Providing indoor location-based services is challenging due to the vast coverage required and the scalability of positioning systems. This article proposes a participatory service platform for indoor location-based services to solve such problems. In the proposed platform, a few site trainers constructed an initial database of indoor positioning locations through minimal intrusive actions. Thereafter, crowd users of indoor positioning services opportunistically contributed sensing data to improve service quality. The proposed service platform provides an autonomous site-training tool for site trainers and a sample application for continuous contributions by individuals. This architecture takes advantage of crowdsourcing-based service construction and offloads the service costs.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computational Theory and Mathematics