Ubiquitous techniques and applications for smart mobility

Abstract

Smart mobility technologies and applications have dramatically influenced our daily lives. To name just a few, these include the green sustainability, environmental monitoring, healthcare, energy managements, building and home automation ... etc. The need for mobility has tied in closely with wireless systems to provide users with high-quality, flexible, and cost-effective telecommunications network connectivity. It is evidenced that smart mobility will impact the business infrastructure as well as the way of businesses operation. For instance, BCC research has forecasted that the global telemedicine market alone will reach a market size of $27.3 billion in 2016 at a compound annual growth rate (CAGR) of 15.8% from 2009 to 2016. Bearing in mind that telemedicine is only one of the potentially applications only, there is no doubt that there are huge potential markets in smart mobility. As captioned, this investigation concerns smart mobility. Hence, the most common architectures of wireless circuits for mobility were investigated. Since ZigBee is one of the popular wireless protocols that offers mesh capability, it is chosen as a fundamental study. With slight tuning, the circuits can be applied to other potential usages, such as Bluetooth, Z-wave etc. To render the investigation “smart”, important and yet smart schemes in a few key areas of application have been developed. The developed schemes include localization, healthcare and energy efficiency. The development and analysis of these smart mobility schemes will be reported. Firstly, a new RF circuit designs for improving the wireless system performance will be reported. The design consists of three blocks: (i) a novel dual band low noise RF amplifier (LNA) [4-5], (ii) a high conversion gain mixer for frequency translation of RF signals into intermediate frequency (IF) [6-8], (iii) wide tuning range and low phase noise frequency oscillators (OSC) [9-11]. It is analyzed and concluded that the LNA, mixer and oscillator combination improves the overall receiver sensitivity from – 85 dBm to -107.7 dBm. As a result, the coverage range has been extended and the system reliability has been increased. Secondly, a high accuracy localization method based on an accurate multiple carriers phase noise model (Chapter 4) was designed for 4G Long Term Evolution (LTE) mobile [12]. A new LTE multiple carriers phase noise model was developed and incorporated into the path loss model. An experiment was conducted using the new noise model to evaluate the LTE mobile location in a high traffic density area in Hong Kong. Analysis and results reveal that the new localization method achieves an improvement of about 10% accuracy compared with existing widely adopted schemes. This method required no additional hardware, rendering it ideal for low cost and low system complexity applications. Thirdly, a healthcare scheme for telemedicine application was proposed and developed to provide high capacity, high mobility, low cost and high reliability within a large coverage area [13]. In this system, ZigBee network was responsible for short-distance communication (within a ward) while WiMax network was considered as the back-bone network for long haul transmission. To cope with smart application development, a new cardiovascular diseases classifier (CDC) was investigated to achieve a speedy abnormality detection [14]. This investigation incorporated the analytic hierarchy process (AHP) based multiple criteria decision analysis (MCDA) to develop feature vectors using Support Vector Machine. The MCDA facilitated the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. The cardiovascular diseases classifier (CDC) adopted the most meaningful features for identification between healthy persons versus patients with cardiovascular diseases. The proposed speedy detection of cardiovascular diseases was successfully implemented to help high risk patients to prepare for the next phase of care. The developed healthcare scheme can be adopted in telemedicine applications. Finally, a energy efficiency development was investigated. A high energy efficiency energy management scheme for parallel hybrid electric vehicles (PHEVs) had been developed [15]. In order to achieve energy saving, an adaptive genetic algorithm scheme was designed to manage adaptively the energy resource usage. The objective function of the genetic algorithm was implemented by designing a fuzzy logic controller which closely monitored and resembled the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicised data showed that the achieved efficiency of the fuzzified genetic algorithm was better by 10% than existing schemes. This method promised a mobility revolution; with minimum clean energy fuelling the driving technologies in the future.

Date of Award	15 Jul 2015
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Kim Fung TSANG (Supervisor)