AI and IoT: a smart way to prevent accidents due to Falling Trees
Heavy rain and storm in Uttar Pradesh have resulted in the killing of 17 people and injury of 11 people in June 2019. The accidents were a result of the falling of the trees with weak roots. This has made risk assessment necessary to avert such accidents.
According to a study conducted by the Department of Electrical Engineering in the City University of Hong Kong, improperly grown trees can pose a danger for the local people and proves to be hazardous for the safety of the environment. Fortunately, according to another study published in journal Sensors, combining the Internet of Things (IoT) and Machine Learning (ML) can help in identifying the poor health of trees and removing them before they fall.
Using a scale of 0-3, the discoloration and defoliation of 100 large trees were examined by the researchers in the City University of Hong Kong campus. By affixing sensors to the controller integrated modules, the proximity environmental feature (PEF) was scaled. The module wan further connected with the IoT module through which the collected data was transferred to the server via the IoT network.
While measuring the PEF, all the potential environmental factors relating to tree growth was considered. As per the reports, any factor crossing the normal range can affect tree growth. To eliminate the abnormal data due to weather interference, active data identifying (ADI) algorithm was used to enhance the performance of the experiment.
The researchers made use of a machine learning algorithm and neural network to find a correlation between the health of the tree and the PEF. This was found to help evaluate the tree’s health and preventing accidents. Monitoring tree health by the use of IoT sensors can be effective in averting accidents due to falling trees.
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