Please use this identifier to cite or link to this item:
Title: EnAcq: Energy-efficient location data acquisition based on improved map matching
Keywords: GPS, Trajectory Data, Map matching, Energy-efficiency
Issue Date: 7-Jun-2011
Citation: FANG SHUNKAI (2011-06-07). EnAcq: Energy-efficient location data acquisition based on improved map matching. ScholarBank@NUS Repository.
Abstract: With location data becoming an important sensor data resource for a broad range of trajectory-based applications on mobile devices such as vehicle tracking, route navigation, and video tagging, location data acquisition schemes that can reduce the amount of energy spent but still provide accurate location information are essential for these applications' feasibility. This thesis presents EnAcq, a novel energy-efficient location data acquisition scheme based on improved map matching that addresses two key challenges: inaccurate trajectory data and energy consumption. To improve the accuracy of the trajectory data, it utilizes an improved Hidden Markov Model (HMM)-based map matching algorithm which can find candidate matches for each sample point without using a range query and determine the most likely route the vehicle has travelled. To avoid unnecessary energy consumption, it adopts an adaptive GPS sampling method which adjusts the GPS sampling period based on the vehicle's current motion state. Three experiments are performed on a public real-world dataset for evaluating our improved map matching algorithm, adaptive sampling method and proposed EnAcq scheme, respectively. The experimental results show that when the GPS sampling period is not too long, our improved map matching algorithm significantly outperforms a recently proposed HMM-based map matching algorithm in terms of running time. Meanwhile, when compared with sampling at a fixed rate, our adaptive sampling method saves a significant amount of energy, hence prolonging a mobile device's battery life. Furthermore, the results of the third experiment indicate clearly that EnAcq still can provide accurate trajectory data without consuming much energy.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Thesis_Fang Shunkai.pdf8.04 MBAdobe PDF



Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.