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Featured Application: This work can be widely used in advanced intelligent systems, including smart city, smart transportation and smart home, etc. Video description plays an important role in the field of intelligent imaging technology. Attention perception mechanisms are extensively applied in video description models based on deep learning. Most existing models use a temporal-spatial attention mechanism to enhance the accuracy of models. Temporal attention mechanisms can obtain the global features of a video, whereas spatial attention mechanisms obtain local features. Nevertheless, because each channel of the convolutional neural network (CNN) feature maps has certain spatial semantic information, it is insufficient to merely divide the CNN features into regions and then apply a spatial attention mechanism. In this paper, we propose a temporal-spatial and channel attention mechanism that enables the model to take advantage of various video features and ensures the consistency of visual features between sentence descriptions to enhance the effect of the model. Meanwhile, in order to prove the effectiveness of the attention mechanism, this paper proposes a video visualization model based on the video description. Experimental results show that, our model has achieved good performance on the Microsoft Video Description (MSVD) dataset and a certain improvement on the Microsoft Research-Video to Text (MSR-VTT) dataset. [ABSTRACT FROM AUTHOR]

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artficial neural network (ANN) approaches to help usees interact wiith computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution. [ABSTRACT FROM AUTHOR]

Remote control his smart home from his mobile device is highly desirable for a mobile user. But, the sensor devices and the user mobile device communicate over an insecure communication channel. Therefore, various attacks are possible, such as impersonation attack, privileged-insider attack, mobile device stolen attack, and the denial of service attack. In this case, an illegal user may gain access to the data sent by the smart devices. In the literature, most of the existing schemes for the remote user authentication are not secure enough with respect to the aforementioned attacks. In addition, they are not enough lightweight at the sensor device side. Therefore, there is a need to design a new secure and lightweight remote user authentication scheme, where only the authorized users may have access to the home sensor devices. So, in this paper, we propose a new secure and lightweight remote user authentication scheme for a smart home environment. For the derivation of a robust session key, we propose to use Elliptic Curve Cryptography. The solution is lightweight for resource-constrained devices with limited resources as the gateway node will assist in deriving the session key to the sensor device. The security of the proposed solution is proved using a formal security evaluation via the Scyther tool. Also, a performance evaluation is performed to show the effectiveness of our solution. [ABSTRACT FROM AUTHOR]

In this paper, we formulate joint optimization of microgrid configuration and energy consumption scheduling as a leader-follower Stackelberg game to model the coordination between two rational decision makers of microgrid configuration and energy consumption scheduling. The microgrid configuration decision, as the leader, is modeled as an upper-level optimization problem for optimal installed numbers of wind turbines, photovoltaic (PV) units, micro-turbines and batteries. The energy consumption scheduling, as the follower, is modeled as a lower-level optimization problem, which responds to decisions of the upper level in order to determine the optimal appliance scheduling. A bi-level nonlinear programming model is formulated for the Stackelberg game. To solve this optimization model, four bi-level hierarchical algorithms with the combination of different evolutionary algorithms are implemented and compared. A case study of microgrid configuration of smart building is employed to demonstrate the feasibility and advantage of the proposed game-theoretic model. [ABSTRACT FROM AUTHOR]

ImAtHome is an iOS application for smart home configuration and management built over Apple HomeKit, a framework for communicating with and controlling home automation accessories. This paper describes the design and development of the visual interaction language made available in ImAtHome for empowering end users, without programming skills, to create event-condition-action rules that control home behavior. It can be regarded as an alternative approach to traditional trigger-action programming interfaces, where the user must define such rules by means of “if-then” constructs. Last but not least, attention has been put to make the interaction style as much coherent as possible with other iOS applications. The paper finally presents a user experiment, carried out with 30 participants according to a between-subject protocol, to evaluate the usability of ImAtHome and compare it with the official app for home automation recently released by Apple. [ABSTRACT FROM AUTHOR]

