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Wireless Sensor Network has been widely used in remote monitoring application. However, energy efficiency of sensor nodes is an important issue, as they are powered by batteries. And most of the cases, sensor nodes are inaccessible once they have been deployed. So a good energy saving scheme of sensor nodes will provide long operational life (2-3 years). In this paper, Dynamic Voltage Scaling (DVS) is proposed to reduce the CPU energy by adjusting the voltage level based on its workload prediction. The workload prediction is based on Linear Prediction model.

The wireless network technology is increasingly important in healthcare as a result of the aging population and the tendency to acquire chronic disease such as heart attack, high blood pressure amongst the elderly. The elderly do not have to show up to the hospital for a blood pressure check. It can be done while they are working by wearing wireless sensor device at home. A wireless sensor network system that has the capability to monitor physiological sign such as SpO2; saturation of arterial oxygen and heartbeat rate in real-time from the human body is highlighted in this study. This research is to design a prototype snesor network hardware, which consists of microcontroller PIC18F series and transceiver unit. The sensor is incorporated into a wearable body sensor network which is small in size and easy to use. The sensor allows a non-invasive, real time method to provide information regarding the health of the body. This kind of medial application such as wireless sensor network has a promising future for humankind. This enables a more efficient and economical means for managing the healthcare of the population.

The recent decades have seen the increase in demand for reliable and clean form of electricity derived from renewable energy sources. One such example is solar power. The challenge remains to maximize the capture of the rays from the sun for conversion into electricity. This paper presents fabrication and installation of a solar panel mount with a dual-axis solar tracking controller. This is done so that rays from the sun fall perpendicularly unto the solar panels to maximize the capture of the rays by pointing the solar panels towards the sun and following its path across the sky. Thus electricity and efficiency increased.

Remotely control applications over a wide area had been commonly used in the industries today. One of the common applications requires remote control and monitoring is inverter fed induction drive system. Drive system has various types of controller, in order to perform some actions such as control the speed, forward and reverse turning direction of the motor. This approach can be done by Programmable Logic Controller (PLC), and with the rise of the technology, Ethernet module will be used in order to achieve the remote con-trol system. Plus the PLC today can be controlled not only using its original software, but 3rd party software as well, such as LabVIEW. LabVIEW is a human machine interfaces design software that is user friendly. It can be easily communicate with different hardware.

PIC is a family of Harvard architecture microcontrollers made by Microchip Technology, derived from the PIC1640 originally developed by General Instrument's Microelectronics Division. The name PIC initially referred to "Peripheral Interface Controller". PICs are popular with the developers and the hobbyists due to their low cost, wide availability, large user base, extensive collection of application notes, free development tools, and serial programming (and re- programming with flash memory) capability. In modern days, PIC microcontrollers are used in the industrial world to control many types of equipment, ranging from consumer to specialized devices. They have replaced older types of controllers, including microprocessors. Also, there is a growing need for off-line support of a computer’s main processor. The demand is going to grow with more equipment uses more intelligence. In the engineering field for instance, PIC has brought a very positive impact in designing an automation control system and controlling industrial machineries. Accordingly, this paper shows the change in the motor speed by the use of PIC in accordance to the light and level of temperature. The project focuses on programming the PIC by embedded software that detects the temperature and light signals and send it to 3 phase induction motor of 240 volt. A theoretical analysis and the practical approach in achieving this work goal have proved that PIC plays an important role in the field of electronics control.

Fluorescent lamps have proven to be the most efficient lighting device. However, energy losses have been found in electromagnetic ballast due to high harmonic distortion and low power factor so energy is consumed unnecessarily. In today's energy demanding environment, energy efficiency of fluorescent lamps can be improved by introducing an energy saving controller in the electromagnetic ballast. The energy saving controller limits the supply voltage to an optimum level which tends to reduce the power losses in electromagnetic ballasts and fluorescent lamps. It is also anticipated that the energy saving controller has desirable characteristics of high power factor with dimmable illuminance level control. In comparison to electronic dimmable ballast, integration an energy saving controller with electromagnetic ballast fluorescent lamps results in less power consumption, dimmable illuminance control and longer life span at a much lower installation cost.Furthermore, there is no replacement cost for integrating the energy saving controller with existing electromagnetic fluorescent lamps system. In this paper, experimental works have been performed to investigate hardware implementation of the system which further supported by simulation on MATLAB Simulink. Experimental results based on the proposed energy saving controller showed that electromagnetic ballast fluorescent lamps can be dimmed without any problems down to 50% illuminance level output. In addition, experimental results show that 37.5% power consumption can be saved by reducing 15% of the supply voltage.

