In wireless sensor networks, observers are interested in spatio-temporal information monitored by sensors. Observers are not interested in sensor itself or massive irrelevant readings from sensors. They often issue spatio-temporal queries such as “Which events did happen in region R from 10:00 to 12:00?”. Since battery supply of sensors is limited, energy-efficient spatio-temporal query processing in sensor networks has become an important research problem. This paper presents a spatio-temporal query processing algorithm based on data-centric storage. The energy consumption of sensors in three storage strategies, namely external storage, local storage and data-centric storage, is analyzed and compared in this paper. The paper also studies the influence of the probability of an event occurring, node density, number of event types, number of queries, temporal window size and spatial area size in spatial-temporal query on energy consumption. Analytical and experimental results show that in most cases the spatio-temporal query processing algorithm proposed in this paper can save more energy than those algorithms based on the external storage and local storage strategies.