About this document
Wi-Fi & Bluetooth Data Fusion Models by pragatiisharmaa22 is a document available to read on EtoBox.
The document compares three data fusion algorithms—KNN, RNN, and Random Forest Regression—for indoor localization using RSSI Wi-Fi and Low Energy Bluetooth data. Random Forest Regression outperforms the other models in terms of Mean Squared Error, Mean Absolute Error, and accuracy, while KNN shows decent performance and RNN struggles significantly. The insights suggest that model choice should consider data characteristics, complexity, and hyperparameter tuning for optimal results.
- Author
- pragatiisharmaa22
- Language
- EN