Showing papers on "Home automation published in 2018"

Securing Fog Computing for Internet of Things Applications: Challenges and Solutions

Abstract: Internet of Things (IoT) allows billions of physical objects to be connected to collect and exchange data for offering various applications, such as environmental monitoring, infrastructure management, and home automation. On the other hand, IoT has unsupported features (e.g., low latency, location awareness, and geographic distribution) that are critical for some IoT applications, including smart traffic lights, home energy management and augmented reality. To support these features, fog computing is integrated into IoT to extend computing, storage and networking resources to the network edge. Unfortunately, it is confronted with various security and privacy risks, which raise serious concerns towards users. In this survey, we review the architecture and features of fog computing and study critical roles of fog nodes, including real-time services, transient storage, data dissemination and decentralized computation. We also examine fog-assisted IoT applications based on different roles of fog nodes. Then, we present security and privacy threats towards IoT applications and discuss the security and privacy requirements in fog computing. Further, we demonstrate potential challenges to secure fog computing and review the state-of-the-art solutions used to address security and privacy issues in fog computing for IoT applications. Finally, by defining several open research issues, it is expected to draw more attention and efforts into this new architecture.

How Can Heterogeneous Internet of Things Build Our Future: A Survey

Abstract: Heterogeneous Internet of Things (HetIoT) is an emerging research field that has strong potential to transform both our understanding of fundamental computer science principles and our future living. HetIoT is being employed in increasing number of areas, such as smart home, smart city, intelligent transportation, environmental monitoring, security systems, and advanced manufacturing. Therefore, relaying on strong application fields, HetIoT will be filled in our life and provide a variety of convenient services for our future. The network architectures of IoT are intrinsically heterogeneous, including wireless sensor network, wireless fidelity network, wireless mesh network, mobile communication network, and vehicular network. In each network unit, smart devices utilize appropriate communication methods to integrate digital information and physical objects, which provide users with new exciting applications and services. However, the complexity of application requirements, the heterogeneity of network architectures and communication technologies impose many challenges in developing robust HetIoT applications. This paper proposes a four-layer HetIoT architecture consisting of sensing, networking, cloud computing, and applications. Then, the state of the art in HetIoT research and applications have been discussed. This paper also suggests several potential solutions to address the challenges facing future HetIoT, including self-organizing, big data transmission, privacy protection, data integration and processing in large-scale HetIoT.

Design of Secure User Authenticated Key Management Protocol for Generic IoT Networks

Abstract: In recent years, the research in generic Internet of Things (IoT) attracts a lot of practical applications including smart home, smart city, smart grid, industrial Internet, connected healthcare, smart retail, smart supply chain and smart farming. The hierarchical IoT network (HIoTN) is a special kind of the generic IoT network, which is composed of the different nodes, such as the gateway node, cluster head nodes, and sensing nodes organized in a hierarchy. In HIoTN, there is a need, where a user can directly access the real-time data from the sensing nodes for a particular application in generic IoT networking environment. This paper emphasizes on the design of a new secure lightweight three-factor remote user authentication scheme for HIoTNs, called the user authenticated key management protocol (UAKMP). The three factors used in UAKMP are the user smart card, password, and personal biometrics. The security of the scheme is thoroughly analyzed under the formal security in the widely accepted real-or-random model, the informal security as well as the formal security verification using the widely accepted automated validation of Internet security protocols and applications tool. UAKMP offers several functionality features including offline sensing node registration, freely password and biometric update facility, user anonymity, and sensing node anonymity compared to other related existing schemes. In addition, UAKMP is also comparable in computation and communication costs as compared to other existing schemes.

Review on Home Energy Management System Considering Demand Responses, Smart Technologies, and Intelligent Controllers

Abstract: The increasing demand for electricity and the emergence of smart grids have presented new opportunities for a home energy management system (HEMS) that can reduce energy usage. The HEMS incorporates a demand response (DR) tool that shifts and curtails demand to improve home energy consumption. This system commonly creates optimal consumption schedules by considering several factors, such as energy costs, environmental concerns, load profiles, and consumer comfort. With the deployment of smart meters, performing load control using the HEMS with DR-enabled appliances has become possible. This paper provides a comprehensive review on previous and current research related to the HEMS by considering various DR programs, smart technologies, and load scheduling controllers. The application of artificial intelligence for load scheduling controllers, such as artificial neural network, fuzzy logic, and adaptive neural fuzzy inference system, is also reviewed. Heuristic optimization techniques, which are widely used for optimal scheduling of various electrical devices in a smart home, are also discussed.

