Jakarta, INTI - A team of Electrical Engineering students from the School of Electrical Engineering and Informatics (STEI) at Institut Teknologi Bandung (ITB) developed an Internet of Things (IoT)-based innovation named Monstree to monitor the health of tree branches in real-time. This precision-instrument monitoring system features an early warning system designed to mitigate the risk of accidents and damage to campus facilities caused by falling tree branches.
The technology was initiated by Electrical Engineering students from the Class of 2022, Alghoza Hamdani, Avila Khadhibyan, and Felix Eduardo Sihaloho. The research and development process was also guided by Dr. Eng. Ir. Infall Syafalni S.T., M.Sc., Muhammad Shiddiq Sayyid Hashuro S.T, M.Eng., Ph.D., and Ir. Habibur Muhaimin S.T, M.Sc.
The development of Monstree was driven by the risk of tree branches breaking and falling onto campus facilities or parked vehicles. Avila noted that such incidents could result in significant financial losses for both vehicle owners and campus management.
"We hope to help prevent losses for both vehicle owners and the campus's Security, Safety, Health and Environment (K3L) unit. This device is designed to mitigate and prevent such losses quickly," said Avila.
Movement and Acoustic Emission Sensors
Unlike conventional mechanical prevention systems that require manual operator intervention, Monstree relies on the continuous monitoring of quantitative branch parameters. The system employs two primary, complementary sensors.
First is Inertial Measurement Unit (IMU) that combines non-instrusive gyroscope and accelerometer components. It monitors movement responses and branch curvature under natural loads, such as wind gusts, rain, or extreme weather.
Second is an acoustic emission sensor that detects vibration waves and sounds generated by micro-cracks within the wood structure. Branch breakage is typically preceded by the accumulation of small, gradually developing cracks, which can generate acoustic signal spikes prior to total structural failure.
Furthermore, Alghoza explained that Monstree can process data regarding movement dynamics and acoustic emissions to precisely determine the risk level of branch failure. The system is also designed to issue automatic notifications whenever indications of structural damage are detected.
Given the campus's extensive green areas and large number of trees, sensor installation is prioritized based on risk levels. Monstree instruments will be placed on lower-order branches in strategic locations, particularly large branches extending over parking areas or high-traffic pedestrian walkways.
Future AI Model Development
Moving forward, the quantitative data collected by Monstree will serve as a foundation for developing artificial intelligence (AI) models. This large-scale dataset regarding branch dynamics is expected to train machine learning algorithms, making the branch-breakage risk detection system increasingly responsive, intelligent, and integrated.
Through the development of Monstree, ITB students demonstrate a commitment to providing solutions based on science and technology that offer not only academic value but also direct benefits for public safety and the campus community.
Conclusion
A team of Electrical Engineering students at ITB developed Monstree, an Internet of Things (IoT)-based monitoring system designed to track the health of tree branches in real-time and provide early warnings regarding the risk of branch breakage. The system uses IMU sensors and acoustic emission sensors. The collected data will be utilized to develop AI and machine learning models for a more responsive system.
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