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 (HC) interfaces for SH systems is given. The survey also highlights the challenges and research trends in this area.

Dementia refers to a group of chronic conditions that cause the permanent and gradual cognitive decline. Therefore, a Person with Dementia (PwD) requires constant care from various classes of caregivers. The care costs of PwDs bear a tremendous burden on healthcare systems around the world. It is commonly accepted that utilising smart homes (SH), as an instance of ambient assisted living (AAL) technologies, can facilitate the care, and consequently improve the quality of PwDs wellbeing. Nevertheless, most of the existing platforms assume dementia care is a straight application of standard SH technology without accommodating the specific requirements of dementia care. A consequence of this approach is the inadequacy and unacceptability of generic SH systems in the context of dementia care. Contrary to most of the existing SH systems proposed for dementia care, this study considers the specific requirements of PwDs and their care circle in all development steps of an SH. In addition, it investigates how utilising novel design and computing approaches can enhance the quality of SHs for dementia care. To do so, the requirements of dementia care stakeholders are collected, analysed and reflected on in an SH system design. Extensions and adaptation of existing frameworks and technologies are proposed to implement a prototype based on the resulting design. Finally, thorough evaluations and validation of the prototype are carried out. The evaluations by a group of stakeholders show the suitability of the proposed methodology and consequently the resulting prototypes for reducing dementia care difficulties as well as its potential for deployment in the real-world environment.

Background: There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods.Objectives:This study is aimed at diagnosing TB using hybrid machine learning approaches.Materials and Methods: Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm.Results:Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Abstract-In this paper, we present a user-centred approach for designing and developing smart homes for people with dementia. In contrast to most of the existing literature related to dementia, the present approach aims at tailoring the system to the specific needs of dementia using a scenario-based methodology. Scenarios are based on typical dementia symptoms which are collected from research literatures and validated by dementia caregivers. They portray the common behaviour of people with dementia. Because they explain real-world situations, scenarios are meant to generalise the requirements of smart homes for people with dementia. Hence, a top-down approach is followed to summarise the content of the scenarios into the essential requirements for smart home frameworks dedicated to monitoring people with dementia.