Accurate position information is nowadays very important in many applications. For instance, maintaining the situation awareness in command center in emergency operations is very crucial. Due to signal strength attenuation and multipath, Global Navigation Satellite Systems are not suitable for indoor navigation purposes. Radio network-based positioning techniques, such as wireless local area network, require local infrastructure that is often vulnerable in emergency situations. We propose here a distributed system for personal positioning based on inertial sensors. The system consists of an inertial measurement unit (IMU) connected to a radio carried by a person and the server connected to another radio. Step length and heading estimation is computed in the IMU and sent to the server. On the server side, the position is estimated using particle filter-based map matching. The benefit of the distributed architecture is that the computational capacity can be kept very low on the user side, which leads to long operation time as power consumption also remains very low.

Distributed Indoor Positioning System With Inertial Measurements and Map Matching

Algorithms for automated generation of navigation models from building information models to support indoor map-matching

A computer implemented method for 3-D visualization of a building module and building related data includes receiving attributes of a plurality of building modules from a building information model and receiving data inputs from a plurality of sensors located in at least a subset of the plurality of building modules. The building related data is calculated for each of the plurality of building modules based on the data inputs. A 3-D visualization data of a selected building module in the plurality of building modules is generated for display on a computer screen.

Occupant centric capture and visualization of building performance data

Locating building components that need to be worked on during maintenance tasks is critical for timely repair of the component and mitigation of the damage. The process of locating a compon...

Analysis of Three Indoor Localization Technologies for Supporting Operations and Maintenance Field Tasks

The work presents a foot-mounted sensor system for a combined indoor/outdoor pedestrian localization. The approach is based on a zero-velocity update scheme formulated as an Extended or Unscented Kalman filter with quaternion orientation representation and employs a custom low-cost sensor unit. Both filters are compared in terms of speed and accuracy on a representative trajectory. A detailed discussion is provided with respect to different filter state formulations, stance still detection mechanisms and associated filter parameters. The presented pure inertial system is augmented with magnetic field measurements for heading correction. The challenging localization scenario with an elevator is addressed by augmenting the system with a barometric pressure sensor for height error correction. The work also demonstrates how the basic algorithm version can be extended with reference systems such as GPS and passive RFID tags on the floor for absolute position drift correction.

A study on indoor pedestrian localization algorithms with foot-mounted sensors

State-of-the-art indoor positioning systems are based on short-range wireless technologies such as ultra-wideband (UWB) and wireless local area network (WLAN). Additional information produced by a low-cost inertial measurement unit (IMU) or selected from low-grade floor plans is frequently used to improve the positioning accuracy. Therefore absolute and relative positioning systems (e.g. WLAN and IMU) are typically integrated using a Kalman filter (KF) or a particle filter (PF). In this case, all the buildings have to be equipped with a large number of transmitters and receivers which may render inoperable during emergency situations and induce substantial costs both in terms of setup and maintenance. Hence, in this paper we present and assess the prototype of a self-contained indoor positioning system. Our prototype consists of a micro-electro-mechanical system- (MEMS) based IMU and a mobile computer which includes a database with characteristic building information. A novel combination of methods is proposed to increase the distance between positions where absolute repositioning is still mandatory.

Thomas Wiessflecker

Papers

Semi-autonomous indoor positioning using MEMS-based inertial measurement units and building information

A Context-Adaptive Building Information Model for Disaster Management