Showing papers in "International Journal of Smart Home in 2015"
TL;DR: An iBeacon-based indoor positioning system for hospitals based on the three-layer architecture of Internet of things to have message-push-service through clients and the shortest distance algorithm Floyd is used to recommend the nearest department or ward to patients.
Abstract: How to help patients find their departments or wards is an issue that needs to be solved by hospitals urgently. This paper presents an iBeacon-based indoor positioning system for hospitals. It firstly analyzes the advantages of iBeacon compared with the common indoor positioning technologies; then designs the indoor positioning system for hospitals based on the three-layer architecture of Internet of things to have message-push-service through clients. Finally, the shortest distance algorithm Floyd is used to recommend the nearest department or ward to patients. Shown as result of the experiment, indoor positioning for hospitals can be realized by the system.
65 citations
TL;DR: The background of Internet of Things (IoT) and its application to u-healthcare is discussed and the idea of framework of IoT which works for u- healthcare is presented.
Abstract: The IoT plays an important role in healthcare applications, from managing chronic diseases at one end of the spectrum to preventing disease at the other. IoT devices can be used to enable remote health monitoring and emergency notification systems. IoT aims to provide means to access and control all kinds of ubiquitous and uniquely identifiable devices, facilities and assets. In this paper we discussed the background of Internet of Things (IoT) and its application to u-healthcare. This also presents the idea of framework of IoT which works for u-healthcare.
51 citations
TL;DR: Elderly, handicapped patients, and people with disabilities who have problems with locomotion difficulty can benefit from this smart home to totally operate, with high performance, all appliances and devices from anywhere in the house.
Abstract: Smart home automation system is increasingly used due to the wide manufacturer brands and various available technologies. From a social point of view, residents are admitted to smart homes for comfort, luxury, improving quality of live, and for providing security against intrusion and burglars. Secondly, home automation is achieved using a single controller, monitoring and the controlling many interconnected appliances such as lights, power plugs, HVAC system, humidity and temperature sensors, gas, smoke and fire detectors, audio, video and home theater as well as security and emergency systems. Smart homes are cheap, low-power, cost effective, efficient, and realize the automation of a variety of domestic appliances using user-friendly interface as remote control or any other handheld devices. Elderly, handicapped patients, and people with disabilities who have problems with locomotion difficulty can benefit from this smart home to totally operate, with high performance, all appliances and devices from anywhere in the house. When a resident is living alone, the ubiquitous access becomes very important and it is realized by using XBee transceivers that maintain RF wireless communication between the remote control and the master control panel board.
49 citations
TL;DR: This paper presents a low-cost and flexible solution to control and monitor home appliances using Smart Plug devices, a power switch which can be accessed via WiFi connection that integrates two temp sensors, a current sensor and an IRemitter.
Abstract: This paper presents a low-cost and flexible solution to control and monitor home appliances using Smart Plug devices. The Smart Plug is a power switch which can be accessed via WiFi connection. It integrates two temp sensors, a current sensor and an IRemitter. Users can plug devices into the Smart Plug to remotely switch power on/off, get information of device’s power consumption and ambient temperature, and eventually control the nearby devices using the integrated IR-emitter. There are two ways to access Smart Plug, that is, either connecting it directly in WiFi Ad-Hoc mode or connecting it with a router in WiFi infrastructure mode and accessing online with IP-connectivity. The paper utilizes RESTful based Web services in which the overall system architecture is client/server model and the Web client uses JavaScript and Ajax to transfer data. An Android-based Smartphone application employs standard operations such as Get and Post requests that return responses to communicate between the remote user and the Web server. Depending on the use cases, users can use Smart Plug as lighting switch, timing switch, infrared controller and temp regulator.
43 citations
TL;DR: In this paper, the authors proposed a system that uses a depth camera to capture the figure of a user standing in front of a large display screen, coordinated to his or her body.
