Bounty: Mix and Mashup
How can we combine the uncombinable?
Go to Challenge | 61 teams have entered this challenge.
Team Name:
The Hackermen
Team Members:
Congestion Management System
Project Info
Team Name
The Hackermen
Team Members
4 members with unpublished profiles.
Project Description
We will use historic data sets that cover parking duration/occupancy, pedestrian traffic, congestion maps, and air quality, to establish a base line for congestion in the Noosa’s Hastings Street area. We will then develop vehicle counters to collect data in real time, to provide a live feed on car parking availability in the local area. We will also use air quality sensors to provide a live feed of the level of vehicle emissions in Hastings Street.
Using roadside signage and online updates, visitors will be advised to divert to public transport or park’n’ride locations when there is low parking availability, or poor air quality due to excessive vehicle emissions, in Hastings Street.
Data Story
We utilised Noosa Parking occupancy and duration of stay reports from early 2018, additionally source data from google live traffic was used for this peak tourism and business time.
DATA SETS WERE PROVIDED VIA EMAIL FROM NOOSA HUB !
Team DataSets
Google Live traffic feed
Description of Use This live data was checked during the day to find trends in demand and congestion levels. This data was also used to correlate between estimated travel times and actual.
Live traffic cameras on the Sunshine Coast
Description of Use This live feed and historical images were used to analyse the traffic during peak demand and see how the congestion affected traffic flow.
Queensland Live traffic
Description of Use Data was used to analyse trends and congestion levels on Hastings St Prescient. Data was also used to check off peak trends and peak business and tourism season trends
Air Quality readings
Description of Use Data was used for checking readings of Air Quality and their link to congested areas with high traffic flow
Smart Parking
Description of Use Data sets were queried to check the frequency and common trends of the parking in the congested areas. This data was used to determine car park trends within peak times and how the use of these parking spots with the aid of google maps can lead to congestion in busy areas.
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