Sidewalk Lab (Toronto) Data Analysis
This is a project guided by
- Professor Fanny Chevalier(http://www.cs.toronto.edu/~fchevali/fannydotnet/) @ University of Toronto
- Sidewalk Toronto (https://www.sidewalktoronto.ca/)
This project demonstrate that it is possible to carry out data collection on pedestrian activities in public space in a way that is consistent with the highest standards of privacy protection, and that the collected data can be analyzed to inform how best to improve the quality of life in public spaces.
Build an interactive web page to display and explain data.
This project can be divided into four parts.
- Pedestrian dwell time behavior pattern in the Lab
- Desired path and spots of pedestrian in the Lab
- Maintenance Schedule Design of the Lab
- Balance individual privacy and benefits for society (Ethic Issue Discussion)
In each part, several sub-topic are demonstrated and discussed. For each sub-topic, an interactive webpage is provided to illustrate. To help audience effectively use the webpage, a well-explained documentation is provided. The documentation includes the instrucion and serveral findings based on the data analysis using this webpage.
This project requires the Python (3.7+) kernel for Jupyter notebook.
To run the website, the project requires the installation of voilà website plug Jupyter Notebook. Click here for more information about voilà.(https://blog.jupyter.org/and-voil%C3%A0-f6a2c08a4a93)