Abstract: Digital technology innovations have led to significant changes in everyday life, made possible by the widespread use of computers and continuous developments in information technology (IT). Based on the utilization of systems applying 3D(three-dimensional) technology, as well as virtual and augmented reality techniques, IT has become the basis for a new fashion industry model, featuring consumer-centered service and production methods. Because of rising wages and production costs, the fashion industry’s international market power has been significantly weakened in recent years. To overcome this situation, new markets must be established by building a new knowledge and technology-intensive fashion industry. Development of virtual clothing simulation software, which has played an important role in the fashion industry’s IT-based digitalization, has led to continuous technological improvements for systems that can virtually adapt existing 2D(two-dimensional) design work to 3D design work. Such adaptions have greatly influenced the fashion industry by increasing profits. Both here and abroad, studies have been conducted to support the development of consumercentered, high value-added clothing and fashion products by employing digital technology. This study proposes a system that uses a depth camera to capture the figure of a user standing in front of a large display screen. The display can show fashion concepts and various outfits to the user, coordinated to his or her body. Thus, a “magic mirror” effect is produced. Magic mirror-based fashion apparel simulation can support total fashion coordination for accessories and outfits automatically, and does not require computer or fashion expertise. This system can provide convenience for users by assuming the role of a professional fashion coordinator giving an appearance presentation. It can also be widely used to support a customized method for clothes shopping.
41 citations
TL;DR: An Internet of Things-based intelligent fire emergency response system that can control directional guidance intelligently according to the time and location of a disaster and the design of an integrated control system using wireless sensor networks to address the problems with existingFire emergency response systems in times of fire or building collapse are suggested.
Abstract: Modern buildings around the world have become complex and augmented. Given the structural characteristics of modern buildings, quick evacuation using emergency exits or evacuee guidance markers during blackouts due to fire, building collapse, earthquakes, or aging of buildings need to be possible. This paper suggests an Internet of Things(IoT)-based intelligent fire emergency response system that can control directional guidance intelligently according to the time and location of a disaster and the design of an integrated control system using wireless sensor networks to address the problems with existing fire emergency response systems in times of fire or building collapse.
34 citations
TL;DR: Two effective learning algorithms: Back propagation Neural Network, and Temporal Differential class of reinforcement learning are used for prediction and adaptation respectively, which indicates better adaptation for context-aware service due to the low error rate.
Abstract: Context-awareness is the key element for building a smart home environment. The goal of a smart home is to predict the demand of home users and proactively provides the proper services by considering the user’s context information. Several methods are used in context-aware system to provide services. Machine learning based approaches are capable to make better prediction and adaptation than others. In this paper, we present machine learning based context-aware system which can provide service according to the trained model. Two effective learning algorithms: Back propagation Neural Network, and Temporal Differential (TD) class of reinforcement learning are used for prediction and adaptation respectively. This approach indicates better adaptation for context-aware service due to the low error rate.
29 citations
TL;DR: In this article, the difference between male and female users in the acceptance of mobile SNS was investigated and the analysis result showed that gender moderates the effects of social influence on behavioral intention and Facilitating Conditions on use behavior.
Abstract: With the proliferation of Mobile SNS, understanding users' acceptance behavior has become an important issue for researchers and service providers. Relevant studies have focused on the relationship of different influence factors of acceptance, little research have been conducted to investigate the moderating effects of gender. This paper incorporates perceived enjoyment with UTAUT theory as research base model and investigates the difference between male and female users in the acceptance of Mobile SNS. Data collected from 359 respondents in China is analyzed. The analysis result shows that gender moderates the effects of Social Influence on Behavioral Intention and Facilitating Conditions on Use Behavior.
23 citations
TL;DR: This paper proposes a very efficient smart card based authentication scheme, solely using xor and hash operations, which is resistant against dishonest users and servers, and anonymity and untraceability of user's behaviour is avoided.
Abstract: Multi-server authentication schemes are very practical from a user point of view, since they allow a user to get access to different services on different servers with one single registration. Smart card based approaches lead to more secure systems because they offer two-factor authentication, based on the strict combination of user's password and the possession of the smart card. In this paper, we first show that a previously proposed scheme does not satisfy perfect forward secrecy and is not resistant against insider attacks. Next, we propose a very efficient smart card based authentication scheme, solely using xor and hash operations, which is resistant against dishonest users and servers. Also anonymity and untraceability of user's behaviour is avoided.