A Pervasive-computing-enriched smart home environment, which contains many embedded and tiny intelligent devices and sensors coordinated by service management mechanisms, is capable of anticipating intentions of occupants and providing appropriate services accordingly. Although there are a wealth of research achievements in recent years, the degree of market acceptance is still low. The main reason is that most of the devices and services in such environments depend on particular platform or technology, making it hard to develop an application by composing the devices or services. Meanwhile, the concept of Web of Things (WoT) is becoming popular recently. Based on WoT, the developers can build applications based on popular web tools or technologies. Consequently, the objective of this paper is to propose a set of novel WoT-driven plug-and-play service management schemes for a smart home called Resource-Oriented Service Administration (ROSA).We have implemented an application prototype, and experiments are performed to show the effectiveness of the proposed approach. The results of this research can be a foundation for realizing the vision of "end user programmable smart environments". [ABSTRACT FROM AUTHOR]

Fuel poverty is a critical issue for a globally ageing population. Longer heating/cooling requirements combine with declining incomes to create a problem in need of urgent attention. One solution is to deploy technology to help elderly users feel informed about their energy use, and empowered to take steps to make it more cost effective and efficient. This study subjects a broad cross section of energy monitoring and home automation products to a formal ergonomic analysis. A high level task analysis was used to guide a product walk through, and a toolkit approach was used thereafter to drive out further insights. The findings reveal a number of serious usability issues which prevent these products from successfully accessing an important target demographic and associated energy saving and fuel poverty outcomes. Design principles and examples are distilled from the research to enable practitioners to translate the underlying research into high quality design-engineering solutions. [ABSTRACT FROM AUTHOR]

If desires steer people, shape products, and define the zeitgeist, then why aren't designers taking them more seriously? An exploration of the thermostat, the temperature of 2017, and a methodology that can make us better. [ABSTRACT FROM AUTHOR]

Smart home is an emerging area that opens up a diverse set of downstream applications, such as dynamic pricing and demand response techniques, whose goals are typically to lower power consumption while providing comfortable and convenient services. Smart home has been extensively studied, and shown to be beneficial in people's real lives. Although useful, typical smart home platforms work at the "servant" level -- highly dependent on user inputs with no predictions of human demands -- which, if well addressed, would significantly widen their applicability. In this article, we propose a human-centric smart home energy management system (SHE) that works at the "butler" level. The system integrates ubiquitous sensing data from the physical and cyber spaces to discover the patterns of power usage and cognitively understand the behaviors of human beings. The relationship between them is established to dynamically infer users' demands for electricity, and then the optimal scheduling of the home energy system is triggered to respond to both the users' demands and electricity rates. Based on the novel framework, our SHE system provides intelligent services to satisfy the requirements of users as a butler -- aiming not only to save the electricity cost or reduce the peak load, but also to predict users' demands and managing "servants." [ABSTRACT FROM AUTHOR]

This article proposes to integrate two entities, the Internet of Things and a cognitive dynamic system (CDS), and studies a smart home scenario as the application of interest. As a people-centric IoT, the smart home aims to enhance the intelligence level of the living environment and improve the quality of human life. Cognition, the distinct principles of which are perception?action cycle, memory, attention, intelligence, and language, can play a key role to pave the way for building truly smart homes. With cognition as its foundation, the engineering paradigm of CDS provides step-by-step guidelines for systematic development of smart homes. Hence, CDS can significantly contribute to the interactive IoT ecosystem. [ABSTRACT FROM AUTHOR]

The recent trend of ubiquitous access to embedded physical devices over the Internet as well as increasing penetration of wireless protocols such as ZigBee has raised attention to smart homes. These systems consist of sensors, devices and smart appliances that can be monitored and controlled remotely by human users and cloud services. However, the lack of a de facto communication standard for smart homes creates a barrier against the interoperability of devices from different vendors. We address this challenge by proposing a holistic and extensible software architecture that seamlessly integrates heterogeneous protocol- and vendor-specific devices and services, while making these services securely available over the Internet. Our architecture is developed on top of the Open Services Gateway initiative framework and incorporates a semantic model of a smart home system. As a result, we come closer to semantic interoperability – the ability to integrate new applications and drivers into the deployed system during runtime. Furthermore, we integrate a new access control model for specific smart home scenarios. As a proof of our concept, we demonstrate the seamless semantic discovery of home devices at runtime by integrating several protocols including X10, Insteon, ZigBee and Universal Plug-and-Play into a real test. Using smart phones and cloud services together with our home gateway implementation, we further demonstrate the ease of integration of new applications and drivers. We show the scalability of our solution by evaluating the execution time for different numbers of devices and configurations of the semantic device discovery. [ABSTRACT FROM PUBLISHER]

