Risk-Based-Trip-Recommender

An individual trip-recommendation system based on risk of epidemic infection and distance of trip

Need to change a code locally:

Go to folium/plugins/marker_cluster.py or right click on MarkerCluster in poi_near_me.py change the __init__ method to include the tooltip values:

def __init__(self, locations=None, popups=None, icons=None, name=None,
                 overlay=True, control=True, show=True, tooltip_strings=None,
                 icon_create_function=None, options=None, **kwargs):
        if options is not None:
            kwargs.update(options)  # options argument is legacy
        super(MarkerCluster, self).__init__(name=name, overlay=overlay,
                                            control=control, show=show)
        self._name = 'MarkerCluster'

        if locations is not None:
            locations = validate_locations(locations)
            for i, location in enumerate(locations):
                self.add_child(Marker(location,
                                      popup=popups and popups[i],
                                      icon=icons and icons[i],
                                      tooltip=tooltip_strings and tooltip_strings[i]))

        self.options = parse_options(**kwargs)
        if icon_create_function is not None:
            assert isinstance(icon_create_function, str)
        self.icon_create_function = icon_create_function

Datasets

Link here: https://drive.google.com/drive/folders/1aTrklikj97VsuOBSC1Xk86uOb8QYRVxG?usp=sharing

and here: https://drive.google.com/drive/folders/1O3ZPLvYV6_P8lyms-3R-7pOqNm_CwPfK?usp=sharing

• POI Risk Map: GTA_risks.csv
• Hex Risk Map: hex_gdf.csv

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Faster Processing

Link here: https://drive.google.com/drive/folders/1O3ZPLvYV6_P8lyms-3R-7pOqNm_CwPfK?usp=sharing To make the files run faster, use:

• Past trips recorded: df_trips.csv
• Past coordinate recorder: df_past_coordinates_search.csv

Usage

Run mainPage.py, copy the url and paste into the browser.

Evaluation

To evaluate the program, run:

1. POI-Explorer.ipynb for the POIs in the GTA
2. POI_risk_calculator.ipynb for the extrapolated, hourly POI risks following skewed, normal, and uniform distributions.
3. queries_generator.py to generate random queries in Toronto
4. QueryProcessor.ipynb to process the queries from step 3
5. animate.py to animate the results