This project proposes a traffic data visualisation as an interactive web application service. Using real-time data from data mall (bus location, taxi availability, road speed, highway camera, and accident data) and Singapore NEA weather services (rainfall forecast and weather forecast), it generates current traffic speeds and a number of charts for a quick update of the current traffic conditions as well as a comparison with historical trends. One can easily correlate data from different sources to explain congestions and other traffic outliers. The data will continuously update to reflect the latest traffic conditions.
This project employs the following technologies, such as python, nodejs, elasticsearch, and open street map. This configuration provides an effective and scalable way to retrieve data from multiple sources and to present them to the users in a real-time manner. The ability to toggle between different view allows users to focus on the traffic conditions at different regions of Singapore. Highway cameras enable users to see the actual traffic condition. Another feature this project offers is historical trends in the last 24 hours. Weather information from NEA provides additional data on how this affects traffic. In conclusion, with all of these features, users can easily observe and monitor the Singapore traffic conditions.
This technology is applicable in the following industries:
(a) Transportation Agency
(b) Public Commuters
In the fast-changing world we live in, accurate information plays an important role. Realizing this trend, this project was specifically designed to provide real-time information by combining data from different sources to help users to observe Singapore traffic conditions. The visualisation also helps to explain traffic congestions and other traffic anomalies in Singapore.