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Yang Wei1, Hao Wang1, Kim Fung Tsang2

  • 1Department of Electrical Engineering, City University of Hong Kong, Hong Kong 999077, China.

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Summary
This summary is machine-generated.

A new proximity environmental feature-based tree health assessment (PTA) scheme uses smart sensors and machine learning to monitor tree health. This system provides early warnings for potential hazards, protecting the environment and human safety.

Keywords:
adaptive data identifying (ADI) algorithmproximity environmental feature (PEF)radial basis function neural network (RBF NN)tree health assessment

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Area of Science:

  • Environmental Science
  • Computer Science
  • Horticulture

Background:

  • Improperly grown trees pose significant environmental and human hazards, including climate change and soil erosion.
  • Early warning systems are crucial for mitigating risks associated with poor tree health.

Purpose of the Study:

  • To develop a proximity environmental feature-based tree health assessment (PTA) scheme for early warning of potential poor tree health.
  • To define and evaluate tree health using proximity environmental features (PEFs) measured by smart sensors.

Main Methods:

  • Defined tree health based on seven key proximity environmental features (PEFs).
  • Collected tree health and PEF data using deployed smart sensors.
  • Applied an adaptive data identifying (ADI) algorithm to refine the database.
  • Utilized a radial basis function (RBF) neural network (NN) to establish the PTA algorithm.

Main Results:

  • Successfully correlated tree health with PEFs using an RBF neural network.
  • Developed a PTA algorithm capable of remote and automatic tree health evaluation.
  • Leveraged Internet of Things (IoT) and machine learning for efficient monitoring.

Conclusions:

  • The PTA scheme offers a novel approach to monitoring tree health using smart sensor data and machine learning.
  • This method enables early detection of potential issues, preventing environmental and human hazards.
  • The integration of IoT and AI facilitates automated, remote assessment of tree well-being.