適用於邊界偵測之低耗電室內定位系統

Abstract

邊界偵測是一種用於偵測追蹤目標是否進入重要區域的位置感知服務。定位時運用較低的位置更新速度，通常可降低系統耗電量，但同時也犧牲了偵測事件的即時性及準確度。在此篇論文中，我們提出根據目標移動狀況，而動態調整定位更新速度的機制，以降低系統耗電量並維持系統偵測的準確度。在模擬測試及在實體測試平台的結果均顯示我們所提出之機制在不影響系統準確度的前提下，可有效減少系統耗電量。值得一提的是，運用實際量測的定位誤差的測試結果，更顯示系統耗電量可有效減少20%。

Boundary detection is a form of location-aware services that aims at detecting targets crossing certain critical regions. Typically, a lower location sampling rate contributes to a lower level of energy consumption but, in the meantime, delays the detection of boundary crossing events. Opting to enable energy-efficient boundary detection services, we propose a mobility-aware mechanism that adapts the location sampling rate to the target mobility. Results from our simulations and live experiments confirm that the proposed adaptive sampling mechanism is effective. In particular, when experimented with realistic errors measured from a live RF-based localization system, the energy consumption can be reduced significantly to 20%.