Wireless Device Location Sensing In a Museum Project

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Wireless Device Location Sensing In a Museum Project Tanvir Anwar Sydney, Australia Email: tanvir.anwar.australia@gmail.com Abstract Dr. Priyadarsi Nanda School of Computing and Communications Faculty of Engineering and IT University of Technology, Sydney, Australia Email: priyadarsi.nanda@uts.edu.au Indoor navigation can be implemented with Bluetooth technology as sensors. We use RTT (Round Trip Time) as an attribute towards the navigation of an object. Designing the scheme for indoor networks with the introduction of pre-fixed co-ordinates has been used as a database. This paper presents a new algorithm that incorporate real life signal strength measurement from access point and peers to estimate position and distance using Bluetooth sensor network. The main feature of this paper is to see how RTT behaves with distance and then what approach we must take to make RTT more robust. We conducted several experiments to validate our proposed algorithm and study RTT behavior in real life application. Keywords: Round Trip Time (RTT), Receive Signal Strength Indicator (RSSI), Bluetooth tags, Sensor I. INTRODUCTION Location awareness is becoming the most important issne in many cases, such as when an urgent accident needs the nearest doctor in the hospital, or in the university the staff members want to check available members for a qnick meeting, or even to track an object. These are some of the important questions which certainly need fast, reliable answers by keeping the privacy as a priority. For varlous reasons localization is rapidly growing and context awareness consists of six questions involving what, who, where, when, why and how? Location awareness mainly tries to answer two of them: "where" and "who". Location sensing can be divided into indoor and outdoor awareness. Indoor systems mainly contain a set of antennas with wireless tags. The antennas communicate wirelessly with tags, which are Annual International Conference on Network Technologies & Communications (NTC 2010) Copyright GSTF 2010 ISBN: 978-981-08-7654-8 doi:l O.5176/978-981-08-7654-8,NTC201 0-35 N-49 attached to humans, or to desired position of the objects. Mobile handsets are also often personal in nature, so the statistics related to measurements reflect behavioral patterns of the user or object. We demonstrate how prototypical patterns of behavior may be found in data produced by Bluetooth scanning. It appears that cyclical nature of the patterns reflects well various daily routines of test objects. The scanning results are then sent via GPRS/ AP to a backend server for further processing for a fixed duration of time. In this project we monitor various data received to ensure that all palmtops and Bluetooth dongles attached to every item of the museum are operating properly. The data set consists of phone ID, timestamp, and MAC address. Some of detected MAC address corresponds to known locations (location of every items of museum). Location evaluation is performed by sensing Bluetooth signal strength with a reference model based approach. We discuss problems which arise when the Bluetooth Received Signal Strength Indicator (RSSI) is used as a measurement of signal strength and propose a novel access point technique based on such data. This access point allows the reading of a wider range of signal strengths using RSSI [1] [2]. This paper is organized into seven sections. Section I gives the introduction. Section II presents an overview of the architecture while section III identifies parameters making RTT as a strong candidate for improvement on localization technique. Section IV and V presents various aspects of Bluetooth protocol and how the database can be accessed. Our proposed algorithm and results of the experiments are giveu in Section VI. We conclude our work in Section VII.