Impact of surrounding information on Wi-Fi sensing efficiency

One of essential parts of mobile applications using Wi-Fi is an energy-efficient Wi-Fi sensing. Lately, there have been many studies on Wi-Fi sensing algorithms using surrounding informations (e.g., bluetooth ID [1], cell ID [2] and speed [3], etc). Based on the correlation between such informations and Wi-Fi encounters, the algorithms can determine the wake-up time from sleep mode to detect a Wi-Fi AP efficiently. In this paper, we measure and compare the impact of each surrounding information on the Wi-Fi sensing efficiency by analyzing the uncertainty of information-conditioned remaining time of a mobile until its next Wi-Fi encounter. Using three metrics (i.e., information gain, conditional expectation and variance) on a real mobility trace, we measure to what extend each surrounding information can reduce the uncertainty of the remaining time, which turns out to be the improvement of Wi-Fi sensing efficiency. Comparing such gains from all surrounding informations, we show that the cell ID information is more energy-efficient than bluetooth ID, speed and even all possible combinations of them in Wi-Fi sensing.