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

The electric vehicle in smart homes: a review and future perspectives

The electric mobility dissemination is forcing the adoption of new technologies and operation paradigms, not only focusing on smart grids, but also on smart homes. In fact, the emerging technologies for smart homes are also altering the conventional grids toward smart grids. By combining the key pillars of electric mobility and smart homes, this paper characterizes the paradigms of the electric vehicle (EV) in smart homes, presenting a review about the state of the art and establishing a relation with future perspectives. Since the smart home must be prepared to deal with the necessities of the EV, the analysis of both on board and off board battery charging systems are considered in the paper. Moreover, the in-clusion of renewable energy sources, energy storage systems, and dc electrical appliances in smart homes towards sustainability is also considered in this paper, but framed in the perspective of an EV off board battery charging system. As a pertinent contribution, this paper offers future perspectives for the EV in smart homes, including the possibility of ac, dc, and hybrid smart homes. Covering all of these aspects, exemplificative and key results are presented based on numerical simulations and experimental results obtained with a proof of concept prototype.FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019. This work has been supported by the FCT Project newERA4GRIDs PTDC/EEI-EEE/30283/2017, and by the FCT Project DAIPESEV PTDC/EEI-EEE/30382/2017. Tiago Sousa is supported by the doctoral scholarship SFRH/BD/134353/2017 granted by FC

The role of the electric vehicle in smart homes: Assessment and future perspectives

The wide spreading of electric mobility is imposing the application of new technologies of hardware and software for supporting new operation paradigms, not only in the perspective of improving smart grids, but also each time more in the perspective of boosting the preponderance of smart homes. Concretely, nowadays it is clear that the emergent technologies for smart homes, targeting power quality and a more efficient power management, are also altering the conventional electrical power grids toward smart grids. In this panorama, by relating the strategic pillars of electric mobility and smart homes, this paper has as main objective the characterization of the role of the electric vehicle (EV) in smart homes, presenting a broad assessment based on the state of the art, as well as creating a link with upcoming advanced operations. From the smart home point of view, since it should be equipped to deal with the requirements of the EV, the assessment of both on-board and off-board EV battery charging systems are considered along the paper. Furthermore, the presence of technologies such as energy storage systems, renewable energy sources and dc electrical appliances in smart homes towards sustainability is also reflected in this paper, but framed from the point of view of an off-board EV battery charging system, since it is more convenient for enabling the interface of these mentioned technologies. Looking the paper as a whole, a relevant contribution is the discussion of future operations for the EV in smart homes, also envisioning the opportunity for ac, dc, or hybrid power grids. Illustrative and strategic results are shown, covering all these features with specific details, not only based on numerical simulations, but also based on experimental results, which were obtained with a proof-of-concept laboratory prototype.FCT -Fundação para a Ciência e a Tecnologia(DAIPESEV PTDC/EEI-EEE/30382/2017

Two-Stream RNN/CNN for Action Recognition in 3D Videos

The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particular related to 3D video, the methodologies to process the data are still subject to research. We demonstrate superior results by a system which combines recurrent neural networks with convolutional neural networks in a voting approach. The gated-recurrent-unit-based neural networks are particularly well-suited to distinguish actions based on long-term information from optical tracking data; the 3D-CNNs focus more on detailed, recent information from video data. The resulting features are merged in an SVM which then classifies the movement. In this architecture, our method improves recognition rates of state-of-the-art methods by 14% on standard data sets.Comment: Published in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

Robust and Lightweight Mutual Authentication Scheme in Distributed Smart Environments

In the smart environments several smart devices are continuously working together to make individuals' lives more comfortable. Few of the examples are smart homes, smart buildings, smart airports, etc. These environments consist of many resource constrained heterogeneous entities which are interconnected, controlled, monitored and analyzed through the Internet. One of the most challenging tasks in a distributed smart environment is how to provide robust security to the resource constraint Internet-enabled devices. However, an authentication can play a major role ensuring that only authorized devices are being connected to the distributed smart environment applications. In this paper, we present a robust and lightweight mutual-authentication scheme (RLMA) for protecting distributed smart environments from unauthorized abuses. The proposed scheme uses implicit certificates and enables mutual authentication and key agreement between the smart devices in a smart environment. The RLMA not only resists to various attacks but it also achieves efficiency by reducing the computation and communication complexities. Moreover, both security analysis and performance evaluation prove the effectiveness of RLMA as compared to the state of the art schemes

Ten Quick Tips for Using a Raspberry Pi

Much of biology (and, indeed, all of science) is becoming increasingly computational. We tend to think of this in regards to algorithmic approaches and software tools, as well as increased computing power. There has also been a shift towards slicker, packaged solutions--which mirrors everyday life, from smart phones to smart homes. As a result, it's all too easy to be detached from the fundamental elements that power these changes, and to see solutions as "black boxes". The major goal of this piece is to use the example of the Raspberry Pi--a small, general-purpose computer--as the central component in a highly developed ecosystem that brings together elements like external hardware, sensors and controllers, state-of-the-art programming practices, and basic electronics and physics, all in an approachable and useful way. External devices and inputs are easily connected to the Pi, and it can, in turn, control attached devices very simply. So whether you want to use it to manage laboratory equipment, sample the environment, teach bioinformatics, control your home security or make a model lunar lander, it's all built from the same basic principles. To quote Richard Feynman, "What I cannot create, I do not understand".Comment: 12 pages, 2 figure

Smart Built Environment Including Smart Home, Smart Building and Smart City: Definitions and Applied Technologies

Technology, particularly over the past decades, has affected the cities and their components, such as building sectors. Consequently, smart building that has currently utilized various technologies which is incorporated into buildings is the core of the present chapter. It provides a comprehensive overview on smart cities, smart buildings and smart home to address what systems and technologies have been incorporated so far. The aim is to review the smart concepts in built environment with the main focus on smart cities, smart buildings, and smart homes. State-of-the-art and current practices in smart buildings were also reviewed to enlighten a set of directions for future studies. The Chapter is primarily focuses on 51 articles in smart buildings/homes, as per collected from various datasets. It represents a summary of systems utilized and incorporared into smart buildings and homes over the past decade (2010–2020). Additional to different features of smart buildings and homes, is the discussion around various fields and system performances currently utilized in smart buildings/homes. Limitations and future trends and directions is also discussed. In total, such building/home systems were categorized into 6 groups, including: security systems, healthcare systems, energy management systems, building/home management systems, automation systems, and activity/movement recognition systems. Furthermore, there are a number of surveys which investigated the user’s acceptance and adoption of the new smart systems in homes and buildings, as presented and summarized thereafter in Tables. The present Chapter is a contribution to a better understanding of the functions and performances of such buildings/homes for further implementation and enhancement so that varying demands of smart citizens are fulfilled and eventually contribute to the development of smart cities