/SensorAI

Sensor data science and AI tutorial

Primary LanguageJupyter Notebook

SensorAI

Sensor data science and AI tutorial

Citation

Bib:

@misc{sensor2024ai, author = "Song, WenZhan and Coshatt, Stephen and Zhang, Yida and Chen, Jiayu", year = "2024", title = "Sensor Data Science and AI Tutorial", url = "https://github.com/wsonguga/SensorAI", institution = "SensorWeb Research Laboratory, University of Georgia" }

MLA:

Song, WenZhan, Stephen Coshatt, Yida Zhang, and Jiayu Chen. "Sensor Data Science and AI Tutorial: https://github.com/wsonguga/SensorAI", SensorWeb Research Laboratory, University of Georgia, 2024.

Outline

  1. Advanced signal processing: tutorial_dsp.ipynb
  2. Classification: tutorial_classification.ipynb
  3. Regression: tutorial_regression.ipynb
  4. Clustering: tutorial_clustering.ipynb
  5. Deep Learning: https://github.com/timeseriesAI/tsai or https://github.com/thuml/Time-Series-Library

Package Installation

Run install.sh to install the necessary packages.

    ./install.sh

General Workflow of Sensor AI

    +----------------------------------+
    |          Raw Signal/Data         |
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |       Signal Preprocessing       |
    | (signal denoising, recovery, etc)|
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |       Feature Extraction         |
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |   Feature Selection/Synthesis    |
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |      Machine/Deep Learning       |
    |            Algorithm             |
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |         Model Evaluation         |
    +----------------------------------+
                 |
                 v
    +----------------------------------+
    |        Deployment/Use            |
    +----------------------------------+