Hey everyone, thanks for coming back to Wi Fi fundamentals with location and analytics. This course will help you to master the air. We have gone through our society distance equation. And now it's time for a more accurate technique. The IRS assigns fingerprint as in our home space utilization video, our assigned fingerprint can be done through empirical approach, a simple site survey carried by a professional or even your Android phone. For rssi fingerprint we will measure distances from access point to stations more accurately and save them to a database, which later on we will correlate to each our society reading our fingerprint map would be done in a square room, five meters long and seven meters wide.
Installed three access points in different positions in the area and record their placement. As in our example, access point one is positioned at the zero origin point. Now divide the space into grid points, grid points doesn't have to be the same size. walk into the room and start collecting our society data in different reference points based on the readings of your access points. The readings will be used as a data set for future readings. You can make your own rssi map using your Android device or laptop.
Move around the area starting from access point to One and start collecting a data set from each reference point. That will include the rssi value from access point one, two, and three. For each grid point, repeat the measurements several times and gather rssi values plus noise. They represent a unique fingerprint. rssi values on the grid are usually grouped and analyzed by professional rssi gathering utility. But for our experiment, it can be inserted into an Excel sheet in Google Sheets, or which app that you choose.
Congratulations, your map is done. And whenever a station enters the area, it's life our assess readings are completed. To your radio map data set and its position is clear. Creating a radio map is time consuming radio environment is hostile. And if the environment changes due to furniture moving overcrowded by people, the rssi values can also change. different vendors smartphone vendors PC vendors also implement different chipset, thus different rssi values.
As you will see correlation between signal strength and distance is not linear. As distance grow, we see more rssi fluctuations, try to keep the map updated. And coming up in our next video. How do we use machine learning algorithms to make our readings even more accurate? We will look at the K nearest neighbors. See you soon.