23 citations
TL;DR: This paper proposes an overall framework of intelligent transportation, and proposes a Support Vector Machine (SVM) modified by Ant Colony Algorithm (ACA) as the solution for traffic accident detection in the IoT platform.
Abstract: Recent years, the transportation efficiency and related issues have become one of the main focuses of the global world. Along this line, intelligent transportation systems (ITS) based on Internet of Things (IoT) has become a common solution to may transportation problems, such as traffic prediction, road status evaluation, traffic accident detection, etc. In this paper, we focus on the traffic accident detection in the IoT platform. Specifically, we propose an overall framework of intelligent transportation. Then, for traffic accident detection, we proposed a Support Vector Machine (SVM) modified by Ant Colony Algorithm (ACA) as the solution. We conduct experiments on real world traffic data to predict 7 types of traffic accidents. The results show that our proposed method is effective and efficient.
22 citations
TL;DR: A review of the common techniques used for high step-down dc-dc voltage conversion is presented in this paper, where the main circuit structure of each topology is given and their features and limitations are given.
Abstract: In this paper, a review of the common techniques used for high step-down dc-dc voltage conversion is presented. First, the limitations of conventional buck & synchronous rectifier buck converters used for high step down dc-dc voltage conversion which include narrow duty cycle, high voltage stress, large ripple and low efficiency are briefly discussed. Then various topologies of non-isolated step-down dc-dc converters are reviewed and discussed. The topologies/techniques used for high step down dc-dc conversion are divided into various groups which include interleaved, quadratic, tapped, switched capacitor, switched inductor, coupled inductor, multi level and buck converter with three state switching cells. Each group of converters is briefly discussed, main circuit structure of each topology is given and their features and limitations are given. Finally a comparison of all the discussed topologies is carried out based on some common features.
TL;DR: This paper presents a context-aware application which can provide service according to predefined choice of user and uses Mahalanobis distance based k nearest neighbors classifier technique for inference of predefined service.
Abstract: Context-awareness is an important characteristic of smart home. Several methods are used in context-aware application to provide services. The main target of smart home is to predict the demand of home users and proactively provide the proper services by computing user’s context information. In this paper, we present a context-aware application which can provide service according to predefined choice of user. It uses Mahalanobis distance based k nearest neighbors classifier technique for inference of predefined service. We combine the features of supervised and unsupervised machine learning in the proposed application. This application can also adapt itself when the choice of user is changed by using Q-learning reinforcement learning algorithm.
TL;DR: In this article, the authors developed an efficient target-oriented smart integrated multiple tracking system that looks up object location based on real time and guarantees the accuracy and reliability of logistics location and resource management by combining the function of multiple tracking systems.
Abstract: With the rapid development of the IoT market many institutions are researching and developing various integrated IOT service platforms. Among them the development of IoT based tracking system requires a platform environment that can check in real time the target-oriented logistics movement status in industrial sites and social environments and manage resources. Previous related researches studied about particular single object tracking and about establishing a linkage process, but there were no studies about systems using Multiple Tracking System that target a variety of objects to establish a total task process such as for materials, personnel, and operations and process management. The study developed an efficient target-oriented smart integrated multiple tracking system that looks up object location based on real time and guarantees the accuracy and reliability of logistics location and resource management by combining the function of multiple tracking system.
TL;DR: The result of this research is the implementation of a remote home automation application in mobile which can help users in order to control the home and determine the cost of electricity that has been used in every electronic device so that the optimization can be achieved.
Abstract: The purpose of this paper is creating a mobile app on a Smartphone device so that the user can control electronic devices; see the amount of flow that has been used in the amount of dollars, so the problem is the difficulty in saving electricity can be resolved. Development and design was done by collecting data using questionnaires to the respondents. Design method using observations, distributing questionnaires and to study literature, and then after that do the design in hardware (microcontroller) made United Modeling Language (UML), database design, code implementation and creation of user interfaces on IOS and Android. The result of this research is the implementation of a remote home automation application in mobile which can help users in order to control the home and determine the cost of electricity that has been used in every electronic device so that the optimization can be achieved.
