Network Rail uses Google AI to assess trackside biodiversity | Computer Weekly
Summary
“The UK has lost nearly half of its biodiversity to urban spread and agriculture since the industrial revolution, ranking in the bottom 10% of nations globally and worst among G7 countries. These declines continue today: the 2019 UK state of nature report found a further 13% decrease in the average abundance of species since scientific monitoring began in the 1970s.” Network Rail is one of the country’s largest public landowners, with a total estate of approximately 52,000 hectares across its 20,000 kilometres of railway corridor. These landholdings traverse all major British terrestrial habitat types, and are home to a rich array of rare, protected and valued species. By using the pre-trained machine learning models BirdNet, BatDetect, and CityNet, Google, Network Rail and ZSL said the AI system was able to detect birds, bats and anthropogenic sounds respectively. Once the predictions for each model were run on all Network Rail audio recordings, the data was further transformed in BigQuery to calculate the frequency of each species for each geographic location and other trends.