Sustainable and smart trip planner for reducing carbon footprint of transportation

• Main Author: Kim, Heonjung
• Other Authors: Long Cheng
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/162850
• Institution: Nanyang Technological University

While global warming is a growing issue around the world, there is still the lack of people’s respect for the environment. It is crucial to be conscious of environmental problems and seek sustainable and eco-friendly habits. Hence, it should be considered to have a tool or application which helps to learn and make sustainable decisions. This project aims to provide and encourage people to make eco-friendly habits while they use transportation and trip planner applications. It provides the carbon footprint emission of each route and also analyses the car park availability in Singapore. This project designs a prediction model to provide the prediction of car park availability and reduces the time on the road while using the car. The report explains the processes of development of the application in frontend and backend side. Also it illustrates the building process of machine learning models and discusses the performance of predictions.