi, numa primeira abordagem, individualmente otimizada através de algoritmos de Machine Learning (incluindo Deep Learning). Como os dados das diversas fontes contêm informação diferente acerca das mesmas características do sistema, a sua fusão torna a classificação mais informada e robusta. Com este objetivo, foram implementadas três abordagens de fusão de dados (input data, early and late fusion), fornecendo um resultado final derivado de contribuições complementares de todas as fontes de dados. Os resultados experimentais mostram que o desempenho do algoritmo desenvolvido melhorou com a inclusão de informação multi-sensor, alcançando um valor para F1- score de 81.8% na distinção entre sete divisões domésticas. Concluindo, o algoritmo de localização indoor, combinando informações de três fontes diferentes através de métodos de fusão de dados, alcançou uma localização room-level e está apto para ser aplicado num cenário de Assistência à Autonomia no Domicílio

A Risk-Based IoT Decision-Making Framework Based on Literature Review with Human Activity Recognition Case Studies

The Internet of Things (IoT) is a key and growing technology for many critical real-life applications, where it can be used to improve decision making. The existence of several sources of uncertainty in the IoT infrastructure, however, can lead decision makers into taking inappropriate actions. The present work focuses on proposing a risk-based IoT decision-making framework in order to effectively manage uncertainties in addition to integrating domain knowledge in the decision-making process. A structured literature review of the risks and sources of uncertainty in IoT decision-making systems is the basis for the development of the framework and Human Activity Recognition (HAR) case studies. More specifically, as one of the main targeted challenges, the potential sources of uncertainties in an IoT framework, at different levels of abstraction, are firstly reviewed and then summarized. The modules included in the framework are detailed, with the main focus given to a novel risk-based analytics module, where an ensemble-based data analytic approach, called Calibrated Random Forest (CRF), is proposed to extract useful information while quantifying and managing the uncertainty associated with predictions, by using confidence scores. Its output is subsequently integrated with domain knowledge-based action rules to perform decision making in a cost-sensitive and rational manner. The proposed CRF method is firstly evaluated and demonstrated on a HAR scenario in a Smart Home environment in case study I and is further evaluated and illustrated with a remote health monitoring scenario for a diabetes use case in case study II. The experimental results indicate that using the framework’s raw sensor data can be converted into meaningful actions despite several sources of uncertainty. The comparison of the proposed framework to existing approaches highlights the key metrics that make decision making more rational and transparent

A Conceptual Model using Ambient Assisted Living to Provide a Home Proactive Monitoring System for Elderly People in the Kingdom of Saudi Arabia

The growth in the ageing population is rapidly increasing and their care cost will be a challenging issue in the future. The number of elderly people worldwide (defined as those aged 60 years and older) was 202 million in 1950; this number has since quadrupled to reach 901 million and is expected to triple again by 2100. In particular, the number of elderly people in the Kingdom of Saudi Arabia (KSA) is increasing rapidly, from 5% of the total population in 2015 to a forecasted 20.9% by 2050. Clearly, the cost of taking care of elderly people is already a challenge, but it will be very difficult to meet in the future, when it will lead to a much higher expenditure on healthcare facilities. Furthermore, although elderly people are vulnerable to a decline in their health, they do not wish to live as they did in the 1970s to 1990s. Instead, their desire is to live independently in their own homes and continue to practice normal activities. In fact, Saudi culture is changing, and the children tend not to live with their parents as they used to. However, the literature review indicates that there is a lack of professionally designed systems that can fulfil the growing needs or requirements of elderly people in the KSA. These demographic changes raise a number of challenges related to the elderly people’s quality of life, including health, autonomy, care, social communication, and the utilisation of institutional services. These challenges require novel approaches to provide dependable self-adapting technological innovations. The era of Information and Communication Technology (ICT) has changed the world of the ageing population. Ambient Assisted Living (AAL) aims to improve the quality of life of elderly people, and to provide them with technologies and services that support their daily activities, help them to live longer and remain independently at home. The aims and objectives of this research are to review Ambient Assisted Living Technology, to provide examples of relevant technologies and applications, and to examine attitudes and perceptions of elderly people towards using AAL technologies in the KSA. This research also explores the factors of AAL, identifying those that affect the adoption of these technologies in the KSA, by conducting a systematic review, and using quantitative and qualitative analyses. The questionnaire results showed that elderly Saudi Arabians are willing and intending to accept and use AAL technologies, and that there are many factors that influence their adoption and use of AAL technologies. This provides an insight for solutions to the provision of support for their independent living. Thus, we developed a conceptual model using AAL to provide a Home Proactive Monitoring System (AALHPMS) that supports the stakeholders in adopting AAL technologies. We envisage that the AALHPMS can fulfil the needs and requirements of elderly people, motivate healthcare providers to implement AAL technologies, and assist the Saudi Government to make suitable provision for issues associated with the ageing population. In addition, a knowledge-based-system was built using a rule-based system. Experiments using Smart watches were conducted to monitor the heart rates. Further experiments using ZigBee, Bluetooth beacons, and surveillance cameras technology were also undertaken for monitoring the movement of elderly persons at their home. A website was also developed to disseminate knowledge related to ageing population and AAL technology in Saudi Arabia

