论文标题
可靠的地理林进行激活，稀疏和零星的位置测量：扩展版本
Reliable Geofence Activation with Sparse and Sporadic Location Measurements: Extended Version
论文作者
论文摘要
Geofences是基于位置服务的基本工具。通常通过检测地理林区域内的位置测量来激活地理林。但是，诸如全科医生之类的位置测量值通常在智能手机上偶尔出现，部分原因是信号或隐私保护，因为用户可能会限制位置感知或节能，因为感应地点可以消耗大量的能量。这些测量之间的不可预测的，有时甚至很长的差距意味着进入地理林的进入可能会完全未被发现。在本文中，我们认为短期位置预测可以通过计算未来进入地理林的可能性来帮助缓解这一问题。使这种预测方法复杂化的事实是，另一个位置测量可以随时出现，这使得预测冗余和浪费。因此，我们开发了一个框架，该框架解释了不确定的位置预测以及新测量的可能性以触发地理启动。我们的框架优化了正确和错误的地理委员会激活的收益和成本，从而导致了一种算法，该算法对未来运动和测量的不确定性有明智地反应。
Geofences are a fundamental tool of location-based services. A geofence is usually activated by detecting a location measurement inside the geofence region. However, location measurements such as GPS often appear sporadically on smartphones, partly due to weak signal, or privacy preservation, because users may restrict location sensing, or energy conservation, because sensing locations can consume a significant amount of energy. These unpredictable, and sometimes long, gaps between measurements mean that entry into a geofence can go completely undetected. In this paper we argue that short term location prediction can help alleviate this problem by computing the probability of entering a geofence in the future. Complicating this prediction approach is the fact that another location measurement could appear at any time, making the prediction redundant and wasteful. Therefore, we develop a framework that accounts for uncertain location predictions and the possibility of new measurements to trigger geofence activations. Our framework optimizes over the benefits and costs of correct and incorrect geofence activations, leading to an algorithm that reacts intelligently to the uncertainties of future movements and measurements.
