MAPPING THE UNDERWORLD: MULTI-SENSOR DEVICE CREATION, ASSESSMENT, PROTOCOLS
Lead Research Organisation:
University of Leeds
Department Name: Sch of Computing
Abstract
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Organisations
Publications
Bilal M
(2018)
Inferring the most probable maps of underground utilities using Bayesian mapping model
in Journal of Applied Geophysics
Chen H
(2011)
Buried Utility Pipeline Mapping Based on Multiple Spatial Data Sources: A Bayesian Data Fusion Approach
in Proceedings of the 22nd International Joint Conference on Artificial Intelligence
Chen H
(2010)
Buried Utility Pipeline Mapping based on Street Survey and Ground Penetrating Radar
in Frontiers in Artificial Intelligence and Applications
Dou Q
(2016)
3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.
in Sensors (Basel, Switzerland)
Dou Q
(2017)
Real-Time Hyperbola Recognition and Fitting in GPR Data
in IEEE Transactions on Geoscience and Remote Sensing
Dutta R
(2013)
3D mapping of buried underworld infrastructure using dynamic Bayesian network based multi-sensory image data fusion
in Journal of Applied Geophysics
Hao T
(2012)
Condition assessment of the buried utility service infrastructure
in Tunnelling and Underground Space Technology
Rogers C
(2012)
Condition assessment of the surface and buried infrastructure - A proposal for integration
in Tunnelling and Underground Space Technology
| Description | In this project at the University of Leeds we investigated how to interpret and integrate sensor data relating to observations of underground utility assets with a view to producing automated mapping of these assets. We have made advances along a number of fronts: - new and better methods to interpret vibro acoustic data - new and better methods to interpret Ground Pentrating Radar data - new and better methods to interpret other electro magnetic wave sensor data - new methods to combine the results of sensor interpretations to produce automated maps of buried utility apparatus |
| Exploitation Route | The results of this project were used in the follow on Assessing the Underworld project (EP/K021699/1) and the EU FP7 NetTUN project (grant agreement 280712). Some of papers related to this project have been cited may times by researchers at other institutions. In general, we have provided methods to interpret sensor data, in particular GPR data, which is a very widely used sensor in multiple domains, not just underground utility detection (for example in tunnel boring machines, mine detection and other applications). |
| Sectors | Construction Transport Other |
| URL | http://mappingtheunderworld.ac.uk/ |
| Description | We have conducted investigations with real world data for a utility survey company using our techniques with a view to help automate their utility surveys. |
| First Year Of Impact | 2018 |
| Sector | Construction |
| Impact Types | Economic |
| Description | ATU |
| Amount | £5,782,838 (GBP) |
| Funding ID | EP/K021699/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 05/2013 |
| End | 05/2017 |
| Description | Intelligent Excavation |
| Amount | £164,000 (GBP) |
| Organisation | Department of Transport |
| Department | Highways Agency |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2017 |
| End | 11/2017 |
| Description | Nettun |
| Amount | € 9,974,600 (EUR) |
| Funding ID | 280712 |
| Organisation | European Commission |
| Sector | Public |
| Country | European Union (EU) |
| Start | 08/2012 |
| End | 02/2017 |