A Common Use Communication Node Design Based on Smart Home Terminal Control

With the development of intelligent home appliance technology, real-time home appliance status information is now generated in large quantities. New technology is necessary in order to process the large amount of status information that is generated every day. An innovative technology that has recently been used to process large amounts of data is cloud computing. Therefore, in this paper, we propose a system model to control and monitor home appliances using home network and cloud computing technologies in a smart home environment. UPnP technology is used to extract status information from home appliances. Cloud computing technology analyzes and processes the information and also provides virtualization services to users. In the proposed method, the gateway collects and stores home appliance information using home network technologies and sends the information to the cloud server for storage and management.

In past few years, Industrial, home automation & remote control and monitoring systems have seen a rapid growth in terms of technology. This proposal gives a review of these systems based on existing technologies; the paper illustrates the working of GSM (Global System for mobile communication).As the GSM technologies, growing faster day by day. In this proposal we are building a home automation system, where one can control the home appliances, using the simple GSM based phone, just by sending SMS through his phone. And as well as this proposal contain different sensor like temperature fire smoke, gas leakage etc. to on/off the respective loads. The other phase of this proposal based on smart home energy meter which have the ability to records the whole month or one day energy consuming by smart house to perform the normal task .the units the smart house uses the whole month can be record in PIC controller and then send this data to owner of smart house with the help of GSM.

Since the end of 2000, smartphones have explosively spread and have made people’s lives plentiful. With the start of smartphones, new smart devices, including tablet PCs, smart TVs, smart refrigerators, and smart air conditioners, have emerged, expanding their areas from individuals to business and home. These days, smart home service has drawn a lot of attention as a human-centric service. It is the environment where home appliances and other smart devices are connected to internet in order for user service and experience. The current smart home service is simply based on wireless home network to execute the function of connected home. The service has no smart home security so that it is possible for users to suffer a financial loss caused by information leakage or home appliance hacking. Therefore, to apply smart home service to surroundings, it is necessary to take into account security of smart devices. In this paper, we propose an enhanced security framework for smart devices in a smart home environment. The security framework provides the integrity system using the self-signing and access control techniques for preventing the security threats such as data modification, leakage and code fabrication.

We are witnessing a significant expansion and penetration of wireless appliances, sensors, smart phones, and PDAs in a wide range of domains such as hospitals, healthcare, smart homes, and elderly home care. Healthcare applications are mission-critical, real-time, and are used in a complex socio-technical system that requires collaboration, communication and coordination between many actors (doctors, patients, nurses, lab technicians, administration, etc.) and devices in the system, depending on their context. This paper introduces a framework for supporting context awareness, which is built from available open source components. The paper illustrates how the framework can be used in the healthcare domain with the help of an emergency department application.

This chapter presents the concept of Smart Home, describes the Smart Home networking technologies and discusses the main issues for ensuring security in a Smart Home environment. Nowadays, the integration of current communication and information technologies within the dwelling has led to the emergence of Smart Homes. These technologies facilitate the building of Smart Home environments in which devices and systems can communicate with each other and can be controlled automatically in order to interact with the household members and improve the quality of their life. However, the nature of Smart Home environment, the fact that it is always connected to the outside world via Internet and the open security back doors derived from the household members raise many security concerns. Finally, by reviewing the existing literature regarding Smart Homes and security issues that exist in Smart Home environments, the authors envisage to provide a base to broaden the research in Smart Home security.

Internet of Thing (IoT) is going to make such a world where physical things (smart home appliances, and smart watches etc.) revolutionized the information networks and services providing systems which provide innovative and smart services to human. With smart home technology, our living area is becoming more comfortable and convenient. Smart home technology provides automated, intelligent, smart, innovative and ubiquitous services to residential users through Information Communication Technology (ICT). Due to internet-connected, dynamic and heterogeneous nature of smart home environment creates new security, authentication and privacy challenges. In this paper, we investigate security attacks in smart home and evaluate their impact on the overall system security. We identified security requirements and solutions in the smart home environment. Based on several scenarios, we suggest to set security goals for the smart home environment. Based on historical data, we forecast security attacks (like malware, virus etc.) and estimated that how many attacks are expected to be launched in coming years.

