Autonomous monitoring and prediction of marine pollution
Lead Research Organisation:
University of Sheffield
Department Name: Automatic Control and Systems Eng
Abstract
The project 'Autonomous monitoring and prediction of marine pollution' is aiming to develop methods for autonomous mapping and monitoring of maritime spillages, usually oil slicks. This will enable long range mapping missions of multiple autonomous vehicles operating efficiently with minimal input from a human controller. High fidelity models of the sea and wind environment, the sensors and the unmanned vehicles will be developed for algorithm verification and testing, with a lower fidelity and real-time simulation to be used in the control loop. The industry sponsor, Andrew Moore and Associates, intends to utilise the research to gather information to support clean-up operations and legal claims that surround maritime accidents: Calculating the spillage epicentre and predicting future damages.
Organisations
People |
ORCID iD |
| Bryn Jones (Primary Supervisor) | |
| Zak Hodgson (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509735/1 | 01/10/2016 | 30/09/2021 | |||
| 1806216 | Studentship | EP/N509735/1 | 01/10/2016 | 31/03/2020 | Zak Hodgson |
| Description | Developed a low-state high-fidelity ocean/oil model for simulating oil spills. Developed an optimisation problem, the solving of which determines sensor placement to estimate the ocean flow and oil location. Developed a method for the updating of the ocean/oil model with data from sparse sensors. |
| Exploitation Route | Ocean/oil model will be deployed by industry to simulate oil spills in the immediate aftermath of a maritime incident, without reliance on government assets. The optimisation solver and sensor updates could be used to guide sensors (whether a man on a rickety boat, or a highly specialised aircraft) to surveillance of oil spills. The method of updating enables a feedback loop, improving the estimate of oil spill drift, with online assets. |
| Sectors | Aerospace, Defence and Marine |
| Description | Findings and ideas have been presented to various Maritime clients/organisations of the Industry sponsor, in an effort to encourage and support their efforts in oil spill clean-ups. The oil model has provided several results to the industry sponsor to guide their decision making. |
| First Year Of Impact | 2017 |
| Sector | Aerospace, Defence and Marine |
| Impact Types | Economic |
| Title | SWEAM Oil Model |
| Description | Ocean/Wind/Oil spill model |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2017 |
| Provided To Others? | No |
| Impact | Used to simulate several real oil spills with results passed to Industry partner. |