Integrating Geospatial and Sensor Data in a Human Probe Environment

With recent advances in MEMS-based sensor technology, low-cost and low-power wireless sensors can be deployed on a human body and utilized as a component of urban sensing. However, the location error of existing positioning technologies depends on environmental factors and users’ walking styles. This variability of the location error brings a huge impact on the data mapping process, especially when we visualize the data using a large-scale map. We therefore propose a system for extracting environmental information considering the variability of location errors. Our system (1) provides adaptive sensing capability that responds to the dynamic change of the user’s location error, and (2) supports management of sensor data that have various degrees of location errors.