Smart Home Energy Management System

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

Definition of an FHIR-based multiprotocol IoT home gateway to support the dynamic plug of new devices within instrumented environments

Internet of Things (IoT) technologies have become a milestone advancement in the digital healthcare domain, since the number of IoT medical devices is grown exponentially, and it is now anticipated that by 2020, there will be over 161 million of them connected worldwide. Therefore, in an era of continuous growth, IoT healthcare faces various challenges, such as the collection over multiple protocols (e.g. Bluetooth, MQTT, CoAP, ZigBEE, etc.) the interpretation, as well as the harmonization of the data format that derive from the existing huge amounts of heterogeneous IoT medical devices. In this respect, this study aims at proposing an advanced Home Gateway architecture that offers a unique data collection module, supporting direct data acquisition over multiple protocols (i.e.BLE, MQTT) and indirect data retrieval from cloud health services (i.e. GoogleFit). Moreover, the solution propose a mechanism to automatically convert the original data format, carried over BLE, in HL7 FHIR by exploiting device capabilities semantic annotation implemented by means of FHIR resource as well. The adoption of such annotation enables the dynamic plug of new sensors within the instrumented environment without the need to stop and adapt the gateway. This simplifies the dynamic devices landscape customization requested by the several telemedicine applications contexts (e.g. CVD, Diabetes) and demonstrate, for the first time, a concrete example of using the FHIR standard not only (as usual) for health resources representation and storage but also as instrument to enable seamless integration of IoT devices. The proposed solution also relies on mobile phone technology which is widely adopted aiming at reducing any obstacle for a larger adoption.

MyMaster : A Multifactor Authentication Scheme for Smart Home Device

Smart homes are one of the Internet of Things (IoT) applications most significant to enable people to operate intelligent devices on the Internet in their homes. However, when users can access an intelligent home system remotely, they have major privacy and confidentiality difficulties to overcome. Nothing has been done to improve the safety characteristics of an intelligent home with current research on authentication approaches. For example, to address these issues and to develop a reciprocal tracking authentication system with a critical aspect of a deal, we recommend an Internet based Smart Home System (IFTTT) model. As a controller and a safety guard, an IFTTT-Home Gateway provides a user with remote access to a Smart Home System within their company. The system is designed for mutual authentication with security features such as anonymity and full advance security by using Elliptical Curve Encryption, Nonces, XOR or cryptographic Hash functions. We also incorporate multi factor authentication (MFA) into the model to ensure more security and preventing privacy leakage.

Smart Home Gateway Based on Integration of Deep Reinforcement Learning and Blockchain Framework

The development of information and communication technology in terms of sensor technologies cause the Internet of Things (IoT) step toward smart homes for prevalent sensing and management of resources. The gateway connections contain various IoT devices in smart homes representing the security based on the centralized structure. To address the security purposes in this system, the blockchain framework is considered a smart home gateway to overcome the possible attacks and apply Deep Reinforcement Learning (DRL). The proposed blockchain-based smart home approach carefully evaluated the reliability and security in terms of accessibility, privacy, and integrity. To overcome traditional centralized architecture, blockchain is employed in the data store and exchange blocks. The data integrity inside and outside of the smart home cause the ability of network members to authenticate. The presented network implemented in the Ethereum blockchain, and the measurements are in terms of security, response time, and accuracy. The experimental results show that the proposed solution contains a better outperform than recent existing works. DRL is a learning-based algorithm which has the most effective aspects of the proposed approach to improve the performance of system based on the right values and combining with blockchain in terms of security of smart home based on the smart devices to overcome sharing and hacking the privacy. We have compared our proposed system with the other state-of-the-art and test this system in two types of datasets as NSL-KDD and KDD-CUP-99. DRL with an accuracy of 96.9% performs higher and has a stronger output compared with Artificial Neural Networks with an accuracy of 80.05% in the second stage, which contains 16% differences in terms of improving the accuracy of smart homes.

A Secure Internet of Things Smart Home Network: Design and Configuration

Many home IoT devices are joining IoT networks by gaining access to some home gateway that configures smart, multimedia, and home networks. To enable secure IoT-based home networking services, (1) an IoT network should be effectively designed and configured with a IoT server, (2) a messaging protocol is required to exchange information between the IoT server and IoT devices, and (3) the home gateway should monitor all safety aspects in both inbound and outbound traffic of the home network. However, not all home network users put in consideration the need for an adequate security posture. Instead, many users still rely on the minimum home network security by setting an easiest-to-guess password to restrict unauthorized access to their home gateway. In this paper, we propose a network design and configuration that enables secure IoT services with MQTT messaging protocol for home networks. With the proposed network design, a home network is interconnected to external networks through a home gateway. To separate the IoT-subnet from other parts of home network, the home gateway subdivides a home network into an inside-subnet and an IoT-subnet with a private IP address using subnet masking. The IoT server, located in the IoT-subnet can be implemented with either a general HTTP server or a security server that acts as an MQTT broker. The secure communications among network entities are governed by a home gateway operating a well-configured extended access control. The effectiveness of the proposed design and configuration is verified through a simulation by showing that it does not impose any significant performance degradation for reinforced security. We expect the proposed configuration to help facilitate interconnection among heterogeneous network entities.

A Review on IoT Based Smart Security And Home Automation

Recent advances in smartphones and affordable open-source hardware platforms have enabled the development of low-cost architectures for Internet-of-Things (IoT)-enabled home automation and security systems. These systems usually consist of sensing and actuating layer that is made up of sensors such as passive infrared sensors, also known as motion sensors; temperature sensors; smoke sensors, and web cameras for security surveillance. These sensors, smart electrical appliances, and other IoT devices connect to the Internet through a home gateway. This project is based on implementation of an IoT based home security system, to be able to control entrance from anywhere in the world is the major aim of this project and at same time it should be secured, and this was achieved with the use of Internet of things and some other electronics components. An automatic door control system working through a mobile app and also through a keypad was achieved. IoT refers to the infrastructure of connected physical devices which is growing at a rapid rate as a huge number of devices and objects are getting associated with the Internet. Home security is a very useful application of IoT and we are using it to create an inexpensive security system for homes as well as industrial use.

A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation

Internet of Things (IoT) technologies are already playing an important role in our daily activities as we use them and rely on them to increase our abilities, connectivity, productivity and quality of life. However, there are still obstacles to achieving a unique interface able to transfer full control to users given the diversity of protocols, properties and specifications in the varied IoT ecosystem. Particularly for the case of home automation systems, there is a high degree of fragmentation that limits interoperability, increasing the complexity and costs of developments and holding back their real potential of positively impacting users. In this article, we propose implementing W3C’s Web of Things Standard supported by home automation ontologies, such as SAREF and UniversAAL, to deploy the Living Lab Gateway that allows users to consume all IoT devices from a smart home, including those physically wired and using KNX® technology. This work, developed under the framework of the EC funded Plan4Act project, includes relevant features such as security, authentication and authorization provision, dynamic configuration and injection of devices, and devices abstraction and mapping into ontologies. Its deployment is explained in two scenarios to show the achieved technology’s degree of integration, the code simplicity for developers and the system’s scalability: one consisted of external hardware interfacing with the smart home, and the other of the injection of a new sensing device. A test was executed providing metrics that indicate that the Living Lab Gateway is competitive in terms of response performance.