Privacy-Preserving and Efficient Aggregation Based on Blockchain for Power Grid Communications in Smart Communities

Abstract: Intelligence is one of the most important aspects in the development of our future communities. Ranging from smart home to smart building to smart city, all these smart infrastructures must be supported by intelligent power supply. Smart grid is proposed to solve all challenges of future electricity supply. In smart grid, in order to realize optimal scheduling, an SM is installed at each home to collect the near-real-time electricity consumption data, which can be used by the utilities to offer better smart home services. However, the near-real-time data may disclose a user's private information. An adversary may track the application usage patterns by analyzing the user's electricity consumption profile. In this article, we propose a privacy-preserving and efficient data aggregation scheme. We divide users into different groups, and each group has a private blockchain to record its members' data. To preserve the inner privacy within a group, we use pseudonyms to hide users' identities, and each user may create multiple pseudonyms and associate his/ her data with different pseudonyms. In addition, the bloom filter is adopted for fast authentication. The analysis shows that the proposed scheme can meet the security requirements and achieve better performance than other popular methods.

User Perceptions of Smart Home IoT Privacy

Abstract: 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.

Learning to live in a smart home

Abstract: Smart homes promise to significantly enhance domestic comfort, convenience, security and leisure whilst simultaneously reducing energy use through optimized home energy management. Their ability to...

IoT-based smart homes: A review of system architecture, software, communications, privacy and security

Abstract: This article presents a review of major technologies of IoT-based smart homes. It starts with definition of the smart home that sets the perspective adopted in the review. In addition to describing the complementary user and system functions of the smart home, it introduces its general, IoT-based architecture and sets smart homes within the larger context of the smart grid. The following sections concentrate on software solutions and components of smart home management systems, related communication technologies, and issues of privacy and security associated with the connected nature of modern smart homes. A separate section presents current challenges of smart home technologies and their dispersion, and points to some interesting solutions and future trends.

Datanet: Deep Learning Based Encrypted Network Traffic Classification in SDN Home Gateway

Abstract: A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined-network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to the access network, i.e., a smart home network, for better end-to-end network management. Specifically, the proposed SDN-HGW can achieve distributed application awareness by classifying data traffic in a smart home network. Most existing traffic classification solutions, e.g., deep packet inspection, cannot provide real-time application awareness for encrypted data traffic. To tackle those issues, we develop encrypted data classifiers (denoted as DataNets) based on three deep learning schemes, i.e., multilayer perceptron, stacked autoencoder, and convolutional neural networks, using an open data set that has over 200 000 encrypted data samples from 15 applications. A data preprocessing scheme is proposed to process raw data packets and the tested data set so that DataNet can be created. The experimental results show that the developed DataNets can be applied to enable distributed application-aware SDN-HGW in future smart home networks.

Smart homes and the control of indoor air quality

Abstract: Global climate change, demographic change and advancing mechanization of everyday life will go along with new ways of living. Temperature extremes, an ageing society and higher demands on a comfortable life will lead to the implementation of sensor based networks in order to create acceptable and improved living conditions. Originally, the idea of the smart home served primarily the efficient use of energy and the optimization of ventilation technology connected with new ways of constructing buildings (low-energy and passive houses, respectively). Today the term 'smart home' is also linked with the networking of home automation systems, home appliances and communications and entertainment electronics. Living in a smart home often makes also significant demands on the occupants who are required to drastically change some of their living habits. This review summarizes current findings on the effect of measured environmental parameters on indoor air quality, individual thermal comfort and living behavior in smart homes with focus on central Europe. A critical evaluation of available sensor technologies, their application in homes and data security aspects as well as limits and possibilities of current technologies to control particles and gaseous pollutants indoors is included. The review also considers the acceptance of smart technologies by occupants in terms of living habits, perceived indoor air quality and data security.

“Home is where the smart is”? Evaluating smart home research and approaches against the concept of home

Abstract: This article develops concepts of what the home is and reflects on smart home technology and the research literature on smart homes in relation to these concepts. The focus is on the aspects of smart home technologies related to energy management within the home (end-uses) and at network or grid level (system). Four aspects of a home are distinguished: a place for security and control, for activity, for relationships and continuity, and for identity and values. These aspects of home are used to discuss approaches to, and ideas of, the smart home, as reflected in the research literature. It is shown that technical and ‘prospective’ research literature focuses on aspects of security and control in the home as well as on activities, whereas research papers that are more conceptual and evaluative are more likely to include questions of relations, values and identities. The paper concludes that a broader understanding of the home in all aspects is needed when conducting research into smart homes. This can be valuable when evaluating how smart home technologies work in real homes, as well as in the more technical and prospective approaches to developing new socio-technical configurations.