In this paper, a novel distributed iterative adaptive dynamic programming (ADP) method is developed to solve the multibattery optimal coordination control problems for home energy management systems. According to system transformations, the multi-input optimal control problem is transformed into a single-input optimal control problem, where all the batteries are implemented at their worst performance. Next, based on the worst-performance optimal control law, an effective distributed iterative ADP algorithm is developed, where, in each iteration, only a single-input optimization problem is implemented. Convergence properties of the distributed iterative ADP algorithm are developed to show that the iterative performance index function converges to the optimum. Finally, numerical analysis is given to illustrate the performance of the developed algorithm. [ABSTRACT FROM PUBLISHER]

Scenarios are used as tools in the development of smart home platforms and middleware for aging-in-place. In order to be effective, a set of scenarios that address all required functionalities are needed. The health condition of the majority of an aging population has been described by medical tools, such as WHO's International Classification of Functioning, Disability and Health (ICF) and local health profiles. However, this has not yet been fully implemented in the development of smart-homes. In this study we develop a Public Health Methodology (PHM) in which we use public health resources for the generation of scenarios. Specific user characteristics are taken from the medical tools. Common daily user activities were supplied by research into common activities as practiced by Dutch end-users. A functional scenario is generated by combining the user characteristics and user activities with the product goal, the physical and non-physical environment, and the product to be developed. Using this method a set of 10 scenarios covered all requirements. The scenarios were used in virtual tests for the validation of smart-home platforms. PHM is a promising tool in the development of smart environments that are more easily adopted by aging populations. [ABSTRACT FROM AUTHOR]

In the recent past Smart Environments, and in particular Smart Homes, have attracted the attention of many researchers and industrial vendors. In such environments, according to the Ambient Intelligence paradigm, heterogeneous devices may operate collectively using context information and intelligence that is usually hidden in the home networks. The networks of ZigBee devices play an important role in this scenario. However they require an easier interaction model with IP-based networks. This work presents an open source platform that seamlessly integrates ZigBee devices with applications running on smart phones and other connected devices available at home. It can be deployed on low-cost devices, such as Plug-PC, and it exploits the OSGi execution environment to discover devices and to notify the smart home of new available services. [ABSTRACT FROM AUTHOR]

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment's reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy. [ABSTRACT FROM AUTHOR]

Nowadays, home automation systems which directly affect people's life styles are designed. The studies carried out in the field of smart home aim to satisfy person's needs easily. Smart home models are only satisfying healthy people's needs. However, this application is inadequate for disabled, diseased and old people. In this study, by using Kinect technology, it is aimed to design a home automation which will render disabled people's daily life more safely and practically during their stay at home. The disabled people in performed study have been categorized as old, diseased and having physical handicap. This study has been carried out by using Kinect technology. All in all, by means of performed study it is aimed to help the disabled people do their daily routine activities more easily. However, it is thought that it will affect disabled people's life quality in a positive way. [ABSTRACT FROM AUTHOR]

The article focuses on the implementation of smart technologies in consumer electronic goods in order to prevent appliances from getting hacked. It discusses ratting that is a phenomenon of hacking personal computer and controlling the device's webcam and mentions that the incidence has increased due to the development of smart televisions that incorporate webcams. It mentions two home automation gateways, the Minos Vera Light and the Insteon Hub.

Smart home technologies are getting considerable attentions nowadays for better care of the residents, especially the elderly. One of the key technologies is the human activity recognition (HAR) system which automatically recognizes various indoor activities of a resident and reacts upon the needs of the resident, known as a proactive system. In this work, we propose a novel HAR system that utilizes depth imaging. Our HAR system utilizes local binary patterns (LBP) as local activity features from depth silhouettes and recognizes human activities via Hidden Markov Model (HMM). In our methodology, first LBP features were extracted from depth human body silhouettes from each frame of a video containing human activity. Then, principal component analysis (PCA) and linear discriminant analysis (LDA) were performed over the LBP features to obtain condensed features. Applying these features, each activity HMM was trained. Finally, HAR was performed with the trained HMMs. Our approach shows superior recognition performance over the traditional silhouette feature-based approaches. The system should be practical to be used for smart homes. [ABSTRACT FROM AUTHOR]