Happy Sip Happy Slurp Happy Shuttle: Enhancing Singapore's Night Life

Refer to our slides here Group Presentation for Happy Sip Happy Slurp Happy Shuttle

1. Introduction

In the bustling cityscape of Singapore, nightlife is a significant component of the city's culture and economy. The efficiency of post-midnight services, particularly in food availability and transportation, plays a crucial role in shaping this aspect. "HappyHour" delves into the geospatial aspects of Singapore's nightlife with an aim to enhance the offerings of post-evening amenities.

This project leverages analytics and data to unravel urban patterns of nightlife, accessibility of late-night services, and their correlations with the city’s demographics. With a focus on affordable and cost-effective options, this study aims to strengthen the cultural vibrancy and economic prosperity of Singapore's night economy.

Singapore currently faces a scarcity of late-night eateries and public transport availability, leading to an overreliance on costly ride-hailing services. Our Project seeks to address these challenges by providing insights into the spatial distribution of nightlife hotspots, accessibilities, and availability of night-time transport services, ultimately guiding business decisions and catalyzing the development of a safer, more inclusive night economy.

2. Objectives

The primary goal of the project is to identify and delineate the landscape of nightlife activities in Singapore, focusing particularly on dining and transportation options post-midnight. The project aims to:

• Assess Accessibility: Measure the ease of finding late-night food and bus routes.
• Analyze Patterns: Understand where people go at night, the availability of food options, and bus services.
• Define Nightlife Hotspots: Establish criteria for what constitutes a nightlife location.

By addressing these objectives, our project hopes to offer insights into the improvement of the night-time scene in Singapore, suggesting potential areas for the addition of food places or bus stop routes post-midnight.

3. Project Structure

Code files in the main directory are labelled No.1 to 5 with each representing the following:

1. Data Preprocessing in R & Python
2. Exploratory Spatial Data Analysis in R
3. Analysis for finding restaurants in R
4. Analysing Bus Stops using KDE, IDW, Kriging and Buffer Spatial Analysis. Note: An updated version of the HTML file requires you to knit the no.4 Rmd file
5. Finding Optimal Bus Stops with Road Networks to map the optimal path

4. Folders

1. Dataset - All of our data sources for this project from the Singapore Base Map, Restaurants Locations, etc
2. Plots - Contains all the image plots for our project analysis onto nightlife
3. optimal_stops - Contains all the analysis in filtering the number of bus stops to serve strategic locations in Singapore's HDB areas
4. optimal_bus_stops - Contains the 2 recommended routes of our public transportation analysis bringing individuals from downtown to high youth density HDB residential areas post-midnight

5. Some plots of our analysis

This project is part of the BT4015 Geospatial Analytics module in the National University of Singapore (NUS) Academic Year 2023/2024 created by Ana Pelin, Minh Hai, Shayer Ahmed, Jeremy Chan Tse Ee, Zhuo Yun Hui