Smart Home Installations Research Articles

Inter-Vendor Intra-Operation in Smart Home using Wi-Fi for Capacious Control and Remote Operation

Abstract: Smart homes have been gaining a lot of momentum lately and people are rushing towards it, because of the ease of control, monitor and security that they offer. Although smart home installation has also become quite easier nowadays, but still pertains to be difficult choice to many, due to the exclusivity of the vendors or the inability of some vendors to support the Zigbee connection. Though Zigbee allows users to assemble their own choice of devices and consumption of low power, as long as the devices support Zigbee interface, but Zigbee still remains sort of unsafe and less capacious (expandable). Inter-vendor Intraoperability using Wi-Fi can provide easier installation and control options to the users and also increase the scalability of the smart homes, allowing the users themselves to choose from the devices that they want to install in their home, and providing them a common platform of control in form of a mobile application, from anywhere wherever the Wi-Fi or mobile internet provided. Also, the data transfer would be more secure and encrypted over Wi-Fi, faster and more expandable, even across the countries. In the project, we explore the interconnection of smart home devices from various vendor together with a Zigbee Bluetooth interface with a mobile application for control, enabling the smart homes more accessible by cost cutting.

Machine learning approaches for non-intrusive home absence detection based on appliance electrical use

Home absence detection is an emerging field on smart home installations. Identifying whether or not the residents of the house are present, is important in numerous scenarios. Possible scenarios include but are not limited to: elderly people living alone, people suffering from dementia, home quarantine. The majority of published papers focus on either pressure/door sensors or cameras in order to detect outing events. Although the aforementioned approaches provide solid results, they are intrusive and require modifications for sensor placement. In our work, appliance electrical use is investigated as a means for detecting the presence or absence of residents. The energy use is the result of power disaggregation, a non intrusive/non invasive sensing method. Since a dataset providing energy data and ground truth for home absence is not available, artificial outing events were introduced on the UK-DALE dataset, a well known dataset for Non Intrusive Load Monitoring (NILM). Several machine learning algorithms were evaluated using the generated dataset. Benchmark results have shown that home absence detection using appliance power consumption is feasible.

Multilabel Classification Methods for Human Activity Recognition: A Comparison of Algorithms.

As the world’s population is aging, and since access to ambient sensors has become easier over the past years, activity recognition in smart home installations has gained increased scientific interest. The majority of published papers in the literature focus on single-resident activity recognition. While this is an important area, especially when focusing on elderly people living alone, multi-resident activity recognition has potentially more applications in smart homes. Activity recognition for multiple residents acting concurrently can be treated as a multilabel classification problem (MLC). In this study, an experimental comparison between different MLC algorithms is attempted. Three different techniques were implemented: RAkEL, classifier chains, and binary relevance. These methods are evaluated using the ARAS and CASAS public datasets. Results obtained from experiments have shown that using MLC can recognize activities performed by multiple people with high accuracy. While RAkEL had the best performance, the rest of the methods had on-par results.

Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set.

Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being. GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols. In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way. With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation. This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices. The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices.

Effects of a computer-based learning environment that teaches older adults how to install a smart home system

In this study, we examined the teaching effectiveness of three strategies (trial-and-error, textbook, and combination) via a computer-based learning environment (CBLE) that teaches smart-home installation (SHiB). One hundred and twenty-five participants were randomly assigned to one of the strategies and tested with SHiB CBLE. Findings revealed that participants in the combination condition performed significantly better than those in the textbook (control) group with medium effect-size (g = 0.70). Senior participants in the trial-and-error group performed significantly better than those in the control condition with large effect-size (g = 0.89). Younger participants in the combination condition performed significantly better than those in the control condition with medium effect-size (g = 0.70). Results suggest that the teaching strategies had differential effects due to age groups.

Evaluation of an assisted‐living smart home for someone with dementia

This paper presents the results of a study evaluating a complete autonomous smart home installation in an apartment in a care home, and the impact it had on the behaviour and independence of someone with quite severe dementia (Mini Mental State Examination, or MMSE, of 10). It describes the technology that has been evolved for this purpose, and how the apartment was configured. The evaluation compared the behaviour of the resident before and after the switching on of a wide range of autonomous support technology, by analysing the logged sensor data, through a questionnaire‐based outcome measure, and through transcribed interviews. The technology enabled the client to retain a lot of independence. It helped him to regain urinary continence, improved his sleep from around 3.5 hours per night to 5.5, and halved the number of night‐time wanderings. The paper concludes with a series of recommendations for future work in this area.

The design of smart homes for people with dementia—user-interface aspects

This paper reports on the user requirements analysis, design and evaluation of smart home solutions for people with dementia. In order to be appropriate for people with dementia, smart home technologies should keep interaction with users to a minimum. In the work presented in this paper, discussions with carers, as well as a more formal user-survey, provided a good understanding of the issues that are faced by this group, and useful indications of potential design solutions. This preliminary survey work led to a design approach that used carer emulation, familiarity of appearance, incorporation of verbal prompts and reminders, and careful user-monitoring, to achieve effective devices. This design approach is illustrated through several examples of specific designs. Evaluations of stand-alone systems were carried out prior to smart home installation, and illustrated the complex interface that exists between assistive technology and people with dementia.