Open AccessAIOSAT - Autonomous Indoor & Outdoor Safety Tracking System
Author(s) -
Iñigo Adín,
Paul Zabalegui,
A. Pérez,
Jaione Arrizabalaga,
Jon Goya,
Jaizki Mendizábal
Publication year - 2019
Publication title -
annual of navigation
Language(s) - English
Resource type - Journals
eISSN - 2300-6633
pISSN - 1640-8632
DOI - 10.1515/aon-2019-0003
Subject(s) - gnss applications , computer science , global positioning system , tracking system , firefighting , satellite system , obstacle , satellite navigation , aeronautics , real time computing , engineering , telecommunications , geography , kalman filter , cartography , archaeology , artificial intelligence
Even though satellite-based positioning increases rescue workers’ safety and efficiency, signal availability, reliability, and accuracy are often poor during fire operations, due to terrain formation, natural and structural obstacles or even the conditions of the operation. In central Europe, the stakeholders report a strong necessity to complement the location for mixed indoor-outdoor and GNSS blocked scenarios. As such, location information often needs to be augmented. For that, European Global Navigation Satellite System Galileo could help by improving the availability of the satellites with different features. Moreover, a multi-sensored collaborative system could also take advantage of the rescue personnel who are already involved in firefighting and complement the input data for positioning. The Autonomous Indoor & Outdoor Safety Tracking System (AIOSAT) is a multinational project founded through the Horizon 2020 program, with seven partners from Spain, Netherlands and Belgium. It is reaching the first year of progress (out of 3) and the overarching objective of AIOSAT system is to advance beyond the state of the art in tracking rescue workers by creating a high availability and high integrity team positioning and tracking system. On the system level approach, this goal is achieved by fusing the GNSS, EDAS/EGNOS, pedestrian dead reckoning and ultra-wide band ranging information, possibly augmented with map data. The system should be able to work both inside buildings and rural areas, which are the test cases defined by the final users involved in the consortium and the advisory board panel of the project