A user-guided personalization methodology to facilitate new smart home occupancy.

Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available. In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system's design. Later, the user-guided transfer learning approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results.

ADAPT: Approach to Develop context-Aware solutions for Personalised asthma managemenT.

People with asthma have heterogeneous triggers and symptoms, which they need to be aware of in order to implement the strategies to manage their condition. Context-aware reasoning has the potential to provide the personalisation that is required to address the heterogeneity of asthma by helping people to define the information that is relevant considering the characteristics of their condition and delivering services based on this information. This research work proposes the Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT), whose aim is to facilitate the creation of solutions allowing the required customisation to address the heterogeneity of asthma. ADAPT is the result of the constant interaction with people affected by asthma throughout the research project, which was possible to achieve thanks to the collaboration formed with the Centre for Applied Research of Asthma UK. ADAPT context dimensions facilitate the development of preventive and reactive features that can be configured depending on the characteristics of the person with asthma. The approach also provides support to people not knowing their triggers through case-based reasoning and includes virtual assistant as a complementing technology supporting asthma management. ADAPT is validated by people with asthma, carers and experts in respiratory conditions, who evaluated a mobile application that was built based on the approach.

A Formal Methodology to Design and Deploy Dependable Wireless Sensor Networks.

Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence, their effects need to be properly assessed before deployment, to obtain a good level of expected performance; and during the operation, in order to avoid dangerous unexpected results. In this paper, we propose a methodology that aims at assessing and improving the dependability level of WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of a dependable WSN and a tool ("ADVISES") to simplify its adoption. The tool is applicable to homogeneous WSNs with static routing topologies. It allows the automatic generation of formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime for WSNs where an acceptable percentage of faults can be defined. During the runtime, we can check the behavior of the WSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, as proof-of-concept, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of the WSN at runtime. Although the method scales up to very large WSNs, the applicability of the methodology may be compromised by the state space explosion of the reasoning model, which must be faced by partitioning large topologies into sub-topologies.

Participatory research to design a novel telehealth system to support the night-time needs of people with dementia: NOCTURNAL.

Strategies to support people living with dementia are broad in scope, proposing both pharmacological and non-pharmacological interventions as part of the care pathway. Assistive technologies form part of this offering as both stand-alone devices to support particular tasks and the more complex offering of the "smart home" to underpin ambient assisted living. This paper presents a technology-based system, which expands on the smart home architecture, orientated to support people with daily living. The system, NOCTURNAL, was developed by working directly with people who had dementia, and their carers using qualitative research methods. The research focused primarily on the nighttime needs of people living with dementia in real home settings. Eight people with dementia had the final prototype system installed for a three month evaluation at home. Disturbed sleep patterns, night-time wandering were a focus of this research not only in terms of detection by commercially available technology but also exploring if automated music, light and visual personalized photographs would be soothing to participants during the hours of darkness. The NOCTURNAL platform and associated services was informed by strong user engagement of people with dementia and the service providers who care for them. NOCTURNAL emerged as a holistic service offering a personalised therapeutic aspect with interactive capabilities.

Software and knowledge engineering aspects of smart homes applied to health.

Smart Home technology offers a viable solution to the increasing needs of the elderly, special needs and home based-healthcare populations. The research to date has largely focused on the development of communication technologies, sensor technologies and intelligent user interfaces. We claim that this technological evolution has not been matched with a step of a similar size on the software counterpart. We particularly focus on the software that emphasizes the intelligent aspects of a Smart Home and the difficulties that arise from the computational analysis of the information collected from a Smart Home. The process of translating information into accurate diagnosis when using non-invasive technology is full of challenges, some of which have been considered in the literature to some extent but as yet without clear landmarks.

Temporal reasoning for decision support in medicine.

OBJECTIVE: Handling time-related concepts is essential in medicine. During diagnosis it can make a substantial difference to know the temporal order in which some symptoms occurred or for how long they lasted. During prognosis the potential evolutions of a disease are conceived as a description of events unfolding in time. In therapy planning the different steps of treatment must be applied in a precise order, with a given frequency and for a certain span of time in order to be effective. This article offers a survey on the use of temporal reasoning for decision support-related tasks in medicine. MATERIAL AND METHODS: Key publications of the area, mainly circumscribed to the latest two decades, are reviewed and classified according to three important stages of patient treatment requiring decision support: diagnosis, prognosis and therapy planning/management. Other complementary publications, like those on time-centered information storage and retrieval, are also considered as they provide valuable support to the above mentioned three stages. RESULTS: Key areas are highlighted and used to organize the latest contributions. The survey of previous research is followed by an analysis of what can still be improved and what is needed to make the next generation of decision support systems for medicine more effective. CONCLUSIONS: It can be observed that although the area has been considerably developed, there are still areas where more research is needed to make time-based systems of widespread use in decision support-related areas of medicine. Several suggestions for further exploration are proposed as a result of the survey.