Studies conducted on resource management in wireless sensor networks have identified energy efficient routing protocols as one of the energy saving mechanisms that can be used to manage the consumption of networks’ available energy and extend network lifetime. Routing protocols assist in finding paths for transmission of sensed events, and they must be able to extend the lifetime of a network despite some of the limitations of sensor nodes in a network and the harsh environments in which the sensor nodes are to operate. In this paper, we survey and compare existing routing protocols in wireless sensor networks. We start by introducing the different solutions that can be used to improve the network lifetime and focus on energy efficient routing protocols as the area of the survey, in addition to network topology modeling. We also model the network regarding energy consumption, sensing and event extraction analysis in the network. Categorization of the routing protocols into homogeneous and heterogeneous was performed, for which, sub-classification into static and mobile and other behavioral patterns of the routing protocols was done. The second phase of the paper presents models and simulations of selected routing protocols and comparisons of their performances. We conclude this paper by discussing future work directions with highlights on some futuristic applications.

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.

The most challenging issue in the design of wireless sensor networks for the application of localization in the underground environment, mostly for miner’s location, is the sensor nodes’ energy consumption, efficiency and communication. Underground Wireless Sensor Networks are active and promising area of application of Wireless Sensor Networks (WSNs), whereby sensor nodes perform sensing duties in the underground environment. Most of the communication techniques used in the underground environment experience a high path loss and hence, hinders the range needed for transmission. However, the available option to increase information transmission is to increase the transmission power which needs large size of apparatus which is also limited in the underground. To solve the mentioned problems, this paper proposed a Magnetic Induction based Pulse Power. Analytical results of the Magnetic Induction based Pulse Power with an ordinary magnetic induction communication technique show an improvement in Signal-to-Noise Ratio (SNR) and path loss with variation in distance between nodes and frequency of operation. This paper further formulates a nonlinear program to determine the optimal data (events) extraction in a grid based WUSNs.

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 % .

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