Skip to content

sudarshan-krishnan/Uber_Tracking_App

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

UberTracker NYC Web App

Welcome to the UberTracker NYC web app! This interactive app allows you to explore a public Uber dataset for pickups and drop-offs in New York City. With this app, you can visualize Uber pickups throughout the day, view raw data, and even filter results by hour.

Getting Started

To start using the app, simply click on the link below:

UberTracker NYC Web App

Features

  • Fetch Data: Utilize Amazon's WAS API and Amazon S3 to fetch and cache the Uber dataset for pickups and drop-offs in NYC.
  • Visualize Data: View the number of pickups by hour through an interactive histogram.
  • Map Visualization: Plot pickup locations on a map of NYC.
  • Filter Data: Filter pickup data by hour using a slider.
  • Toggle Raw Data: Toggle the display of raw data with a checkbox.

Usage

  1. Show Raw Data: Toggle the display of raw data by checking the "Show raw data" checkbox.
  2. Number of Pickups by Hour: Explore the distribution of pickups throughout the day using the histogram.
  3. Map of Pickups: View pickup locations on the map of NYC.
  4. Filter by Hour: Use the slider to filter pickup data by hour.
  5. Toggle Raw Data Display: Show or hide the raw data table by checking or unchecking the checkbox.

Scope

Expansion to Bangalore, India

In addition to analyzing Uber pickups in New York City, we plan to expand the app's functionality to include data from Bangalore, India. This expansion will involve integrating with Uber's API and accessing relevant datasets to visualize and analyze Uber pickups in Bangalore.

Optimization for Reduced Wait Times

With data from Bangalore incorporated into the app, we aim to optimize the allocation of cab drivers to reduce wait times for passengers. By analyzing historical booking times, traffic patterns, and demand fluctuations, we will identify areas and times of high demand to strategically position cab drivers, ensuring prompt availability for passengers during peak hours.

Key Objectives:

  1. Data Collection: Obtain access to Uber's API and relevant datasets for Bangalore, India.

  2. Visualization and Analysis: Implement features to visualize and analyze Uber pickups in Bangalore, including histograms, maps, and filters similar to those available for New York City data.

  3. Optimization Algorithms: Develop algorithms to optimize the allocation of cab drivers based on historical booking times and demand patterns.

  4. User Interface Enhancements: Enhance the user interface to accommodate the expansion to Bangalore, providing a seamless experience for users accessing data from both cities.

  5. Testing and Deployment: Thoroughly test the expanded features and ensure compatibility with the existing functionality before deploying the updated version of the app.

By expanding the scope of the UberTracker web app to include Bangalore, India, and implementing optimization strategies based on recorded booking times, we aim to improve the efficiency of Uber services and enhance the overall experience for both passengers and drivers in the region.

Releases

No releases published

Packages

No packages published

Languages