A UBC research team from the Department of Electrical, Computer Engineering and Forestry uses ground-based sensors, drones, mobile data, and artificial intelligence to understand tree health and social and environmental norms in urban green spaces. here more of Brian Shami and a research team at the University of British Columbia:
Climate change is expected to exacerbate the frequency and severity of extreme weather events, including severe storms, tornadoes and thunderstorms, causing significant damage to urban and forest natural assets. . IoT systems have allowed low-cost, low-power sensor networks to improve the efficiency of city operations and services, including urban forest management. . In addition, natural disaster management tools have emerged to provide proactive measures to mitigate damage and ensure effective response and rapid recovery after disasters, such as falling trees on buildings, roads and infrastructure. [3, 4]. In particular, microelectromechanical systems (MEMS) sensors, such as inertial sensors, have been adopted for various applications including monitoring tree dynamics, the natural ways in which trees oscillate in response to environmental factors, such as wind, rain, temperature, and humidity levels. [5,6] and associated preliminary assessment of tree death .
Inertial Measurement Unit (IMU) sensors have also been used in tree fall detection for assessment systems after natural disasters (eg severe storms). . In our approach, we use a 6DoF-IMU (3-axis accelerometer/gyroscope, MPU6050, InvenSense Inc.) to monitor differences in tree dynamics due to wind/drought stress. The sensors connect to the trunks and branches of two northern red oak (Quercus rubra) trees, one mature and the other relatively younger, a pinoak, and western cedar.
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