Mohd Norasri Ismail

A Survey on Energy-Aware Profiler for Mobile Devices

Contemporary designs for mobile devices sometimes lack of energy-aware profiler thus require an optimized use of system power. Energy-aware profiler is one of the major parts in the energy management that plays an important role to minimize energy consumption in mobile devices. Many different methods and research efforts on energy-aware profiler have been discussed and proposed during the past few years. However, there is a little effort on summarizing and providing the generic requirement for energy-aware profilers in relation to mobile devices. In this paper we review several areas of classification in energy-aware profilers that have been recommended over the recent years. Moreover, we also discuss briefly on the categories, approaches and open challenges that related to energy profiler.

Classifying content adaptation systems based on energy-aware requirements

Rapid development of mobile computing technology has led to sufficient computing and communication power to support multimedia application such as video streaming, 3D games, video conferencing and mobile TV. However, most existing mobile devices are lacking in battery life. There have been many projects focused on energy-aware content adaptation that have been designed with different goals and approaches. This paper analyzes the functional aspects on solutions that have been proposed during the last few years, to improve the energy efficiency of wireless multimedia streaming in mobile devices via content adaptation. We categorize the research work according to different classification of multimedia content adaptation based on energy-aware requirements. In addition, we discuss the research spectrum of energy-aware multimedia delivery and some challenges in energy-aware content adaptation systems.

SWM: Smart waste management for green environment

Smart Waste Management (SWM) system is a waste management system that tracks the status of fill level of trash bins equipped with ultrasonic sensors and tracks GPS-equipped trash collection trucks. The problems identified are the overflowing trash bins especially in public areas with high population density and the complaints from the residents or public complaints regarding the punctuality of trash collection trucks. The objectives of the project are to design a Smart Waste Management (SWM) system based on Bootstrap platform, develop the system and test its functionality in fulfilling the requirements of the project. The methodological approach selected in this project is the waterfall methodology in which it comprises of four crucial phases: planning and analysis, system design, system implementation and system testing whereby each phase must be completed systematically prior to the commencement of subsequent phase. It is expected that the Smart Waste Management (SWM) system would be able to fulfill all of the projects objectives. This system is aimed to address the problems of overflowing trash bins and public complaints on trash collection trucks. The development of this system brings a huge significance in which operators would be able to know which trash bins require immediate collection and request for immediate dispatch by collection trucks. This method is seen to be more efficient compared to routine collection. Operators would also be able to track the relevant dispatch trucks through this convenient system.