As trees grow older and larger, they are more likely to develop defects such as cavities and decay, threatening their structural health and may lead to tree failures - the structural deterioration or breakage of any part of a tree.
Now, scientists at NTU Singapore are developing, with support from National Parks Board (NParks), a new artificial intelligence-enabled innovation that can detect cavities and decay inside tree trunks. As part of this ongoing project, a prototype has been built in NTU's labs.
The prototype comprises a radar that scans the trunk's interior using microwaves. Advanced signal processing techniques 'clean up' the data captured by the radar, before a deep learning model analyses the data and pinpoints any defects in the trunk. This process takes three to four minutes, from scanning to analysis and detection.
When tested on freshly cut trunks of the Angsana tree - a common roadside tree in Singapore - the scientists found that their prototype showed a 96 per cent accuracy in identifying defects within trunk samples.
The prototype is currently being finetuned so that it might one day be deployed in the field to monitor the structural health of trees.
