Abstract: Wireless sensor networks opens up a fresh research area of database, where efficient use of sensors' limited energy is the primary goal. In general, queries issued to wireless sensor networks are approximate (precise results are not required due to networks' constraint and saving limited energy on sensors), continuous (used to monitor the trend of physical world) and running in parallel. Most studies focus on one aspect of these three features to achieve energy-efficient process in wireless sensor networks. However, if multiple approximate continuous range queries (ACQ) are injected into the networks and run independently without optimization, they will cause a serious problem—sensors are likely to send reduplicate data for different queries and therefore shorten the networks' lifetime. In this paper, the technology of energy-efficiently processing multiple ACQ is studied, and a data structure called rq-kd-tree to index multi-dimensional range queries is designed, which is used to get the common required data of different queries (query intersecting areas). Based on a concept called query similarity degree, original queries are rewritten and issued to the networks. Finally, detailed experiments on both real data and synthetic data are conducted to prove the proposed methods achieving energy-efficient in processing multiple queries.