TL;DR: It is shown that the proposed dynamic-id based remote user authentication scheme is not too much secured as they have claimed and it can suffer from stolen smart card attack, user impersonate attack and lack of some important features of smart card as well.
Abstract: As computer networks become an essential part of our daily life, therefore, protecting the resources from unauthorized users come forward with more challenging and complicated task for the researchers. From the last few decades, many number of password-based authentication schemes have been adopted in multi-server environment to protect the resources from any adversary means. Recently, Li et al. has proposed a dynamic-id based remote user authentication scheme and claimed that their scheme can provide more security than existing schemes and is suitable for practical applications. But, in this paper, we have shown that their scheme is not too much secured as they have claimed and it can suffer from stolen smart card attack, user impersonate attack and lack of some important features of smart card as well. To overcome these security flaws, we have further proposed an improved anonymous authentication scheme.
TL;DR: In this paper, a BP neural network PID control system based on virtual instrument LabVIEW is designed to reduce the influences caused by the factors mentioned above, by simulating the responses of the system in real time control, the verification tests using actual system are avoided.
Abstract: The anti-rolling tank swing bench is a typical hydraulic position servo system. Its function is to simulate the ship roll motion and to verify the performance of the anti-rolling tank. Generally, the PID control method can achieve an ideal control effect. But the uncertainties, such as the couplings and the nonlinearty of the swing bench, make it difficult to establish the precise mathematical model of system. During experiments, the different disturbance torques are generated according to the different dimension scales of the anti-rolling tanks. Changes of the natural characteristics of the system are caused by changes of load, and the fixed parameters of PID controller are difficult to continue to ensure a good control effect. In order to reduce the influences caused by the factors mentioned above, a BP neural network PID control system based on virtual instrument LabVIEW is designed. By simulating the responses of the system in real time control, the verification tests using actual system are avoided. Finally, the experiments of swing bench are carried out. The results show that the controller can ensure the control accuracy and stability. The parameters tuning process efficiency is improved. The operation is convenient. The data acquisition process is simple and practical.
TL;DR: Wang et al. as discussed by the authors discussed the application value and effect of inquiry teaching in college basketball education, which can effectively improve the normal teaching, not only promote students to actively take the basketball class, but also strengthen comprehensive physical education, as the effect is significant.
Abstract: Network education is a new concept of modern information technology applied to education, which is the education of the use of network technology, according to a series of outstanding problems in the traditional basketball teaching, we discussed the application value and effect of inquiry teaching in college basketball education. The data was collected from Jiangxi Normal University; experiment object is 36 students, and we put them in the experimental group (18) and the control group (18).By using interview method and empirical analysis, the result shows that in 50 meters (F=4.227, P=0.048<0.05); standing long jump (F=5.495, P=0.025<0.05); 1000 meters (F=4.702, P=0.037<0.05); Run-up to touch high( F=6.398 P=0.016<0.05); 1 minute shot (F=9.396 P=0.004<0.01); basketball technology F=9.116 P=0.005<0.01; basketball interest (F=16.279, P=0.000<0.01); basketball theory results (F=12.066 P=0.001<0.01). Inquiry teaching method can effectively improve the normal teaching, not only promote students to actively take the basketball class, but also strengthen comprehensive physical education, as the effect is significant, so this education model is worth to promote.
TL;DR: Wang et al. as discussed by the authors analyzed the physical structure of ice bath and put forward the control as well as the output of the ice tank for energy storage air conditioning system, by analyzing the mechanism of ice tank, ice melting system outside the tank model is established.
