Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.