The Internet of things is a new technological revolution following the computer and Internet. It aims to connect all physical objects existing in the world and forms a network with everything. In recent years, smart home gradually enters into our life. Smart home uses the Internet of things technology to connect all kinds of devices in the home, to achieve a smart home environment. Although the development of smart home has brought a qualitative leap to people’s life, there are many problems in security. Privacy security is one of the challenges to the smart home environment. Attackers can intrude various smart devices in the smart home environment, to achieve the purpose of stealing users’ personal information and privacy. Among these devices, smart cameras are the most intruded frequently. Since many cameras are installed in users’ homes to achieve real-time monitoring of the environment, but the existence of these cameras provides a channel to get information for attackers. In recent years, the leak of video privacy is emerging in an endless stream. According to the researches about privacy protection, this paper proposes a new scheme to selectively encrypt the video captured by the cameras through machine learning technology, so as to protect the personal privacy of users and improve the security of the smart home environment.

Emerging domains such as smart homes and more recently smart cities represent a big challenge to software engineering. In such context, the need of runtime self-adaptations to cope with both user needs and environmental changes brings Dynamic Software Product Lines (DSPL) as a suitable solution. However, DSPL implementation itself is challenging, which demands a proper modeling. In this sense, the literature still lacks of means of choosing the modeling technique that best fits a given domain. This paper tackles such problem by defining a criteria for rank such techniques, which is used for ranking a set DSPL modeling techniques found in the literature.

Real world engineering problems often involve selecting between alternatives. As cyber-physical systems (CPS) become more prevalent in society, including smart cities, intelligent transportation networks, smart homes, etc., these alternatives will increasingly not only include variations in hardware but also in software. Stakeholders will have to decide between competing designs consisting of varying sensor sets and varying machine learning models. Ensuring that these selections are well guided and include multiple objectives such as performance, cost, and sensitivity is paramount. Many of these CPS will include machine learning classification models. The receiver operating characteristic (ROC) analysis is useful for selecting between alternative classification models based on performance and sensitivity, however, this analysis fails to treat classification models as a system of hardware and software, a CPS. Therefore, the ROC analysis ignores additional stakeholder objectives such cost and reliability. This thesis presents methods to extend the ROC analysis to include an additional objective of system cost. The methodology is demonstrated on three real world data sets that include additional cost information. The presented methodology is shown to drastically reduce the stakeholder decision space and guide stakeholder decisions using performance, cost, and sensitivity objectives.

Smart homes are an emerging paradigm of Internet of Things (IoT) in which users can remotely control various home devices via the internet anytime and anywhere. However, smart home environments are vulnerable to security attacks because an attacker can inject, insert, intercept, delete, and modify transmitted messages over an insecure channel. Thus, secure and lightweight authentication protocols are essential to ensure useful services in smart home environments. In 2021, Kaur and Kumar presented a two-factor based user authentication protocol for smart homes using elliptic curve cryptosystems (ECC). Unfortunately, we demonstrate that their scheme cannot resist security attacks such as impersonation and session key disclosure attacks, and also ensure secure user authentication. Moreover, their scheme is not suitable in smart home environments because it utilizes public-key cryptosystems such as ECC. Hence, we design a secure and lightweight three-factor based privacy-preserving authentication scheme for IoT-enabled smart home environments to overcome the security problems of Kaur and Kumar’s protocol. We prove the security of the proposed scheme by using informal and formal security analyses such as the ROR model and AVISPA simulation. In addition, we compare the performance and security features between the proposed scheme and related schemes. The proposed scheme better provides security and efficiency compared with the previous schemes and is more suitable than previous schemes for IoT-enabled smart home environments.