Abstract: In case of energy storage air conditioning system, due to load fluctuation, the traditional control methods can't obtain good effect, the model predictive control method can realize the optimization control system, and can overcome the influence of load fluctuation. In order to realize the predictive control, need to study model of air conditioning system. Ice storage air-conditioning system, by analyzing the mechanism of ice tank, ice melting system outside the tank model is established. First, analyzed the physical structure of ice bath, determine the parameters of ice bath, put forward the control as well as the output of the ice tank. Good model will be built using TRNSYS and MATLAB joint simulation, and the model simulation results and the widely used now BAC coil and TSQINGHUA TONGFANG ice coil characteristic has carried on the contrast, determine the tank model is built by ice in the most good ice tank was simulated under the condition of outlet temperature, and focused on the top 20% of the ice melted and the error of 20%, after put forward the reasonable solution, the interpretation of the ice tank established ice model has practical significance.
TL;DR: This paper adopts different dimensions of features, feature representation methods and classifiers to analyze the integral effect of aspect extraction and shows that ME is the best classifiers and presence is most suitable feature representation method for aspect extraction.
Abstract: With the development of Web, there are more and more online reviews. These reviews have become the important information for people. Therefore, automatic analysis of online reviews has become the active research area in natural language processing and management sciences. Apart from the researches about document sentiment classification and sentence sentiment classification, there are an increasing number researches about aspect-based sentiment analysis. This paper tries to use machine learning to extract aspect from Chinese hotel reviews. Through a lot of experiments, we find that machine learning methods are suitable for the aspect extraction of Chinese reviews. This paper adopts different dimensions of features, feature representation methods and classifiers to analyze the integral effect of aspect extraction. The experiment result shows that ME is the best classifiers and presence is most suitable feature representation method for aspect extraction.
TL;DR: The analysis shows that this model is suitable for the practical engineering application and can provide a basis for optimal operation of air conditioning control systems of large public buildings.
Abstract: Energy conservation and indoor environment concerns have motivated extensive research on various aspects of control of Heating, Ventilating and Air-Conditioning (HVAC) and building systems. The study on optimal operation as well as modeling of HVAC and building systems is one of the fastest growing fields that contribute to saving energy and improving indoor environment of buildings. The reasonable operation adjustment is one of the main methods to improve the energy efficiency. Cooling load prediction is the foundation of the optimization operation. This paper is devoted to the development of a comprehensive modeling of cooling load for a large building with ice-storage systems in Beijing, China. The models describe the dynamics of cooling load, outdoor climate parameters and indoor parameters as one multi-variable nonlinear system in a way that is useful for prediction analysis. The cooling load data collected is from June to September, and then the method of similarity for both longitudinal and transverse waveforms is used to judge whether there is abnormal data. The optimal parameter setting in the proposed model is studied. Principle Component Analysis (PCA) method was applied to select input parameters. A load prediction model has been constructed based on BP neural networks. Taking account of the generalization ability of neural networks, this paper has chosen the bayesian regularization algorithm, which can get better fitting effect than other training algorithms, to train the neural networks. Then, the BP neural network model is used for the summer hourly cooling load prediction of the business building. Evaluation of the prediction accuracy of the proposed models is based on the root mean square error (RMSE). The results show that the prediction model can accurately predict the future hourly load of 1 week and 1 day, with the prediction error at 1.60% and 1.18% respectively. The analysis shows that this model is suitable for the practical engineering application and can provide a basis for optimal operation of air conditioning control systems of large public buildings.
TL;DR: An intelligent-agent traffic model is implemented that controls the amount of time a light runs green for, based on the number of cars standing in the light, which results in increased congestion along the roads.
