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There is a growing interest in using wireless sensor networks for security monitoring in the underground coal mines. In such applications, the sensor nodes are deployed to detect interested events, e.g., the density of certain gas at some locations is higher than the predefined threshold. These events are then reported to the base station outside. Using conventional multi-hop routing for data reporting, however, will result in imbalance of energy consumption among the sensors. Even worse, the unfriendly communication condition underground makes the multi-hop data transmission challenging, if not impossible. In this paper, we thus propose to leverage tramcars as mobile sinks to assist event collection and delivery. We further observe that the sensor readings have spatial and temporal correlation. More precisely, the same event may be observed by multiple neighboring sensor nodes and/or at different time. Obviously, it can be more energy-efficient if the data are selectively reported. As such, we first provide a general, yet realistic definition on the events. We then transform the event collection problem into a set coverage problem; and our objective is to maximize the system lifetime with the coverage rate of events guaranteed. We show that the problem is NP-hard even when all the events are known in advance. We present an online scheme which leverages the spatial-temporal correlation of the events to balance the communication energy of the static sensor nodes. We prove that the expected event coverage rate can be guaranteed in theory. Through extensive simulation, we demonstrate that our scheme can significantly extend system lifetime, as compared to a stochastic collection scheme.