Inhabitants of today's smarter homes struggle with complicated user interfaces and inflexible home configurations. The proposed smart home recommender system addresses these issues by continuously ...

Typical Internet of Things (IoT) and smart home environments are composed of smart devices that are controlled and orchestrated by applications developed and run in the cloud. Correctness is important for these applications, since they control the home’s physical security (i.e. door locks) and systems (i.e. HVAC). Unfortunately, many smart home applications and systems exhibit poor security characteristics and insufficient system support. Instead they force application developers to reason about a combination of complicated scenarios—asynchronous events and distributed devices. This paper demonstrates that existing cloud-based smart home platforms provide insufficient support for applications to correctly deal with concurrency and data consistency issues. These weaknesses expose platform vulnerabilities that affect system correctness and security (e.g. a smart lock erroneously unlocked). To address this, we present OKAPI, an application-level API that provides strict atomicity and event ordering. We evaluate our work using the Samsung SmartThings smart home devices, hub, and cloud infrastructure. In addition to identifying shortfalls of cloud-based smart home platforms, we propose design guidelines to make application developers oblivious of smart home platforms’ consistency and concurrency intricacies.

Interacting with the Web of Things

With the rapid development of economy, science, and technology, people have higher and higher requirements for the quality of home life, and smart home systems are required to have higher convenience and comfort. The continuous development of embedded technology, short‐range wireless communication technology, and microcontroller technology provides a new development direction for the research and development of smart home systems. Under the premise of fully studying the research status and development trend of smart home systems, this paper combines embedded technology, ZigBee wireless communication technology, voice recognition technology, GSM communication technology, etc., and proposes a ZigBee‐based smart voice home appliance control system. The system adopts ZigBee wireless communication to form a comprehensive management system for household electrical appliances, electronic and electrical equipment, etc., for household electrical control, intelligent security, and environmental monitoring. This paper designs the overall scheme of a smart home control system based on voice recognition technology. According to this scheme, the hardware and software of the system are designed, and the wireless communication method combining Wi‐Fi and RF (radio frequency) of the system is also determined. In order to make the system more humane, two sets of control schemes, voice control and button control, are designed according to the system’s functional requirements. In the voice control solution, the user first reads the control commands set in the voice library on the smart terminal, and then, the system automatically recognizes the commands read by the user. After the recognition is successful, the user can control the home appliances through the command. In the key control scheme, users can control home appliances through keys on the smart terminal. The upper computer transplants the audio library and the algorithm studied in this paper to realize the audio collection and storage, the confirmation of family members, and the recognition of voice commands; the lower computer is used for real‐time collection of environmental information and wireless control of home facilities. After the system is started, the family members are first confirmed by voice, and then, the voice command recognition result and real‐time environmental information jointly decide to form a control command. The upper computer sends the control command to the lower computer through the serial port to control the corresponding home equipment. The system is tested and analyzed under experimental conditions. The test results show that the system can control home facilities through voice commands combined with real‐time environmental information while confirming family members.

Smart Home research started in 2000. Since then, Smart Home has attracted the attention of many researchers, and several studies have been conducted. This study aims to chart Smart Home research trends using bibliometric analyses from all years up to the publication date indexed in Scopus. We use keywords related to Smart Home in the Scopus database. Analysis techniques that use parameters include the year of publication, Scopus quartile range, year of publication, type of publication, journal publication, the publication of the most frequently cited maps, and density display mapping. The results show that the Q1 journal dominated since the first Smart Home publication in 2000 and peaked in 2013. The journal article type is the most commonly published compared to research conferences and other publications. Journal publications show the majority of IEEE transactions in consumer electronics. Three Smart Home publications have been cited more than 1563 times. This study also found that the words ‘smart home’, ‘technology,’ and ‘management’ are widely used by researchers. For future research, you should use keywords like ‘smart home energy management,’ ‘smart home environment,’ ‘sensor,’ ‘electric vehicle,’ and ‘smart home technology.’