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.

Intelligent power monitoring and control with wireless sensor network techniques

<span>Undoubtedly, there is a necessity for establishing a more intelligent power system in the existing energy system, which is increased according to the development of wireless system network (WSN) and the Internet of Things (IoT). This study presents intelligent power monitoring and control with wireless sensor network techniques, based on WSNs and IoT technologies is designed to manage real-time power at buildings. This system includes a complete network of wireless sensing node, base station and a smart home gateway. A sensing node is utilized as wireless sensors to measure voltage and current and to calculate power consumption of connected appliances that are transmitted wirelessly to a base station via Zigbee node. A base station is designed to receive all data transmitted from the sensing node and display it through GUI available at the personal computer with the possibility of controlling ON and OFF appliances according to consumer requirements. All of these readings are stored at database for analysis. In addition, a smart home gateway is used to connect the system with internet, allowing consumers to continuous monitoring and remote control the appliances via a smartphone application. The benefit of this system is that the mechanism of appliances control can be done in different ways (manually, automatically and remotely). To ensure better accuracy of the equipment many appliances are tested and compared with practical measurement. Best results are obtained for the error, voltage, current and the power. </span>