Smart Home Based on WiFi Sensing: A Survey

Abstract: Conventional sensing methodologies for smart home are known to be labor-intensive and complicated for practical deployment. Thus, researchers are resorting to alternative sensing mechanisms. Wi-Fi is one of the key technologies that enable connectivity for smart home services. Apart from its primary use for communication, Wi-Fi signal has now been widely leveraged for various sensing tasks, such as gesture recognition and fall detection, due to its sensitivity to environmental dynamics. Building smart home based on Wi-Fi sensing is cost-effective, non-invasive, and enjoys convenient deployment. In this paper, we survey the recent advances in the smart home systems based on the Wi-Fi sensing, mainly in such areas as health monitoring, gesture recognition, contextual information acquisition, and authentication.

HoMonit: Monitoring Smart Home Apps from Encrypted Traffic

Abstract: Smart home is an emerging technology for intelligently connecting a large variety of smart sensors and devices to facilitate automation of home appliances, lighting, heating and cooling systems, and security and safety systems Our research revolves around Samsung SmartThings, a smart home platform with the largest number of apps among currently available smart home platforms The previous research has revealed several security flaws in the design of SmartThings, which allow malicious smart home apps (or SmartApps) to possess more privileges than they were designed and to eavesdrop or spoof events in the SmartThings platform To address these problems, this paper leverages side-channel inference capabilities to design and develop a system, dubbed HoMonit, to monitor SmartApps from encrypted wireless traffic To detect anomaly, HoMonit compares the SmartApps activities inferred from the encrypted traffic with their expected behaviors dictated in their source code or UI interfaces To evaluate the effectiveness of HoMonit, we analyzed 181 official SmartApps and performed evaluation on 60 malicious SmartApps, which either performed over-privileged accesses to smart devices or conducted event-spoofing attacks The evaluation results suggest that HoMonit can effectively validate the working logic of SmartApps and achieve a high accuracy in the detection of SmartApp misbehaviors

User Perceptions of Smart Home IoT Privacy

Abstract: 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.

Towards Dynamic Coordination Among Home Appliances Using Multi-Objective Energy Optimization for Demand Side Management in Smart Buildings

Abstract: In this paper, we propose a home energy management system that employs load shifting strategy of demand side management to optimize the energy consumption patterns of a smart home. It aims to manage the load demand in an efficient way to minimize electricity cost and peak to average ratio while maintaining user comfort through coordination among home appliances. In order to meet the load demand of electricity consumers, we schedule the load in day-ahead and real-time basis. We propose a fitness criterion for proposed hybrid technique, which helps in balancing the load during ON-peak and OFF-peak hours. Moreover, for real-time rescheduling, we present the concept of coordination among home appliances. This helps the scheduler to optimally decide the ON/OFF status of appliances in order to reduce the waiting time of appliance. For this purpose, we formulate our real-time rescheduling problem as knapsack problem and solve it through dynamic programming. This paper also evaluates the behavior of the proposed technique for three pricing schemes including: time of use, real-time pricing, and critical peak pricing. Simulation results illustrate the significance of the proposed optimization technique with 95% confidence interval.

Design, Implementation and Practical Evaluation of an IoT Home Automation System for Fog Computing Applications Based on MQTT and ZigBee-WiFi Sensor Nodes.

Abstract: In recent years, the improvement of wireless protocols, the development of cloud services and the lower cost of hardware have started a new era for smart homes. One such enabling technologies is fog computing, which extends cloud computing to the edge of a network allowing for developing novel Internet of Things (IoT) applications and services. Under the IoT fog computing paradigm, IoT gateways are usually utilized to exchange messages with IoT nodes and a cloud. WiFi and ZigBee stand out as preferred communication technologies for smart homes. WiFi has become very popular, but it has a limited application due to its high energy consumption and the lack of standard mesh networking capabilities for low-power devices. For such reasons, ZigBee was selected by many manufacturers for developing wireless home automation devices. As a consequence, these technologies may coexist in the 2.4 GHz band, which leads to collisions, lower speed rates and increased communications latencies. This article presents ZiWi, a distributed fog computing Home Automation System (HAS) that allows for carrying out seamless communications among ZigBee and WiFi devices. This approach diverges from traditional home automation systems, which often rely on expensive central controllers. In addition, to ease the platform’s building process, whenever possible, the system makes use of open-source software (all the code of the nodes is available on GitHub) and Commercial Off-The-Shelf (COTS) hardware. The initial results, which were obtained in a number of representative home scenarios, show that the developed fog services respond several times faster than the evaluated cloud services, and that cross-interference has to be taken seriously to prevent collisions. In addition, the current consumption of ZiWi’s nodes was measured, showing the impact of encryption mechanisms.

