Patient Location via Received Signal Strength (RSS) Analysis D. Albano, C. Comeau, J. Ianelli, S. Palastro Components Hardware Pre-existing b infrastructure with at least 3 AP’s Software Rmapr, a radio map generator - generates a location-specific radio map Creates radio map of a location by recording RSS values of reference AP’s at many points in the area Generates a list with the form (x, y, RSS 1, RSS 2, RSS 3, RSS 4, RSS 5 ) As map density increases, accuracy increases, but set-up time increases as well Radio map is stored in server Trakr, the main end-user program - compares real-time RSS values with radio map data to approximate location As user moves, the software reads the RSS values of nearby AP’s These RSS values are compared to the radio map The closest match from the radio map is loaded and the location data is read This data is interpreted by the software and updated in the GUI The Viterbi algorithm allows us to predict the path and location of the user from the observed changes in signal strength Makes use of a moving average estimation Predicts current/future path based on past movement Acknowledgments Thanks to the generous gift of Drs. Hal Wrigley and Linda Baker, the Bioengineering Department, Dr. Taieb Znati for his time, effort, and funding, the Computer Sciences Department, Bob Hoffman for network access and troubleshooting, and Anandha Gopalan for Linux advice and code troubleshooting. Abstract The goal of this project is to become familiar with and succeed in implementing a successful location- aware computing network. This position-tracking network will be RSS (Received Signal Strength) based and will be used to determine the precise positions of moving objects in a given space. Initially, the recreation of a previously established system will be the main priority of the project. The positioning network will be implemented by using wireless access points (AP's) and laptop computer. After the signal strength is received and logged in the wireless device, the position of the laptop will be calculated using a triangulating algorithm. A “radio-map” of the sample space will also be constructed using both (x,y) coordinates and RSS values from five of the AP's. After mapping the sample space, the mobile device will also be able to be located via comparison with the database of the various radio-map coordinates. The software will then be calibrated to achieve a certain level of accuracy within a tolerable range. After the initial goal is realized, the technology will then be implemented onto smaller, more mobile devices such as PDAs and the process will be repeated. The system will then transmit data to a server, and the server will be used to pinpoint the locations of multiple wireless devices in the sample space. If successful, multiple GUIs (Graphical User Interfaces) will be adapted to both the mobile devises and the server in order to make the system as user-friendly as possible. Time permitting, additional features will be added to the system, and the transfer of information between server and mobile nodes will also be implemented to add longevity to the network. Design Approach We have chosen a design approach that will expand upon what has already been accomplished in the field of location-aware computing. We first intend to replicate the works of the Microsoft project. We are taking on the same design approach as they did by using an b infrastructure using five access points strategically located throughout the floor of an office building. We are then going to construct a radio map; a database consisting of all the received signal strengths and (x,y) coordinates of the floor. We intend to then use this radio map as one of the ways of location detection by taking the five received signal strengths given from the access points and looking for (x,y) coordinate pair that matches with those strength readings. To elaborate, we intend to place the access points in the orientation shown in Figure 1 to the right, with the test bed being the fifth floor of the Sennot Square building. The test AP's are Linksys 55AG and the test computer will be a Lenovo ThinkPad X60 Tablet PC with an Atheros a/b/g/n Wireless LAN Mini-PCI Express Adapter network interface card. The software application is coded in C++ using Wireless Researcher’s Application Programming Interface (WRAPI) to extract the RSS values from the NIC. We are using WRAPI because it is non-hardware specific, and thus we have the freedom to perform this on any mobile device with an b compatible wireless NIC. Once this experiment is carried out successfully, the software used on the laptop will then be translated over to a PALM mobile device. This will allow for a more “real system” involving a true mobile device that is in use in today’s society. If successful, we will expand on this simple design and create a user- friendly GUI for the applications on both the mobile device and the server. We will also develop, compare, and combine other methods of location detection in order to make the application as accurate as possible. The algorithm will be tuned to produce the most accurate results possible, and additional features to the system (including data transfer) will be added if time permits the work (01,01) <--(x,y) Coordinate pair with AP1 = -12, AP2 = -34, AP3 = -56, AP4 = -78, AP5 = -90 dBm (01,02) <--Coordinate pair with AP1 = -23dBm, etc … //This is the radio map of the 5th floor of Sennot square starting in the northwest corner //with the positive x direction being east and positive y direction north. We took points every //step and our map is outlined visually. Each point is represented by five RSS values //of five access points. Each gives us a RSS in -dBm (we have truncated -100 or less to -99). //These represent the first ten digits of the line. The last four digits are the x,y //coordinate pairs that will be referenced via the map to approximate location. Notes: If the last RSS string ending in zero (i.e. the AP5 has an RSS of 90, etc.), the reference will not find it, as the compare statement will consider it a null character. Radio Map Example Figure 1. Simplified overhead view of 5 th floor Sennot Sq. The five AP locations are shown in each corner and the center of the floor. Figure 2. Example window outputs of the Trakr command-line program back-end. A dynamic, graphical GUI front-end is in development for Windows, Linux, and Palm OS™.