Many single and three-phase converters are well developed, and covered up in most of electric markets. It is used in many applications in power systems and machine drives. However, an exact definite output signal from the dc side still not recognized. The waveforms of output voltage and current demonstrate an imperfect dc signal and constitute losses, harmonic distortion, low power factor, and observed some ripples. An approximately perfect rectifier bridge is the aim of this research. Perhaps it gives the ability to identify the parameters of the converter to obtain, as much as possible, a perfect dc signal with less ripple, high power factor and high efficiency. Design is implemented by simulation on Power Simulator PSIM, and practically, a series regulator LM723 is applied to provide regulating output voltage. Comparisons of both simulation and hardware results are made to observe differences and similarities.

The body sensor nodes armed with a MSP430 microcontroller, a IEEE 802.15.4 radio chip, a memory flash and an electronic amplifier circuits is proposed as an educational platform for electronic design and embedded system courses. The body sensor nodes are designed based on a commercial wireless sensor network (WSN) device that contains the microcontroller, radio chip and memory flash in a single platform. The WSN device also supplies the connection pins for I/O signals, ADC, SPI and UART functionalities, to control an electronic amplifier circuit. For electronic design courses, the ease of creating the body sensor node, will be hard to resist by the students. An electronic amplifier is designed and fabricated by the students in the laboratory in the electronic design courses. The WSN device is stacked on the top of the electronic amplifier circuit to prototype a new body sensor node. For the embedded system course students, the unique properties of TinyOS used as the operating system for the body sensor node allowed the students see the effects of the software in short time.

In this paper, the S-curve membership function methodology is used in a reallife industrial problem in which there are various products, each of which requires a certain mix of raw materials selected from a set of available raw materials. This problem occurs in the chocolate manufacturing industry where decision makers and implementers play important roles that enable successful manufacturing of the products in an uncertain environment. The analysis in this paper tries to find a solution that helps a decision maker when deciding on what to implement. This problem is considered because it can be modeled with the help of fuzzy parameters (for example, the availability of raw materials is not always certain, and so can be treated as a fuzzy parameter). With 29 constraints and 8 variables the problem here is sufficiently large for the S-curve methodology employed because this methodology is applicable to problems with as few as 1 constraint and 1 variable. A decision maker can specify which vagueness parameter α is suitable for achieving a revenue which through the analysis results in an initial solution that can be implemented. From the results of this implementation the decision maker can then suggest some possible and practicable changes in fuzzy intervals for improving the revenue. Within the framework of the analysis this interactive process has to go on between the decision maker and the implementer until an optimum solution is achieved and implemented.

This chapter proposes a new method to obtain optimal solution using satisfactory approach in uncertain environment. The optimal solution is obtained by using possibilistic linear programming approach and intelligent computing by MATLAB?. The optimal solution for profit function, index quality and worker satisfaction index in construction industry is considered. Decision maker and implementer tabulate the final possibilistic and realistic outcome for objective functions respect to level of satisfaction and vagueness for forecasting and planning. When the decision maker finds the optimum parameters with acceptable degree of satisfaction, he/she can apply the confidence of gaining much profit in terms of helping the public with high quality and least cost products. The proposed fuzzy membership function allows the implementer to find a better arrangement for the equipments in the production line to fulfill the wanted products in an optimum way.

This paper describes the optimization of a hybrid energy system model. Currently in Sarawak, people living in the rural areas still depend on diesel generators to generate electricity. This increases the demand for fossil fuel, creates noise pollution and toxic gas is emitted to the environment. Hence, hybrid energy systems were introduced to replace this conventional energy system as well as improving the living standard in the villages. In this paper, several hybrid energy system configurations were investigated in order to find out the most cost effective hybrid system through Hybrid Optimization Model for Electric Renewability (Homer) software. Homer simulates, optimizes, and analyzes the sensitivity variables for each of the system configurations.