There is sufficient evidence proving the impact that negative lifestyle choices have on people’s health and wellness. Changing unhealthy behaviours requires raising people’s self-awareness and also providing healthcare experts with a thorough and continuous description of the user’s conduct. Several monitoring techniques have been proposed in the past to track users’ behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters. This work presents an innovative multimodal context mining framework to inspect and infer human behaviour in a more holistic fashion. The proposed approach extends beyond the state-of-the-art, since it not only explores a sole type of context, but also combines diverse levels of context in an integral manner. Namely, low-level contexts, including activities, emotions and locations, are identified from heterogeneous sensory data through machine learning techniques. Low-level contexts are combined using ontological mechanisms to derive a more abstract representation of the user’s context, here referred to as high-level context. An initial implementation of the proposed framework supporting real-time context identification is also presented. The developed system is evaluated for various realistic scenarios making use of a novel multimodal context open dataset and data on-the-go, demonstrating prominent context-aware capabilities at both low and high levels.

/pdf/human-behavior-analysis-by-means-of-multimodal-context-4x6dd2ny19.pdf

Human Behavior Analysis by Means of Multimodal Context Mining.

Wireless-sensor-network-based home monitoring system for elderly activity behavior involves functional assessment of daily activities. In this paper, we reported a mechanism for estimation of elderly well-being condition based on usage of house-hold appliances connected through various sensing units. We defined two new wellness functions to determine the status of the elderly on performing essential daily activities. The developed system for monitoring and evaluation of essential daily activities was tested at the homes of four different elderly persons living alone and the results are encouraging in determining wellness of the elderly.

Wireless Sensor Network Based Home Monitoring System for Wellness Determination of Elderly

https://hal.archives-ouvertes.fr/hal-01715576/document

A survey on health monitoring systems for health smart homes

Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security a privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work.

https://www.mdpi.com/1424-8220/15/8/20570/pdf

Context Aware Middleware Architectures: Survey and Challenges

The age span of elderly people is increasing and this trend may continue for another two decades. The independent living of elderly people are keen on fulfilling lives, but the self-regulating way of life involve with risks, such as weakening, memory loss or impaired judgment and falls that limit mobility. In particular, the daily home activity involving basic functions like preparing breakfast or food, showering, walking, sleeping, watching television, reading books etc., is a key indicator in determining the performance of elder home activity. An intelligent, robust, less cost, flexible and real time home monitoring unit has been developed to record the basic home activities and respond immediately when there is a change in the regular daily activity of the elder person. This paper will report our recent works on the development of intelligent algorithm to determine the behavior.

Wireless sensors network based safe home to care elderly people: behaviour detection

The growing aging population faces a number of challenges, including rising medical cost, inadequate number of medical doctors and healthcare professionals, as well as higher incidence of misdiagnosis. There is an increasing demand for a better healthcare support for the elderly and one promising solution is the development of a context-aware middleware infrastructure for pervasive health/wellness-care. This allows the accurate and timely delivery of health/medical information among the patients, doctors and healthcare workers through a widespread deployment of wireless sensor networks and mobile devices. In this paper, we present our design and implementation of such a context-aware middleware for pervasive homecare (CAMPH). The middleware offers several key-enabling system services that consist of P2P-based context query processing, context reasoning for activity recognition and context-aware service management. It can be used to support the development and deployment of various homecare services for the elderly such as patient monitoring, location-based emergency response, anomalous daily activity detection, pervasive access to medical data and social networking. We have developed a prototype of the middleware and demonstrated the concept of providing a continuing-care to an elderly with the collaborative interactions spanning multiple physical spaces: person, home, office and clinic. The results of the prototype show that our middleware approach achieves good efficiency of context query processing and good accuracy of activity recognition.

Context-aware middleware for pervasive elderly homecare

Context-aware computing is a key paradigm of ubiquitous computing in which applications automatically adapt their operations to dynamic context data from multiple sources. Managing a number of distributed sources, a middleware that facilitates the development of context-aware applications must provide a uniform view of all these sources to the applications. Local schemas of context data from individual sources need to be matched into a set of global schemas in the middleware, upon which applications can issue context queries to acquire data. In this paper, we study this problem of schema matching for context-aware computing. We propose a multi-criteria algorithm to determine candidate attribute matches between two schemas. The algorithm adaptively adjusts the priorities of different criteria based on previous matching results to improve the efficiency and accuracy of succeeding operations. We further develop an algorithm to categorize a new local schema into one of the global schemas whenever possible via a shared attribute dictionary. Our results based on schemas from real-world websites demonstrate the good matching accuracy achieved by our algorithms.

/pdf/schema-matching-for-context-aware-computing-b7x1ibm2sy.pdf

Schema matching for context-aware computing

Applications in context-aware computing continuously change their operations based on sensor data or services provided by various physical spaces in the real world, such as persons, shops and homes. We propose a gateway framework for physical spaces in this paper, which serves as a middleware platform for context-aware applications to access data from sensor networks deployed in these spaces. The gateway contains a number of components that facilitate the sensor data acquisition, processing and communication in context-aware applications. These include diversified services with plug-in management, a query processing engine with reasoning capability, and the global connection and local detection between gateways.

Gateways of physical spaces in context-aware computing

Context-aware applications can monitor and detect the surrounding Context-aware applications can monitor and detect the surrounding situation changes of context entities, and adapt to these situations automatically. As context-aware applications can reside in mobile entities such as cars and mobile phone, an efficient context data management mechanism is required for mobile context-aware applications. In this paper, we propose a new mechanism to model and represent mobile entities. In addition, we also propose new system services to support mobile applications so that disruptions caused by mobility can be minimized.

/pdf/context-data-management-for-mobile-spaces-4h4jk3chif.pdf

Wenwei Xue

Papers

Context-aware middleware for pervasive elderly homecare

Schema matching for context-aware computing

Gateways of physical spaces in context-aware computing

Context Data Management for Mobile Spaces

Gateways of physical spaces in context-aware computing