Abstract: The performance of traffic systems is greatly dependent on their ability to react to changing traffic patterns and different situations. On traditional traffic systems, the lights run green for fixed intervals of time no matter what the density of the traffic is. Here, we implement an intelligent-agent traffic model that controls the amount of time a light runs green for, based on the number of cars (density) standing in the light. With an increase in the pace at which we lead our lives, time is of the essence. One place where time is wasted is on the road being stuck in traffic jams due to mismanagement of traffic. The effectiveness of (urban) traffic control systems greatly depends on its ability to react upon changes in traffic patterns, however, conventional traffic control systems, being unintelligent are unable to do this. Be the traffic density, high or low, the signals are timed and run according to those times only. This results in increased congestion along the roads which also results in significant air pollution, an increased safety risk and also has a negative effect on the populace's mental wellbeing. It is only when the ability to react becomes an integral part of the traffic control unit, its ability to react to changes in traffic conditions improves. The responsive control system should have sufficient knowledge of the situation to be able to handle unforeseen changes in traffic flow, such as accidents or car break-down. Intelligent signal control systems must have the capability to optimize the traffic flow by adjusting the traffic lights and co- ordinate operation between each signal in order to maximize the person and vehicular throughput and minimize delay. For intelligent urban traffic control, we ideally need a fully pro-active, real-time traffic control system; anticipating what will happen within the near future. 2. Need for Smart City A smart city (also smarter city) uses digital technologies or information and communication technologies (ICT) to enhance quality and performance of urban services, to reduce costs and resource consumption, and to engage more effectively and actively with its citizens. Smart city applications are developed with the goal of improving the management of urban flows and allowing for real time responses to challenges (18).A
TL;DR: The realization ofchemical industrial park integrated information management platform based on cloud computing and IOT technologies will greatly improve the management level of chemical industrial parks, intensify surveillance, achieve information resource sharing and lower the probability of accident occurrence.
Abstract: Chemical industry is the fundamental strategic industry in national economy and one of pillar industries in China. A wealth of chemical industrial parks has been built one after another in many places, where lots of chemical enterprises are established. In the normal operation of those enterprises, their raw materials or products manufactured, transported and stored are usually featured by flammable, explosive or toxic properties, resulting in frequent occurrence of pollution and personal accidents and causing great threats to surrounding environment. This thesis realizes an integrated information management platform based on currently advanced cloud computing and IOT (The Internet of Things) technologies, so as for integrated management of chemical industrial parks. This thesis designs the architectural structure of said integrated information management platform, expounds the roles and realization approaches of the basic support platform and the business service platform, analyzes the principles and methods for realization of regionally coordinate emergency management operation mechanism based on the information management platform, that of IOT architecture technology and that of RFID and Wireless Sensor Network (WSN), and discusses that the standard unification of heterogeneous data under cloud computing is realized by means of multisource data integration middleware. The said platform can accomplish the wholeprocess, real-time and dynamic follow-up and control of chemicals and hazardous materials and also provide effective service for users’ decision-making by mining and analyzing tremendous data of a chemical industrial park with Agent-middleware technology. The information management platform is capable of assessing the safety factors of chemical enterprises at peacetime, giving necessary warning before accidents and offering effective technical support for rescue via expert system, emergency plan system, monitoring system and positioning system. The realization of chemical industrial park integrated information management platform based on cloud computing and IOT technologies will greatly improve the management level of chemical industrial parks, intensify surveillance, achieve information resource sharing and lower the probability of accident occurrence.
TL;DR: An improved support vector machine (SVM) based on characteristics and integrated method of image classification that can extract comprehensive description of image content features, using principal component analysis to extract the characteristics of transformation, remove redundant information.
Abstract: In this research paper, we conduct theoretical analysis and numerical analysis on novel image classification algorithm based on multi-feature extraction and modified SVM classifier. Image object classification and detection are two important basic problems in the study of computer vision, image segmentation, object tracking, behavior analysis and so on the basis of other high-level vision tasks. Existing image classification method can make full use of every single feature between the complementary characteristics of the extracted features of a large number of redundant information, which can lead to image classification accuracy is not high. For this, put forward an improved support vector machine (SVM) based on characteristics and integrated method of image classification. This method can extract comprehensive description of image content features, using principal component analysis to extract the characteristics of transformation, remove redundant information. The experimental result proves the effectiveness and feasibility of the proposed algorithm. In the final part, we conclude the paper and set up the prospect for the future research.
TL;DR: An improved asymmetric variable universe adaptive landing fuzzy controller with Safe Flight Area during approach for carrier-based aircraft with better performance with more accuracy and practicability is presented.