Peek-a-Boo: I see your smart home activities, even encrypted!

Abstract: A myriad of IoT devices such as bulbs, switches, speakers in a smart home environment allow users to easily control the physical world around them and facilitate their living styles through the sensors already embedded in these devices. Sensor data contains a lot of sensitive information about the user and devices. However, an attacker inside or near a smart home environment can potentially exploit the innate wireless medium used by these devices to exfiltrate sensitive information from the encrypted payload (i.e., sensor data) about the users and their activities, invading user privacy. With this in mind,in this work, we introduce a novel multi-stage privacy attack against user privacy in a smart environment. It is realized utilizing state-of-the-art machine-learning approaches for detecting and identifying the types of IoT devices, their states, and ongoing user activities in a cascading style by only passively sniffing the network traffic from smart home devices and sensors. The attack effectively works on both encrypted and unencrypted communications. We evaluate the efficiency of the attack with real measurements from an extensive set of popular off-the-shelf smart home IoT devices utilizing a set of diverse network protocols like WiFi, ZigBee, and BLE. Our results show that an adversary passively sniffing the traffic can achieve very high accuracy (above 90%) in identifying the state and actions of targeted smart home devices and their users. To protect against this privacy leakage, we also propose a countermeasure based on generating spoofed traffic to hide the device states and demonstrate that it provides better protection than existing solutions.

Smart technology in the home: time for more clarity

Abstract: The idea of the smart home has been around for decades but smart homes (under most definitions) are extremely rare, although digital technology and automated appliances are commonplace in the more ...

EPIC: A Differential Privacy Framework to Defend Smart Homes Against Internet Traffic Analysis

Abstract: The Internet of Things (IoT) becomes a novel paradigm as more and more devices are connected to the Internet, enabling several innovative applications such as smart home, industrial automation, and connected health. However, the cyber-attack to these applications is a big issue and countermeasures are in dire need to provide system security and user privacy. In this paper, we address the traffic analysis attack to smart homes, where adversaries intercept the Internet traffic from/to the smart home gateway and profile residents’ behaviors through digital traces. Traditional cryptographic tools may not work well due to the effectiveness of adversaries’ machine learning algorithms in classifying encrypted traffic, so here we propose a privacy-preserving traffic obfuscation framework to achieve the goal. To be specific, we leverage the smart community network of wirelessly connected smart homes and intentionally direct each smart home’s traffic to another home gateway before entering the Internet. The design jointly considers the network energy consumption and the resource constraints in IoT devices, while achieving strong differential privacy guarantee so that adversaries cannot link any traffic flow to a specific smart home. Besides, we consider a hostile smart community network and develop secure multihop routing protocols to guarantee the source/destination unlinkability and satisfy each user’s personalized privacy requirement. To evaluate the effectiveness of our framework in protecting privacy and reducing network energy consumption, extensive simulations are conducted and the results demonstrate that our design outperforms other differential privacy mechanism in preserving privacy and minimizing network utility cost.

Smart Home Energy Management Including Renewable Sources: A QoE-Driven Approach

Abstract: Smart home energy management (SHEM) systems can introduce adjustments in the working period and operations of home appliances to allow for energy cost savings, which can however affect the quality of experience (QoE) perceived by the user. This paper analyses this issue and proposes a QoE-aware SHEM system, which relies on the knowledge of the annoyance suffered by users when the operations of appliances are changed with respect to the ideal user’s preferences. Accordingly, a number of profiles describing different usages are created in the design phase. At the deployment stage, users behavior and annoyance are registered to assign one of these profiles per appliance. The assigned profile is then exploited by the QoE-aware cost saving appliance scheduling and the QoE-aware renewable source power allocation algorithms. The former is aimed at scheduling controlled loads based on users profile preferences and electricity prices. The latter re-allocates appliances’ operations whenever a surplus of energy is available by renewable energy sources. Experimental results demonstrate that the annoyance perceived by users is severely diminished with respect to a QoE-unaware strategy, at the expenses of only a limited reduction in energy saving.

Smart-home automation using IoT-based sensing and monitoring platform

Abstract: In order to help maintain comfortable living conditions within a home, home monitoring and automation are utilized. The standards of human's comfort in homes can be categorized into several types. Among these categories, the most significant ones are the thermal comfort, which is related to temperature and humidity, followed by the visual comfort, related to colors and light, and hygienic comfort, associated with air quality. A system can be set to monitor these parameters to help maintain them within an acceptable range. Additionally, making the house smart is to allow for intelligent automatic executing of several commands after analyzing the collected data. Automation can be accomplished by using the Internet of Things (IoT). This gives the inhabitant accesses to certain data in the house and the ability to control some parameters remotely. This paper presents the complete design of an IoT based sensing and monitoring system for smart home automation. The proposed design uses the EmonCMS platform for collecting and visualizing monitored data and remote controlling of home appliances and devices. The selected platform is very flexible and user-friendly. The sensing of different variables inside the house is conducted using the NodeMCU-ESP8266 microcontroller board, which allows realtime data sensing, processing and uploading/downloading to/from the EmonCMS cloud server.

