| UFPA | Federal University of Pará |
| LOS | Line-of-sight |
| NLOS | Non-line-of-sight |
| IOT | Internet of Things |
| LoRA | Long Range |
| MMSE | Minimum mean square error |
| RMSE | Root mean squared error |
| WSNs | Wireless sensor |
| 5G | Fifth generation |
| ML | Machine learning |
| RNAs | Artificial neural networks |
| SF | Spreading factor |
| GRG-MAPE | Maximization of gray relationship degree and mean absolute percentage error |
| UAVs | Unmanned aerial vehicles |
| LoRaWan | Long range wide area network |
| SNR | Signal-to-noise ratio |
| Tx | Transmitter |
| Rx | Receiver |
| VV | Vertical–vertical |
| HH | Horizontal–horizontal |
| PLE | Path loss exponent |
| FI | Floating intercept |
| CI | Close in |
| RSSI | Received signal strength indicator |
| GRNN | General regression neural network |
| MLPNN | Multi-layer perceptron neural network |