Previous Image
Next Image

info heading

info content

Wireless Indoor Localization

Using Wi-Fi and Bluetooth signals to track mobile devices.

The robot automatically collects wireless packets at different locations and produces a database of RSSI and CSI fingerprints together with a 2D LIDAR map of the floor.

Cavity Sensing

We observed the optomechanical oscillation of a whispering gallery mode (WGM) microcavity, a silica microsphere, in liquid. Thanks to its high quality (Q) factor and small mode volume, the accumulated high intensify of the cavity on optical resonance leads to an radiation force, which is sufficient to amplify the mechanical motion of the cavity and trigger the regenerative oscillation. By keeping the pump laser at a constant optical power within a certain range of wavelength near the resonance, the mechanical oscillation of the optical resonator is achieved under the highly dissipative environment. Furthermore, the spectra indicate a high stability of such an optomechanical oscillation for cavities immersed in either heavy water or buffered solution.

Visual SLAM

Simultaneous localization and mapping (SLAM) using cameras and machine learning

ECG Analysis

Electrocardiography analysis via machine learning for detecting QRS complexes and diagnosing cardiovascular diseases.

Gas spectra quantification and classification using machine learning algorithms

Using machine learning to identify attacks on SCADA systems.

Dynamic ML

Machine learning algorithms that change their own structure at runtime for adapting to dynamic goals and problems.

Published Papers

  1. Yifeng Bie, Shuai You, Xinrui Li, Xuekui Zhang, Tao Lu, “Essential Number of Principal Components and Nearly Training-Free Model for Spectral Analysis”
  2. B. Yuen, Y. Bie, D. Cairns, G. Harper, J. Xu, C. Chang, X. Dong, T. Lu, “Wi-Fi And Bluetooth Contact Tracing Without User Intervention”  IEEE Access, 2022
  3. M.T. Hoang, B. Yuen, K. Ren, A. Elmoogy, X. Dong, T. Lu, R. Westendorp, K. Reddy, “Passive Indoor Localization with WiFi Fingerprints”  arxiv, 2021
  4. M.T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, “A CNN-LSTM Quantifier for Single Access Point CSI Indoor Localization ”  arxiv, 2020
  5. B. Yuen, M.T. Hoang, X. Dong, and T. Lu, “Universal activation function for machine learning,” Scientific Reports, 2021
  6. M.T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Semi-Sequential Probabilistic Model for Indoor Localization Enhancement,” IEEE Sensors Journal, 2020
  7. A. Elmoogy, X. Dong, T. Lu, R. Westendorp and K. Reddy, “SURF-LSTM: A Descriptor Enhanced Recurrent Neural Network For Indoor Localization,” IEEE Conference on Vehicular Technology, 2020
  8. Jun Gao, Luyun Gan, Fabiola Buschendorf, Liao Zhang, Hua Liu, Peixue Li, Xiaodai Dong, and Tao Lu, “Omni SCADA Intrusion Detection Using Deep Learning Algorithms,”  IEEE Internet of Things Journal 2020
  9. A. Elmoogy, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Linear-PoseNet: A Real-Time Camera Pose Estimation System Using Linear Regression and Principal Component Analysis,” IEEE Conference on Vehicular Technology, 2020
  10. B. Yuen, X. Dong, and T. Lu, “Detecting Noisy ECG QRS Complexes Using WaveletCNN Autoencoder and ConvLSTM,” IEEE Access, 2020
  11. A. Elmoogy, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Generalizable Sequential Camera Pose Learning Using Surf Enhanced 3D CNN,” IEEE Conference on Vehicular Technology, 2020
  12. B. Yuen, X. Dong, and T. Lu, “Inter-Patient CNN-LSTM for QRS Complex Detection in Noisy ECG Signals,” IEEE Access, 2019
  13. Jun Gao, Luyun Gan, Fabiola Buschendorf, Liao Zhang, Hua Liu, Peixue Li, Xiaodai Dong, and Tao Lu, “LSTM for SCADA Intrusion Detection,”  2019 IEEE Pacific Rim Conference
  14. Luyun Gan, Brosnan Yuen and Tao Lu, “Multi-Label Classification with Optimal Thresholding for Multi-Composition Spectroscopic Analysis,” Mach. Learn. Knowl. Extr. 2019, 1(4), 1084-1099
  15. M.T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Recurrent Neural Networks for Accurate RSSI Indoor Localization,” IEEE Internet of Things Journal, 2019
  16. M.T. Hoang, Y. Zhu, B. Yuen, T. Reese, X. Dong, T. Lu, R. Westendorp and M. Xie, “Soft Range Limited K-Nearest Neighbours Algorithm for Indoor Localization Enhancement,” IEEE Sensor Journal, pp. 10208-10216, Dec. 2018
  17. Wenyan Yu, Wei C. Jiang, Qiang Lin, and Tao Lu, “Cavity Optomechanical Spring Sensing of Single Molecules,” Nature Communications 7, 12311 (2016) 
  18. Wenyan Yu, Wei C. Jiang, Qiang Lin, and Tao Lu, “Coherent Optomechanical Oscillation of a Silica Microsphere in an Aqueous Environment,” Optics Express Vol. 22, Iss. 18, pp. 21421-21426 (2014) 
  19. Serge Vincent, Wenyan Yu, and Tao Lu, “Implementation of a Reference Interferometer for Nanodetection,” Journal of Visualized Experiments (86), e51133 (2014) 

Archived Theses

  1. Minh Tu Hoang, “WiFi fingerprinting based indoor localization with autonomous survey and machine learning,” UVicSpace, ETD (Electronic Theses and Dissertations)
  2. Ahmed Elmoogy, “Efficient image based localization using machine learning techniques,” UVicSpace, ETD (Electronic Theses and Dissertations)
  3. Luyun Gan, “Multi-label classification with optimal thresholding for multi-composition spectroscopic analysis,” UVicSpace, ETD (Electronic Theses and Dissertations)
  4. Brosnan Yuen, “Applications of machine learning” UVicSpace, ETD (Electronic Theses and Dissertations)
  5. Charles Chang, “Investigation of Neural ODE LSTM for RSSI Indoor Localization” UVicSpace, ETD (Electronic Theses and Dissertations)

Datasets

  1. https://github.com/WiFiLocalization/ESP32C3_WiFi_FTM_RSSI_Indoor_Localization
  2. https://github.com/WiFiLocalization/BLE_Wi-Fi_RSSI_SQI_Indoor_Localization
  3. https://zenodo.org/records/10883013
  4. https://ieee-dataport.org/documents/esp32c3-wifi-ftm-rssi-indoor-localization
  5. https://zenodo.org/records/10862916
  6. https://ieee-dataport.org/documents/wi-fi-and-bluetooth-rssi-sqi-indoor-localization
  7. https://zenodo.org/records/10864532
  8. https://ieee-dataport.org/open-access/wifi-rssi-indoor-localization
  9. https://huggingface.co/datasets/Brosnan/WIFI_RSSI_Indoor_Positioning_Dataset

Source Code

  1. https://github.com/SensorOrgNet/Universal_Activation_Function
  2. https://github.com/SensorOrgNet/Recurrent_Neural_Networks_for_Accurate_RSSI_Indoor_Localization
  3. https://github.com/SensorOrgNet/A_Soft_Range_Limited_K_Nearest_Neighbors_Algorithm_for_Indoor_Localization_Enhancement