ABS TRACT:The past few years have seen wide spread adoption of outdoor positioning services, mainly GPS, being incorporated into everyd ay devices such as smartphones and tablets. While outdoor positioning has been well received by the public, its indoor counterpart has been mostly limited to private use due to its higher costs and complexity for setting up the proper environment . The objective of this research is to provide an affordable mean for indoor localization using wireless local area network (WLAN) Wi-Fi technology. We combined two different Wi-Fi approaches to locate a user. The first method involves the use of matching the pre-recorded received signal strength (RSS) from nearby access points (AP), to the data transmitted from the user on the fly. This is commonly known as "fingerprint matching". The second approach is a distance-based trilateration approach using three known AP coordinates detected on the user"s device to derive the position. The combination of the two steps enhances the accuracy of the user position in an indoor environment allowing location-based services (LBS) such as mobile augmented reality (M AR) to be deployed more effectively in the indoor environment. The mapping of the RSS map can also prove useful to IT planning personnel for covering locations with no Wi-Fi coverage (ie. dead spots). The experiments presented in this research helps provide a foundation for the integration of indoor with outdoor positioning to create a seamless transition experience for users.
Although location estimation algorithms based on signal attenuation may not be the most promising approach for providing location services, signal strength is the only common attribute available among various kind of mobile network. Together with the fact that the cell layout in metropolitan areas like Hong Kong is different from other smaller cities, this paper is an investigation and a revisit in search of a set of location estimation algorithms based on signal attenuation.With the technical support from a local mobile operator, we have constructed and conducted several real world experiments for our investigation and results are promising.
A dual channel system 1 2 , which is based on the GPS and the GSM Network, is being developed to compensate the problem of the lost of GPS signals in providing location services to mobile users in urban areas. In this design, when GPS signals are being blocked in blind spot areas, GSM positioning algorithms would be used as an alterative method to provide location estimations. This research is an investigation in search of a set of location estimation algorithms based on signal attenuation to work with GPS, so as to develop a dual channel positioning system. With the technical support from a local mobile operator, we have constructed and conducted several real world experiments for our investigation and results are promising.
ABSTRACT:A web-based system based on the 3DTown project was proposed using Google Earth plug-in that brings information from indoor positioning devices and real-time sensors into an integrated 3D indoor and outdoor virtual world to visualize the dynamics of urban life within the 3D context of a city. We addressed limitation of the 3DTown project with particular emphasis on video surveillance camera used for indoor tracking purposes. The proposed solution was to utilize wireless local area network (WLAN) WiFi as a replacement technology for localizing objects of interest due to the wide spread availability and large coverage area of WiFi in indoor building spaces. Indoor positioning was performed using WiFi without modifying existing building infrastructure or introducing additional access points (AP)s. A hybrid probabilistic approach was used for indoor positioning based on previously recorded WiFi fingerprint database in the Petrie Science and Engineering building at York University. In addition, we have developed a 3D building modeling module that allows for efficient reconstruction of outdoor building models to be integrated with indoor building models; a sensor module for receiving, distributing, and visualizing real-time sensor data; and a web-based visualization module for users to explore the dynamic urban life in a virtual world. In order to solve the problems in the implementation of the proposed system, we introduce approaches for integration of indoor building models with indoor positioning data, as well as real-time sensor information and visualization on the web-based system. In this paper we report the preliminary results of our prototype system, demonstrating the system's capability for implementing a dynamic 3D indoor and outdoor virtual world that is composed of discrete modules connected through pre-determined communication protocols.
A dual channel system, which is based on the GPS and the GSM Network, is being developed to compensate the problem of the lost of GPS signals in providing location services to mobile users in urban areas. In this design, when GPS signals are being blocked in blind spot areas, GSM positioning algorithms would be used as an alternative method to provide location estimations. This research is an investigation in search of a set of location estimation algorithms based on signal attenuation to work with GPS, so as to develop a dual channel positioning system. With the technical support from a local mobile operator, we have constructed and conducted several real world experiments for our investigation and results are promising.
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