A full overview and detailed description of the LOKI project and the functionality of the developed modules is explained in the extensive LOKI Wiki. Code of the modules developed in LOKI is hosted and documented on GitLab.
The aim of the LOKI project is to develop an interdisciplinary system that enables fast and reliable airborne situation assessments following an earthquake. The system will serve to reduce longer-term damage after an earthquake by recording information on the current situation as efficiently as possible, thereby enabling remediation actions to be undertaken within appropriate timescales. A central focus is the timely overview and detailed recording of the damage to critical infrastructures, such as lifelines (bridges and roads), health care facilities and public institutions (e.g. schools). LOKI will improve the response time and reliability of information provided in the event of an earthquake, and enables better use of existing resources and emergency forces. The objectives will be met by combining existing expertise in earthquake research with a variety of new technologies and concepts, including machine learning, crowdsourcing, Unmanned Aerial Vehicles (UAVs, flying drones available for civil use) and 3D monitoring.
Core components of the LOKI research project and their interaction.
Project partners and their research focuses in the project
Heidelberg University serves as the coordinator of the research project, which is a collaboration between several project partners. Within this collaboration, components and services developed by the individual partners will be integrated into a single system.
Coordination mechanisms for UAV fleets:
Coordination mechanisms for UAV fleets: Development of real-time capable and adaptive planning mechanisms for UAVs and investigation of decentralized coordination mechanisms, with which UAVs themselves coordinate the division of the area, the prioritization of targets and the route to be flown.
Exposure modelling: Integration of crowdsourcing and primary UAV overflights into building-specific (iterative) exposure modelling, as well as the adaptation of corresponding evaluation algorithms. This approach is capable of working with very heterogeneous data availability.