Artificial Intelligence (AI) has been hitting the headlines recently with fears that technology will be replacing humans across the jobs market. In the field of data collection and monitoring however, the use of AI could be hugely positive as it will allow farmers, landowners and environmentalists to capture data to prove or disprove the effectiveness of environmental schemes.
The UK Centre for Ecology & Hydrology (UKCEH) will be deploying solar-powered biodiversity monitoring stations comprising camera ‘traps’ and acoustic recording equipment at farms to monitor wildlife. There will also be recording equipment at sites that are using schemes to reduce emissions, increase carbon capture and support wildlife, such as wildflower hay meadows and agroforestry.
The monitors will also be used at sites not under any schemes in order to make comparisons and measure the impact of any strategies.
They will also be located at degraded peatland areas to compare species populations on farms which remain drained for agricultural use and nearby sites that are being rewetted to provide wetland habitats that support biodiversity and absorb carbon dioxide from the atmosphere.
Researchers will then use AI software to identify species from the photographs or recordings of their calls.
Currently the research is taking place in four sites across the UK: Northampton, Oxfordshire, Wiltshire and Dorset. There is also ongoing research at two farms in Cambridgeshire to assess the impact of agri-environmental schemes on two peatland sites; one which is being farmed, the other which is being restored.
Dr Tom August, a computational ecologist at UKCEH who is overseeing the deployment of the monitoring stations, explained how important AI was to the process: ‘New sensor and AI technology is transforming the way ecologists monitor biodiversity.
‘Automated biodiversity monitoring stations with solar power allow us to monitor wildlife round-the-clock in remote locations without being on site. AI technologies allow us to process the thousands of images and recordings they produce far faster than a human can.’
UKCEH will present its findings after completion of the four-year study though preliminary data will be available during the project.
Photo courtesy: UKCEH