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The latest technologies and communication protocols are arousing a keen interest in automation, in which the field of home area networks is the most prominent area to work upon toward solving the issues and challenges faced by wireless home area networks regarding adaptability, reliability, cost, throughput, efficiency, and scalability. However, managing the immense number of communication devices on the premises of a smart home is a challenging task. Moreover, the Internet of Things (IoT) is an emerging global trend with billions of smart devices to be connected in the near future resulting in a huge amount of diversified data. The continuous expansion of the IoT network causes complications and vulnerabilities due to its dynamic nature and heterogeneous traffic. In the applications of IoT, the wireless sensor network (WSN) plays a major role, and to take benefits from WSN, medium access control (MAC) is the primary protocol to optimize, which helps in allocating resources to a huge number of devices in the smart home environment. Furthermore, artificial intelligence is highly demanded to enhance the efficiency of existing systems and IoT applications. Therefore, the purpose of this research paper is to achieve an optimized medium access control protocol through machine learning. The machine learning classifier, e.g., random forest (RF) and linear regression model, is adopted for predicting the features of home area networks. The proposed technique is helpful and could overcome the demerits of existing protocols in relation to scalability, throughput, access delay, and reliability and help in achieving an autonomous home area network (HAN). [ABSTRACT FROM AUTHOR]

Because traditional electronics cannot directly use the alternating output voltage and current provided by electric field energy harvesters, harvesting systems require additional regulating and conditioning circuits. In this field, this work presents a conditioning circuit, called serial switch-only rectifier (SSOR) for low-voltage electric field energy harvesting (EFEH) applications. The proposed approach consists of a tubular topology harvester mounted on the outer jacket of a 230 V three-wires electrical cable (neutral, ground, and phase), in which terminals are connected to SSOR. We compare SSOR performance with classic electronic approaches, such as a full-bridge rectifier and voltage doubler. Experimental findings showed that the gathered energy by a 1 m cylindrical harvester increased in approximately 73.3% using the SSOR as a power management circuit. Experimental findings showed that the gathered energy by a 1 m cylindrical harvester increase in approximately 73.3% using the SSOR as a power management circuit. This increase is principally due to the fact that a serial bidirectional switch disconnects the harvester from the rest of the management circuit, enhancing the charge collection process. Although simulated results disclosed that SSOR increased collected energy for smaller-scale harvesters (experimental tests obtained using a 10 cm cylindrical harvester), additional losses in bidirectional switch reduced its performance. In addition, we introduce a comprehensive analysis of EFEH systems based on SSOR according to the mains frequency for future power systems. [ABSTRACT FROM AUTHOR]

Smart meters (SMs) are key components of the smart grid (SG) which gather electricity usage data from residences and businesses. Home area networks (HANs) are used to support two-way communications between SMs and devices within a building such as appliances. This can be implemented using power line communications (PLCs) via home wiring topologies. In this paper, a bottom-up approach is designed and a HAN-PLC channel model is obtained for a split-phase power system which includes branch circuits, an electric panel with circuit breakers and bars, a secondary transformer and the wiring of neighboring residences. A cell division (CD) method is proposed to construct the channel model. Furthermore, arc fault circuit interrupter (AFCI) and ground fault circuit interrupter (GFCI) circuit breaker models are developed. Several HAN-PLC channels are presented and compared with those obtained using existing models. [ABSTRACT FROM AUTHOR]