IoT Smart Home Adoption: The Importance of Proper Level Automation

Abstract: The word “smart” has been used in various fields and is widely accepted to mean intelligence. Smart home service, one of the representative emerging technologies in the IoT era, has changed house equipment into being more intelligent, remote controllable, and interconnected. However, the intelligence and controllability of a smart home service are contradictory concepts, under certain aspects. In addition, the level of intelligence or controllability of a smart home service that users want may differ according to the user. As potential users of smart home services have diversified in recent years, providing the appropriate functions and features is critical to the diffusion of the service. Thus, this study examines the smart home service features that current users require and empirically evaluates the relationship between the critical factors and the adoption behavior with 216 samples from Korea. The moderating effect of personal characteristics on behavior is also tested. The results of the analysis provide various theoretical and practical implications.

Smart GSM Based Home Automation System

Abstract: This research work investigates the potential of Full Home Control, which is the aim of the Home Automation Systems in near future. The analysis and implementation of the home automation technology using Global System for Mobile Communication (GSM) modem to control home appliances such as light, conditional system, and security system via Short Message Service (SMS) text messages is presented in this paper. The proposed research work is focused on the functionality of the GSM protocol, which allows the user to control the target system away from residential using the frequency bandwidths. The concept of serial communication and AT-commands has been applied towards the development of the smart GSM-based home automation system. Homeowners will be able to receive feedback status of any home appliances under control whether switched on or off remotely from their mobile phones. PIC16F887 microcontroller with the integration of GSM provides the smart automated house system with the desired baud rate of 9600 bps. The proposed prototype of GSM based home automation system was implemented and tested with a maximum of four loads and shows the accuracy of greater or equal 98%.

Blockchain framework for IoT data quality via edge computing

Abstract: Smart home presents a challenge in control and monitoring of its wireless sensors networks (WSN) and the internet of things (IoT) devices which form it. The current IoT architectures are centralized, complex, with poor security in its communications and with upstream communication channels mainly. As a result, there are problems with data reliability. These problems include data missing, malicious data inserted, communications network overload, and overload of computing power at the central node. In this paper a new architecture is presented. This architecture based in blockchain introduce the edge computing layer and a new algorithm to improve data quality and false data detection.

IoT based smart home automation system using sensor node

Abstract: In recent years, the advancements in Information and Communication Technology (ICT) are mainly focused on the Internet of Things (IoT). In a real-world scenario, IoT based services improve the domestic environment and are used in various applications. Home automation based IoT is versatile and popular applications. In home automation, all home appliances are networked together and able to operate without human involvement. Home automation gives a significant change in humans life which gives smart operating of home appliances. This motivated us to develop a new solution which controls some home appliances like light, fan, door cartons, energy consumption, and level of the Gas cylinder using various sensors like LM35, IR sensors, LDR module, Node MCU ESP8266, and Arduino UNO. The proposed solution uses the sensor and detects the presence or absence of a human object in the housework accordingly. Our solution also provides information about the energy consumed by the house owner regularly in the form of message. Also, it checks, the level of gas in the gas cylinder if it reaches lesser than the threshold, it automatically books the gas and sends a reference number as a message to the house owner. The proposed solution is deployed and tested for various conditions. Finally, in this paper, the working model of our proposed solution is developed as a prototype and explained as a working model.

Implemented IoT-Based Self-Learning Home Management System (SHMS) for Singapore

Abstract: Internet of Things makes deployment of smart home concept easy and real. Smart home concept ensures residents to control, monitor, and manage their energy consumption without any wastage. This paper presents a self-learning home management system. In the proposed system, a home energy management system, demand side management system, and supply side management system were developed and integrated for real time operation of a smart home. This integrated system has some capabilities such as price forecasting, price clustering, and power alert system to enhance its functions. These enhancing capabilities were developed and implemented using computational and machine learning technologies. In order to validate the proposed system, real-time power consumption data was collected from a Singapore smart home and a realistic experimental case study was carried out. The case study has shown that the developed system has performed well and created energy awareness to the residents. This proposed system also displays its ability to customize the model for different types of environments compared to traditional smart home models.