Deployment of a smart telecare system to carry out an intelligent health monitoring at home

Information and Communication Technologies together appropriate reasoning tools can add value to current telecare systems, including smart tele-monitoring solutions to enhance the capability for identifying risk situations at home. Cooperation between Home Area Networks (HAN) and Body Area Networks (BAN) at home can provide smart systems to support effective health solutions for ageing people living alone, improving service quality and security to the users and relatives. This paper details the development of a reasoning platform to monitor situations of the person at home, and react in risk situations that demanding care support of remote careers. The system integrates BAN and HAN with intelligent agents, whose behavior is defined by ontologies and rules. The system manages environmental and user data to proactively detect risk situations, and dynamically adjust its behavior to trigger the adequate problem solve mechanisms. A development methodology was also adapted to sustain knowledge acquisition process from experts in all stages of the development process and to create the reasoning logic adapted to the users in telecare scenario. Thus, the platform is flexible and easily customizable, according hardware conditions and user profile

Towards a service-oriented architecture for a mobile assistive system with real-time environmental sensing

Dalian Key Lab. of Smart Medical and Healthcare, Computer Science Department, Dalian University, China,With the growing aging population, age-related diseases have increased considerably over the years. In response to these, ambient assistive living (AAL) systems are being developed and are continually evolving to enrich and support independent living. While most researchers investigate robust activity recognition (AR) techniques, this paper focuses on some of the architectural challenges of the AAL systems. This work proposes a system architecture that fuses varying software design patterns and integrates readily available hardware devices to create wireless sensor networks for real-time applications. The system architecture brings together the service-oriented architecture (SOA), semantic web technologies, and other methods to address some of the shortcomings of the preceding system implementations using off-the-shelf and open source components. In order to validate the proposed architecture, a prototype is developed and tested positively to recognize basic user activities in real time. The system provides a base that can be further extended in many areas of AAL systems, including composite AR

Central monitoring system for ambient assisted living

Smart homes for aged care enable the elderly to stay in their own homes longer. By means of various types of ambient and wearable sensors information is gathered on people living in smart homes for aged care. This information is then processed to determine the activities of daily living (ADL) and provide vital information to carers. Many examples of smart homes for aged care can be found in literature, however, little or no evidence can be found with respect to interoperability of various sensors and devices along with associated functions. One key element with respect to interoperability is the central monitoring system in a smart home. This thesis analyses and presents key functions and requirements of a central monitoring system. The outcomes of this thesis may benefit developers of smart homes for aged care

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

New platform for intelligent context-based distributed information fusion

Tesis por compendio de publicaciones[ES]Durante las últimas décadas, las redes de sensores se han vuelto cada vez más importantes y hoy en día están presentes en prácticamente todos los sectores de nuestra sociedad. Su gran capacidad para adquirir datos y actuar sobre el entorno, puede facilitar la construcción de sistemas sensibles al contexto, que permitan un análisis detallado y flexible de los procesos que ocurren y los servicios que se pueden proporcionar a los usuarios. Esta tesis doctoral se presenta en el formato de “Compendio de Artículos”, de tal forma que las principales características de la arquitectura multi-agente distribuida propuesta para facilitar la interconexión de redes de sensores se presentan en tres artículos bien diferenciados. Se ha planteado una arquitectura modular y ligera para dispositivos limitados computacionalmente, diseñando un mecanismo de comunicación flexible que permite la interacción entre diferentes agentes embebidos, desplegados en dispositivos de tamaño reducido. Se propone un nuevo modelo de agente embebido, como mecanismo de extensión para la plataforma PANGEA. Además, se diseña un nuevo modelo de organización virtual de agentes especializada en la fusión de información. De esta forma, los agentes inteligentes tienen en cuenta las características de las organizaciones existentes en el entorno a la hora de proporcionar servicios. El modelo de fusión de información presenta una arquitectura claramente diferenciada en 4 niveles, siendo capaz de obtener la información proporcionada por las redes de sensores (capas inferiores) para ser integrada con organizaciones virtuales de agentes (capas superiores). El filtrado de señales, minería de datos, sistemas de razonamiento basados en casos y otras técnicas de Inteligencia Artificial han sido aplicadas para la consecución exitosa de esta investigación. Una de las principales innovaciones que pretendo con mi estudio, es investigar acerca de nuevos mecanismos que permitan la adición dinámica de redes de sensores combinando diferentes tecnologías con el propósito final de exponer un conjunto de servicios de usuario de forma distribuida. En este sentido, se propondrá una arquitectura multiagente basada en organizaciones virtuales que gestione de forma autónoma la infraestructura subyacente constituida por el hardware y los diferentes sensores

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

Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

A review of smart homes in healthcare

The technology of Smart Homes (SH), as an instance of ambient assisted living technologies, is designed to assist the homes’ residents accomplishing their daily-living activities and thus having a better quality of life while preserving their privacy. A SH system is usually equipped with a collection of inter-related software and hardware components to monitor the living space by capturing the behaviour of the resident and understanding his activities. By doing so the system can inform about risky situations and take actions on behalf of the resident to his satisfaction. The present survey will address technologies and analysis methods and bring examples of the state of the art research studies in order to provide background for the research community. In particular, the survey will expose infrastructure technologies such as sensors and communication platforms along with artificial intelligence techniques used for modeling and recognizing activities. A brief overview of approaches used to develop Human–Computer interfaces for SH systems is given. The survey also highlights the challenges and research trends in this area

Flexibility Support for Homecare Applications Based on Models and Multi-Agent Technology

In developed countries, public health systems are under pressure due to the increasing percentage of population over 65. In this context, homecare based on ambient intelligence technology seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and help optimize medical resources. Thus, current technological developments make it possible to build complex homecare applications that demand, among others, flexibility mechanisms for being able to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node failure (availability). The solution proposed in this paper copes with these flexibility requirements through the whole life-cycle of the target applications: from design phase to runtime. The proposed domain modeling approach allows medical staff to design customized applications, taking into account the adaptability needs. It also guides software developers during system implementation. The application execution is managed by a multi-agent based middleware, making it possible to meet adaptation requirements, assuring at the same time the availability of the system even for stateful applications.This work was financed in part by the University of the Basque Country (UPV/EHU) under project UFI 11/28, by the Regional Government of the Basque Country under Project IT719-13, and by the MCYT&FEDER under project DPI 2012-37806-C02-01

HABITAT: An IoT Solution for Independent Elderly

In this work, a flexible and extensive digital platform for Smart Homes is presented, exploiting the most advanced technologies of the Internet of Things, such as Radio Frequency Identification, wearable electronics, Wireless Sensor Networks, and Artificial Intelligence. Thus, the main novelty of the paper is the system-level description of the platform flexibility allowing the interoperability of different smart devices. This research was developed within the framework of the operative project HABITAT (Home Assistance Based on the Internet of Things for the Autonomy of Everybody), aiming at developing smart devices to support elderly people both in their own houses and in retirement homes, and embedding them in everyday life objects, thus reducing the expenses for healthcare due to the lower need for personal assistance, and providing a better life quality to the elderly users