Name
Title | ||
|---|---|---|
Proximity Environmental Feature Based Tree Health Assessment Scheme Using Internet of Things and Machine Learning Algorithm. |
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19143115 | SENSORS |
Keywords | Field | DocType |
tree health assessment,proximity environmental feature (PEF),adaptive data identifying (ADI) algorithm,radial basis function neural network (RBF NN) | Warning system,Radial basis function,Internet of Things,Tree health,Algorithm,Artificial intelligence,Engineering,Feature based,Artificial neural network,Machine learning,Salient | Journal |
Volume | Issue | ISSN |
19 | 14 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Wei | 1 | 2 | 0.73 |
| Hao Wang | 2 | 440 | 127.79 |
| Kim Fung Tsang | 3 | 61 | 26.02 |
| Yucheng Liu | 4 | 116 | 26.77 |
| Chung Kit Wu | 5 | 18 | 8.49 |
| Hongxu Zhu | 6 | 10 | 5.64 |
| Yuk-Tak Chow | 7 | 0 | 0.68 |
| Faan Hei Hung | 8 | 7 | 5.99 |