IEEE 802.21 in heterogeneous handover environments

Mestrado em Engenharia de Computadores e TelemáticaO desenvolvimento das capacidades tecnológicas dos terminais móveis, e das infra-estruturas que os suportam, potenciam novos cenários onde estes dispositivos munidos com interfaces de diferentes tecnologias vagueiam entre diferentes ambientes de conectividade. É assim necessário providenciar meios que facilitem a gestão de mobilidade, permitindo ao terminal ligar-se da melhor forma (i.e., optando pela melhor tecnologia) em qualquer altura. A norma IEEE 802.21 está a ser desenvolvida pelo Institute of Electrical and Electronics Engineers (IEEE) com o intuito de providenciar mecanismos e serviços que facilitem e optimizem handovers de forma independente da tecnologia. A norma 802.21 especifica assim um conjunto de mecanismos que potenciarão cenários como o descrito acima, tendo em conta a motivação e requerimentos apresentados por arquitecturas de redes futuras, como as redes de quarta geração (4G). Esta dissertação apresenta uma análise extensiva da norma IEEE 802.21, introduzindo um conjunto de simulações desenvolvidas para estudar o impacto da utilização de mecanismos 802.21 em handovers controlados por rede, numa rede de acesso mista composta por tecnologias 802.11 e 3G. Os resultados obtidos permitiram verificar a aplicabilidade destes conceitos a ambientes de próxima geração, motivando também uma descrição do desenho de integração de mecanismos 802.21 a arquitecturas de redes de quarta geração. ABSTRACT: The development of the technological capabilities of mobile terminals, and the infra-structures that support them, enable new scenarios where these devices using different technology interfaces roam in different connectivity environments. This creates a need for providing the means that facilitate mobility management, allowing the terminal to connect in the best way possible (i.e., by choosing the best technology) at any time. The IEEE 802.21 standard is being developed by the Institute of Electrical and Electronics Engineers (IEEE) to provide mechanisms and services supporting Media Independent Handovers. The 802.21 standard specifies a set of mechanisms that enable scenarios like the one described above, considering the motivation and requirements presented by future network architectures, such as the ones from fourth generation networks (4G). This thesis presents an extensive analysis of the IEEE 802.21 standard, introducing a set of simulations developed for studying the impact of using 802.21 mechanisms in network controlled handovers, in a mixed access network composed of 802.11 and 3G technologies. The obtained results allow the verification of the applicability of these concepts into next generation environments, also motivating the description of the design for integration of 802.21 mechanisms to fourth generation networks

Mobile network design : Orange UK 2G to 3G mobile backhaul evolution

The research presented in this thesis is focused on the evolution of a GSM/GPRS (2G) cellular mobile network to UMTS (3G) and then subsequently, HSDPA. The particular technical area of research relates to the mobile backhaul network which provides the connectivity between radio cell sites which support the wide area radio coverage, and the mobile network operator’s core network. Due to the evolution of UMTS with HSDPA, the research covers the initial UMTS network rollout and then addresses the evolution of this infrastructure to support mobile broadband communications, through the introduction of HSDPA as a network upgrade. The two research questions being addressed are therefore: •How is it possible to evolve a GSM/GPRS mobile backhaul network to support a converged GSM/GPRS and UMTS cellular mobile service? •How is it possible to ensure scalability of the converged backhaul network given the introduction of HSDPA and associated mobile broadband data growth? The starting point of the research is an established GSM and GPRS commercial network in the UK and the study is based on the design of the Orange network and focused on the period 2000 to 2010. During this period the author was working as Principal Network Designer within Orange and had overall responsibility for the strategy, architecture and design of the UK mobile backhaul network. The thesis provides a detailed explanation of the novel network design that was adopted and how it was evolved throughout the ten year period covered by the research. The research proves that the original static TDM approach was not suitable for UMTS and therefore the outcome was the introduction of an ATM network with optimisation based on traffic class rt-VBR over protected STM-1 transmission links. HSDPA drove further traffic growth and resulted in an evolution of the solution to ensure massive scalability was supported through the migration to Carrier Ethernet and implementation of pseudo-wires. In addition, to providing a technical description of the network design, the thesis also aims to provide a historical record of the technologies and equipment used during this period of rapid change within the UKs mobile networks