A Dynamic UI Remote Control APP based on Pedestrian Dead Reckoning

NCUIR > College of Electrical Engineering & Computer Science > Executive Master of Computer Science and Information Engineering > Electronic Thesis & Dissertation > Item 987654321/74627

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/74627

Title:	A Dynamic UI Remote Control APP based on Pedestrian Dead Reckoning
Authors:	許良宇;Hsu, Liang-Yu
Contributors:	資訊工程學系在職專班
Keywords:	遠端控制;SRCS;Remote control;PDR
Date:	2017-05-24
Issue Date:	2017-10-27 14:34:21 (UTC+8)
Publisher:	國立中央大學
Abstract:	現今每個家庭普遍擁有多個遠端控制器，尋找不同的遙控器變成使用者的負擔。為了解決這個問題，我們提出了智慧遙控系統(a smart remote control system, SRCS)。SRCS的主要概念分為兩個步驟，第一步，SRCS透過行人航位推算(pedestrian dead reckoning, PDR)系統建立行人的位置並且量測目標裝置的座標。第二步，SRCS使用這個資訊決定遠端遙控器是否指向該裝置。如果SRCS發現該裝置，則使用介面以及按鈕隨著目標裝置而調整。為了評估SRCS的可行性，我們在Android智慧手機上建立程式並加以實驗。實驗結果顯示當兩個裝置被隔離超過120公分時，SRSC可以有效的減少判斷錯誤。;Indoor localization has become a popular issue in recent years. Most of the indoor localization approaches either require the availability of an infrastructure or the additional training efforts. The traditional pedestrian dead reckoning (PDR) system can be implemented on mobile devices without additional cost and training. However, it accumulates errors quickly and leads to unacceptable results after a short period of time. To address this issue, we propose the ultrasound-based collaborative pedestrian dead reckoning (UCPDR) system. The main idea of UCPDR is to reduce the estimation error of a pedestrian′s location by two steps: First, UCPDR estimates the pedestrian′s location based on another nearby pedestrian′s location information obtained by PDR and the distance information obtained by ultrasound signals exchanged by the two pedestrians; second, it reduces the error estimation through the opportunistic Kalman filter by using the previous location estimation as a new measurement. In addition, the backward correction scheme is used to improve the accuracy of user′s trajectory. To evaluate feasibility of UCPDR, a prototype is built on the iOS (iPhone Operating System) platform. The results of conducted experiment show that UCPDR is able to limit the localization error within 2m (when number of steps is less than 80) after a long period of time through the help of neighbors′ location information and ultrasound distance information. Our UCPDR system always achieves a better localization accuracy than the traditional PDR system.
Appears in Collections:	[Executive Master of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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