Modified Timed Efficient Stream Loss-tolerant Authentication to Secure Power Line Communication

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.

Design and simulation of an automatic room heater control system

This paper presents the design and simulation of an Automatic Room Heater Control system. This system allows the user to set a desired temperature which is then compared to the room temperature measured by a temperature sensor. With the help of a microcontroller, the system responds by turning ON any of the two (2) loads (Fan or a heater) automatically depending on the temperature difference. The Fan is triggered ON when the room temperature is higher than the set temperature and the heater is triggered ON when the room temperature is lower than the set temperature. The system was designed and simulated using Proteus 8, circuit building software used for building electronics system. Proteus software was used to design and simulate the main circuit, and Micro-C hex file was loaded on the Proteus schematic design. For coding the PIC Microcontroller, Micro-C compiler was used. A 5 V DC power supply was designed in order to provide a biasing voltage to most of the active devices used in the system design circuit. The DC power supply was designed and simulated using Multisim software. The system was simulated and simulation results were in accordance to the design specifications

Power-Efficient Hybrid Energy Storage System for Seismic Nodes

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%