Development Trends in Precision Agriculture and Its Management in China Based on Data Visualization
Abstract
:1. Introduction
1.1. Background and Origin of the Research
1.2. Literature Works
2. Big Data Analytics-Initiated Agriculture Monitoring System (BDA-AMS)
2.1. Reasons for System Design
2.2. BDA-AMS’ Basic Framework and Main Principles
2.3. Operation of System
3. Results and Discussion
3.1. Precision Ratio (%) and Mean Absolute Percentage Ratio (%)
3.2. Data Transmission Rate (%) and Reliability Ratio (%)
3.3. Accuracy Ratio (%)
3.4. Performance Ratio (%)
3.5. Power Consumption Ratio (%)
3.6. Weather Forecasting Ratio (%)
3.7. Production Density (%)
4. Conclusions and Future Work
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Symbol | Description |
---|---|
G | Measured resistance |
σ | Molar conductivity |
FB | Temperature traction |
O | Molar |
N | Cell-constant |
Uj | Value of the ion charge |
eq | Translation factor of temperature |
q | Temperature |
a0a1 | Regression coefficients |
Y | Number-dependent variable |
Number of Devices | Weather Forecasting Ratio (%) | ||||
---|---|---|---|---|---|
IoT-DSS | LCA | SDSS | CNN-ANN | BDA-AMS | |
10 | 21.836 | 15.937 | 17.852 | 19.231 | 84.622 |
20 | 20.401 | 16.765 | 17.727 | 19.342 | 85.711 |
30 | 19.094 | 14.657 | 17.494 | 19.659 | 86.315 |
40 | 18.024 | 14.922 | 17.571 | 23.987 | 87.318 |
50 | 18.882 | 16.342 | 17.790 | 23.567 | 88.724 |
60 | 17.852 | 12.212 | 18.234 | 23.459 | 90.648 |
70 | 17.727 | 14.254 | 18.345 | 25.671 | 91.727 |
80 | 15.974 | 13.084 | 18.675 | 30.222 | 92.922 |
90 | 15.571 | 16.145 | 18.879 | 33.567 | 93.321 |
100 | 15.128 | 14.124 | 19.111 | 34.987 | 94.864 |
Number of Devices | Production Density (%) | ||||
---|---|---|---|---|---|
IoT-DSS | LCA | SDSS | CNN-ANN | BDA-AMS | |
10 | 31.836 | 65.937 | 77.852 | 84.231 | 91.622 |
20 | 30.401 | 66.765 | 77.727 | 84.342 | 92.711 |
30 | 39.094 | 64.657 | 77.494 | 85.659 | 92.315 |
40 | 38.024 | 64.922 | 78.571 | 86.987 | 93.318 |
50 | 38.882 | 66.342 | 78.790 | 86.567 | 94.724 |
60 | 47.852 | 72.212 | 79.234 | 87.459 | 94.648 |
70 | 47.727 | 74.254 | 80.345 | 88.671 | 95.727 |
80 | 45.974 | 63.084 | 81.675 | 89.222 | 96.922 |
90 | 55.571 | 66.145 | 82.879 | 90.567 | 97.321 |
100 | 55.128 | 64.124 | 83.111 | 90.987 | 98.864 |
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Song, C.; Ma, W.; Li, J.; Qi, B.; Liu, B. Development Trends in Precision Agriculture and Its Management in China Based on Data Visualization. Agronomy 2022, 12, 2905. https://doi.org/10.3390/agronomy12112905
Song C, Ma W, Li J, Qi B, Liu B. Development Trends in Precision Agriculture and Its Management in China Based on Data Visualization. Agronomy. 2022; 12(11):2905. https://doi.org/10.3390/agronomy12112905
Chicago/Turabian StyleSong, Chuanhong, Wenbo Ma, Junjie Li, Baoshan Qi, and Bangfan Liu. 2022. "Development Trends in Precision Agriculture and Its Management in China Based on Data Visualization" Agronomy 12, no. 11: 2905. https://doi.org/10.3390/agronomy12112905