Abstract: During the process of aircraft landing, the control manners of carrier-based aircraft are always used to study. This is one of the important ways to avoid pilot-aircraft adverse coupling. In order to keep the accuracy of landing, this paper presents an improved asymmetric variable universe adaptive landing fuzzy controller with Safe Flight Area during approach for carrier-based aircraft. By means of universe-conversion factors and contraction–expansion factors, universe of discourse can be modified online, and fuzzy rules can reproduce automatically to adapt to the modified universe of discourse. The model simulation results indicate the better performance of the new method in comparison with the traditional controller with more accuracy and practicability.
TL;DR: This software gives a real-time and remote watch on fire in Greater Xing’ an Mountains, simultaneously the UAV is flying and getting the aerial data, helping users quickly master the number and location of fire points.
Abstract: This software provides functions on processing UAV (unmanned aerial vehicle) aerial image data according to the requirements of forestry area application on UAV platform. It gives a real-time and remote watch on fire in Greater Xing’ an Mountains, simultaneously the UAV is flying and getting the aerial data, helping users quickly master the number and location of fire points. Monitoring software covers functions including fire source detection module, fire location module, fire range estimation module, and report generation module. Mutual cooperation among the various modules improves operational efficiency and detection reliability of the system. What’s more, user-friendly visual interface is provided to give a convenience in user operation and interaction.
TL;DR: Analysis of new security threats, caused by open-platform of Internet of Things (IoT) and interconnectivities among various smart devices and sensors via the Internet, and requirements and scenarios for establishing standards and secure IoT service are provided.
Abstract: For the Internet of Things security, it should be considered security risk environments such as various platforms and services including smart devices that can be mounted on household electric appliances, healthcare, car, and heterogeneous networks that are connected to the Internet, and cloud services mobile apps. In this paper, we provides analysis of new security threats, caused by open-platform of Internet of Things (IoT) and interconnectivities among various smart devices and sensors via the Internet, and requirements and scenarios for establishing standards and secure IoT service.
TL;DR: This paper proposes Smart Home Web of Object User Privacy (SWOPR) architecture to protect and control the release of user PIIs according to the user consent, and suggests an architecture that integrates the RESTful framework, ISO/IEC-29101, and XACML/Ontology; the integration is not supported in existing systems.
Abstract: This paper presents user privacy framework for web-of-objects based smart home services to control the release of personally identifiable information (PII) in smart home environment. The ubiquity of smart home enables smart home users and third parties to access home devices and data from any location at any time. The ubiquitous and pervasiveness improves the user comfort level, but also makes user PIIs highly prone to leakage. We propose Smart Home Web of Object User Privacy (SWOPR) architecture to protect and control the release of user PIIs according to the user consent. We suggest an architecture that integrates the RESTful framework, ISO/IEC-29101, and XACML/Ontology; the integration is not supported in existing systems. The SWOPR introduces Smart Home Web of Objects Privacy Controller (SWOPC) and Privacy Processor (SWOPP) nodes. SWOPC controls the process of collection of PIIs from users to the release of his PIIs to others. SWOPP provides PIIs processing functions such as anonymization and encryption under the control of SWOPC. The proposed privacy framework architecture is simple, lightweight and has high performance. We also present service scenarios to acquire the user PIIs, consents and release of PIIs to others.
TL;DR: To solve the security problem of smart city should put forward a system security mode from the view of system engineering, through analyzing smart city architecture and security risk, put forward smart city security platform.
Abstract: Based on the traditional city, smart city is a new city that is constructed by Internet of things, mobile Internet, cloud computing, big data and other information technologies. Smart city can change interaction way of people, improve the real-time processing capability of information and response speed; promote comprehensive and sustainable development of various social works of smart city. But because Internet of things connected the real world and cyber space, in the smart city operation, not only include the traditional security problems, for example, the related equipment and building destruction, also include through software and instruction to damage network information, city construction and so on, which will bring a big challenge to smart city operation. To solve the security problem of smart city should put forward a system security mode from the view of system engineering. Through analyzing smart city architecture and security risk, put forward smart city security platform, studied the physical equipment protection, information security technologies, effective management, laws, personal information security literacy of smart city.