= Real-time machine learning-based user authentication via daily activities using wireless signals = == Group Members == 1. Bhargav Singaraju [[Image(data:image/jpeg;base64,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)]] 2. Sachin Mathew [[Image(https://media-exp1.licdn.com/dms/image/C4E03AQERmCBO7wu00A/profile-displayphoto-shrink_100_100/0?e=1600905600&v=beta&t=ctjy2Y44nBEYkvB2iL3xhvOHtMgmPxqlN4ZfoTiMC14)]] 3. Rishika Sakhuja == Project Objective == In this project, we plan to develop an end-to-end user authentication system that takes real-time WiFi signals as input and can recognize the user’s identity with low delay. The system first detects the presence of human activity and segment the activity which is then fed to a machine learning model. Based on the activity segment, the machine learning model determine the user identity associated with the activity segment in real-time. Tasks for this project could include wireless preprocessing-implementing real-time data segmentation, time/frequency-domain feature extraction mechanisms based on Python and scikit-learn library; machine learning-based model-developing SVM/DNN-based user identification/activity recognition models based on Python and TensorFlow library; real-time system-integrating the code for CSI preprocessing and machine learning-based model and fine-tune the system to make it capable of running in real time. == Development Tools Tutorials == - Pytorch tutorial: https://pytorch.org/tutorials/ - Tensorflow tutorial: https://www.tensorflow.org/tutorials == Week 1 Activities == [https://docs.google.com/presentation/d/1xBrFMNUiyFOAZEqU0OIx8Acni-KNOaUU2UmlLHwSYxY/edit?usp=sharing Week 1 Presentation] == Week 2 Activities == [https://docs.google.com/presentation/d/1wDVsaRjOhi3KHFyWXiqyKhHh9tJTpOgJk36T5OnCfTw/edit Week 2 Presentation] == Week 3 Activities == [https://docs.google.com/presentation/d/1CO3l_t6dhO04TOfTPElTjG_pPDF8jP0jyYrQLehCZZg/edit?usp=sharing Week 3 Presentation] == Week 4 Activities == [https://docs.google.com/presentation/d/1dlDFwY4mrTWo62a3Ftd5AHB5afSCroCqfodVQRFVq3k/edit?usp=sharing Week 4 Presentation] == Week 5 Activities == [https://docs.google.com/presentation/d/1k9HBXV__7ox3STv5_RfKBZK_ST3EcM1mmeeZUf_2JGA/edit?usp=sharing Week 5 Presentation] == Week 6 Activities == [https://docs.google.com/presentation/d/1RHxtIlvzaPefc87gSGJN7s36z110LCBT5oUMXegflRA/edit?usp=sharing Week 6 Presentation] == Week 7 Activities == [https://docs.google.com/presentation/d/1SmexQk_5nKFyZBXUoXoogh-2qMBb4bhxOMJns_8q5Iw/edit?usp=sharing Week 7 Presentation] == Week 8 Activities == [https://docs.google.com/presentation/d/1rvwltbtVX1Xrx73qvXCe8PG8xDS3EGcHfJEy1EqqazQ/edit?usp=sharing Week 8 Presentation] == Final Presentation == [https://docs.google.com/presentation/d/1mTtXs8rx23qPwCMlC4lOBiM7-w0SfScn8S4-6Qd1GBM/edit?usp=sharing Final Presentation] == Research Poster == [https://docs.google.com/presentation/d/1y6ecqqO7d_jpVBKz1bNJq-BefOHUSSLaDoT8qKkeiYU/edit?usp=sharing Research Poster]