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- Title
Proximity Environmental Feature Based Tree Health Assessment Scheme Using Internet of Things and Machine Learning Algorithm.
- Authors
Wei, Yang; Wang, Hao; Tsang, Kim Fung; Liu, Yucheng; Wu, Chung Kit; Zhu, Hongxu; Chow, Yuk-Tak; Hung, Faan Hei
- Abstract
Improperly grown trees may cause huge hazards to the environment and to humans, through e.g., climate change, soil erosion, etc. A proximity environmental feature-based tree health assessment (PTA) scheme is proposed to prevent these hazards by providing guidance for early warning methods of potential poor tree health. In PTA development, tree health is defined and evaluated based on proximity environmental features (PEFs). The PEF takes into consideration the seven surrounding ambient features that strongly impact tree health. The PEFs were measured by the deployed smart sensors surrounding trees. A database composed of tree health and relative PEFs was established for further analysis. An adaptive data identifying (ADI) algorithm is applied to exclude the influence of interference factors in the database. Finally, the radial basis function (RBF) neural network (NN), a machine leaning algorithm, has been identified as the appropriate tool with which to correlate tree health and PEFs to establish the PTA algorithm. One of the salient features of PTA is that the algorithm can evaluate, and thus monitor, tree health remotely and automatically from smart sensor data by taking advantage of the well-established internet of things (IoT) network and machine learning algorithm.
- Subjects
PRETORIA (South Africa); INTERNET of things; MACHINE learning; RADIAL basis functions; INTELLIGENT sensors; SOIL erosion; HAZARD Analysis &; Critical Control Point (Food safety system); INTERNET access
- Publication
Sensors (14248220), 2019, Vol 19, Issue 14, p3115
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s19143115