13,047 research outputs found
Integration of Legacy Appliances into Home Energy Management Systems
The progressive installation of renewable energy sources requires the
coordination of energy consuming devices. At consumer level, this coordination
can be done by a home energy management system (HEMS). Interoperability issues
need to be solved among smart appliances as well as between smart and
non-smart, i.e., legacy devices. We expect current standardization efforts to
soon provide technologies to design smart appliances in order to cope with the
current interoperability issues. Nevertheless, common electrical devices affect
energy consumption significantly and therefore deserve consideration within
energy management applications. This paper discusses the integration of smart
and legacy devices into a generic system architecture and, subsequently,
elaborates the requirements and components which are necessary to realize such
an architecture including an application of load detection for the
identification of running loads and their integration into existing HEM
systems. We assess the feasibility of such an approach with a case study based
on a measurement campaign on real households. We show how the information of
detected appliances can be extracted in order to create device profiles
allowing for their integration and management within a HEMS
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
Occupant Privacy Perception, Awareness, and Preferences in Smart Office Environments
Building management systems tout numerous benefits, such as energy efficiency
and occupant comfort but rely on vast amounts of data from various sensors.
Advancements in machine learning algorithms make it possible to extract
personal information about occupants and their activities beyond the intended
design of a non-intrusive sensor. However, occupants are not informed of data
collection and possess different privacy preferences and thresholds for privacy
loss. While privacy perceptions and preferences are most understood in smart
homes, limited studies have evaluated these factors in smart office buildings,
where there are more users and different privacy risks. To better understand
occupants' perceptions and privacy preferences, we conducted twenty-four
semi-structured interviews between April 2022 and May 2022 on occupants of a
smart office building. We found that data modality features and personal
features contribute to people's privacy preferences. The features of the
collected modality define data modality features -- spatial, security, and
temporal context. In contrast, personal features consist of one's awareness of
data modality features and data inferences, definitions of privacy and
security, and the available rewards and utility. Our proposed model of people's
privacy preferences in smart office buildings helps design more effective
measures to improve people's privacy
User Perceptions of Smart Home IoT Privacy
Smart home Internet of Things (IoT) devices are rapidly increasing in
popularity, with more households including Internet-connected devices that
continuously monitor user activities. In this study, we conduct eleven
semi-structured interviews with smart home owners, investigating their reasons
for purchasing IoT devices, perceptions of smart home privacy risks, and
actions taken to protect their privacy from those external to the home who
create, manage, track, or regulate IoT devices and/or their data. We note
several recurring themes. First, users' desires for convenience and
connectedness dictate their privacy-related behaviors for dealing with external
entities, such as device manufacturers, Internet Service Providers,
governments, and advertisers. Second, user opinions about external entities
collecting smart home data depend on perceived benefit from these entities.
Third, users trust IoT device manufacturers to protect their privacy but do not
verify that these protections are in place. Fourth, users are unaware of
privacy risks from inference algorithms operating on data from non-audio/visual
devices. These findings motivate several recommendations for device designers,
researchers, and industry standards to better match device privacy features to
the expectations and preferences of smart home owners.Comment: 20 pages, 1 tabl
Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments
In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog
Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People
This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.This research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants
to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system
integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría
de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación
y Universidades
Smart City Ontologies and Their Applications: A Systematic Literature Review
The increasing interconnections of city services, the explosion of available urban data, and the need for multidisciplinary analysis and decision making for city sustainability require new technological solutions to cope with such complexity. Ontologies have become viable and effective tools to practitioners for developing applications requiring data and process interoperability, big data management, and automated reasoning on knowledge. We investigate how and to what extent ontologies have been used to support smart city services and we provide a comprehensive reference on what problems have been addressed and what has been achieved so far with ontology-based applications. To this purpose, we conducted a systematic literature review finalized to presenting the ontologies, and the methods and technological systems where ontologies play a relevant role in shaping current smart cities. Based on the result of the review process, we also propose a classification of the sub-domains of the city addressed by the ontologies we found, and the research issues that have been considered so far by the scientific community. We highlight those for which semantic technologies have been mostly demonstrated to be effective to enhance the smart city concept and, finally, discuss in more details about some open problems
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