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| 008 | 100209s2008 th uu|m rtt 0| a1eng d | ||
| 035 | _a.b12072783 | ||
| 099 | 9 | _aAIT Diss. no.RS-08-02 | |
| 100 | 0 | _aWutjanun Muttitanon | |
| 245 | 1 | 3 | _aAn indoor positioning system (IPS) using wireless LAN (WLAN) |
| 260 |
_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2008 |
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| 300 |
_a100 p. : _bill. + _e1 online resource |
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| 490 | 1 |
_aDissertation ; _vno. RS-08-02 |
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| 500 | _aA dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Technical Science | ||
| 502 | _aThesis (Ph.D.) - Asian Institute of Technology, 2008 | ||
| 520 | _aTo date many positioning systems are available to determine or track a user's location; three main categories include global positioning system (GPS), wide area location system and indoor positioning system. The GPS technology is being utilized in numerous military and civil applications. It enables the sensors to acquire specific reference in time and position. The system works poorly in areas where the satellites do not have good coverage. For indoor positioning system many approaches like infrared sensing, radio frequency, ultrasonic are proposed; each of these methods has their own advantages and disadvantages. Considering cost-effectiveness, speed and accuracy a recent interest is growing on using wireless technology, to find alternatives and accuracy for indoor location system using WLAN. A wireless local-area network (WLAN) based positioning system has some distinct advantages like low-cost and wider area coverage. This study proposes a system to determine the location of a mobile terminal in high speed, low-cost. The goal is to build a location determination system that is able to find out the user or device location wireless networks by using the wireless communications infrastructure, 802.11 standard access points. The experimental set up used an indoor wireless facility of an auditorium, Asian Institute of Technology, where signals strength were from three access points (APs) were measured and recorded to train a position determination model to calculate and map a position of the user or device location. The WLAN indoor positioning system is designed to operate on handheld devices such as PDA. Several positioning models were applied to calculate the position of a client using two methods: regression method and empirical method and. The regression method included linear model, polynomial model and exponential model that are model-based signal propagation distribution training of the signal strength, and convert signal strength to a distance measurement. With information about the coordinates of the access points, the Trilateration method can be used to compute the position of the device location or user location. And the empirical method included neural network model and grid model, that the signal strengths are collected and available in each cell is used for estimating the position of the user position or device location. The system is concerned with developing precise method for determining the user position with less requirements. At the end a comparison was made on the resulted positions of the client obtained from both methods, regression and empirical methods. A handheld PDA equipped with application software was the client device. OpenNav is the software-based design developed to operate on Windows CE operation system. The application which was written in visual basic.NET languages contains the application that is capable to scan, detect, and measure signal strength from several access points and display their information and identifying position of the device in relation to the indoor environment, using signal information of surrounding access points, a pre-constructed radio map and a mathematical algorithm. The results show that the OpenNav system is able to achieve accuracy significant better than the other system. The accuracy assessment has been performed to identify the distance errors, and the average distance error was found lowest for the grid empirical model. The results of the experiments reveal that the accuracy ranges 0.5 - 4 m can be achieved. The Wireless LAN deployment is expected to continue to develop, the outcome might be showing what it could be a popular and an low-cost solution by using the existing facility for mobile indoor positioning system. In further, the more intelligent algorithms are to be developed and placed in devices with more than one RF to make several choices of best operation. The noisy characteristics and the surrounding environment are the obstacle of the location determination using WLAN. The specification of the equipment is needed to be concern. More data need to be collected and analyzed to establish intelligent algorithms. | ||
| 650 | 0 | _aGlobal Positioning System | |
| 650 | 0 | _aWireless LANs | |
| 700 | 1 |
_aTripathi, Nitin Kumar, _eChairperson |
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| 700 | 1 |
_aSouris, Marc, _eExamination committee |
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| 700 | 1 |
_aRajatheva, R.M.A.P, _eExamination Committee |
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| 710 | 2 |
_aMahidol University, _eScholarship donor |
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| 810 | 2 |
_aAsian Institute of Technology. _tDissertation ; _vno. RS-08-02 |
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| 856 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B00745 |
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