• Energy Research

Due to human influence and its negative impacts on the world's environment, the world is changing into a cleaner and more sustainable energy system. In both private and public buildings, there is a desire to reduce electricity usage, automate appliances, and optimize the electricity usage of a building. This paper presents the design and implementation of a secured smart home switching system based on wireless communications and self-energy harvesting. The proposed secured smart home switching system integrates access control of the building's electricity, energy harvesting, and storage for the active electronic components and circuitries, and wireless communication for smart switches and sockets. The paper gives two contributions to the design of smart home systems: 1) A practical design and implementation of security (access control system) for a building's power supply which adds a locking feature such that only authorized personnel are capable of altering the power state of the smart sockets and switches in a building, and; 2) A model of energy harvesting and storage system for the active electronic components of the circuitries and wireless communication for smart switches and sockets. The access control involves four stages (a control unit, a comparator unit, a memory unit, and the switching unit). The access control system provides means of access control by having a security keypad that switches ON or OFF the building's electricity, provided the user knows the security pin code (8 coded pins). The proposed system also harvests and stores energy for all the active electronic devices using a photovoltaic system with ultracapacitor energy buffer. The designed secured smart home utilized smart power and switches, and message queuing telemetry transport for ease of controlling energy usage. The experimental results obtained from extensive testing of the prototype shows an improvement in security and energy management in a building.

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>This paper investigates the feasibility of Timed Efficient Stream Loss-tolerant Authentica- tion to serve security needs of Power Line Communication (PLC) system. PLC network has been identified as the ideal choice to function as the last mile network, deliver load management messages to smart meters. However, there is need to address the security concerns for load management messages delivered over power line communications. The ubiquitous nature of the power line communication infrastructure exposes load management systems (LMS) deployed over it to a security risk. Ordinarily, PLC network does not em- ploy any security measures on which the smart meters and data concentrators can depend on. Therefore, the need to provide a secure mechanism for communication of load man- agement system messages over a PLC network. In LMS, source authentication is of highest priority because we need to respond only to messages from an authenticated source. This is achieved by investigating suitable robust authentication protocols. In this paper we present modifications to Timed Efficient Stream Loss-tolerant Authentication for secure authentica- tion to secure messages for load management over PLC. We demonstrate that PLC can be used to securely and effectively deliver Load Management messages to smart meters, with minimal overhead. </span></p></div></div></div>

The objective of our work is to provide an in-depth analysis and compilation of device-level strategies for enhancing the energy efficiency of Machine-Type Communication (MTC). The necessity for such strategies stems from the growing demand for sustainable and energy-efficient communication systems in various industries. We begin by presenting a comprehensive background on MTC, detailing its essential characteristics, the architecture of machine-type devices (MTDs), and their diverse applications. Next, we explore a range of energy-efficient techniques designed to optimize key subsystems of MTDs. These subsystems include the radio for communication efficiency, processing power for computational efficiency, and sensing subsystems for data acquisition efficiency. Each technique is evaluated for its potential impact on overall energy consumption and the trade-offs and limitations associated with these techniques are also assessed. In concluding, the paper highlights potential future research directions in this domain, outlining the ongoing need for innovative solutions to meet the escalating demands of energy efficiency in MTC.

The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is a widely used method for managing energy consumption in Wireless Sensor Networks (WSNs). However, it has limitations that affect network longevity and performance. This paper presents an improved version of the LEACH protocol, termed MFG-LEACH, which incorporates the Mean Field Game (MFG) theory to optimize energy efficiency and network lifetime. The proposed MFG-LEACH protocol addresses the imbalances in energy consumption by modeling the interactions among nodes as a game, where each node optimizes its transmission energy based on the collective state of the network. We conducted extensive simulations to compare MFG-LEACH with Enhanced Zonal Stable Election Protocol (EZ-SEP), Energy-Aware Multi-Hop Routing (EAMR), and Balanced Residual Energy routing (BRE) protocols. The results demonstrate that MFG-LEACH significantly reduces energy consumption and increases the number of packets received across different node densities, thereby validating the effectiveness of our approach.

Recent surveys in the energy harvesting system for seismic nodes show that, most often, a single energy source energizes the seismic system and fails most frequently. The major concern is the limited lifecycle of battery and high routine cost. Simplicity and inexperience have caused intermittent undersizing or oversizing of the system. Optimizing solar cell constraints is required. The hybridization of the lead-acid battery and supercapacitor enables the stress on the battery to lessen and increases the lifetime. An artificial neural network model is implemented to resolve the rapid input variations across the photovoltaic module. The best performance was attained at the epoch of 117 and the mean square error of 1.1176e-6 with regression values of training, test, and validation at 0.99647, 0.99724, and 0.99534, respectively. The paper presents simulations of Nsukka seismic node as a case study and to deepen the understanding of the system. The significant contributions of the study are (1) identification of the considerations of the PV system at a typical remote seismic node through energy transducer and storage modelling, (2) optimal sizing of PV module and lead-acid battery, and, lastly, (3) hybridization of the energy storage systems (the battery and supercapacitor) to enable the energy harvesting system to maximize the available ambient irradiance. The results show the neural network model delivered efficient power with duty cycles across the converter and relatively less complexities, while the supercapacitor complemented the lead-acid battery and delivered an overall efficiency of about 75 % .