Team Name:
Pakers
Team Members:
Pakers
The Happy Parking! project aims to make the most use of the open-source data from government solving practical problems and tell stories of urban development according to historical car park data.
Parkers aim to create a real-time web app for end-users, helping drivers to find a vacant spot efficiently.
It allows users to select the location they want to go and get them all vacant car parks in the area within 500 m and match the car park restrictions with duration they are willing to park. It has a priority rank for the matching function -- free first, within the area, outside area. If there are no vacant spots in this area, users can also use the off-street car park locations to find a car park.
At the government end, the real-time parking solution can help reduce the air pollution or traffic problem that caused by circling vehicles for vacant spaces as well as reduce the time wasted in finding a vacant spot, especially in the city area.
On the other hand, the visualization shows the land utilization in a more straightforward way, which supports the government to monitor and make a decision to improve quality of life.
In addition, the web app also provides a visualization regarding the analysis of the parking area occupancy rate based on historical data of the past years.
It demonstrates the occupancy rate changes in each street with inground sensors according to their timestamps. Regarding these car park analysis data, it enables users to understand the urban planning in Melbourne and the changes in economic centres. Moreover, support the government’s urban planning decision in car parking, Remove car parks with low occupancy rate and build greenspace or improve public transportation network construction to reduce car park stress.
The datasets provided by the City of Melbourne identifies the location of car park bay and vacancy in real-time told by in-ground sensor systems, which allow us to consolidate information and generate parking solutions for drivers.
For historical archived data, they give a knowledge about how well the parking systems are utilized, thus, the government could benefit from them to make a decision in respect to city resources planning.
we judged the occupancy rate on the peak hour(6:30-9: 00 am & 3:00-18: 30 pm) and whether it is the weekdays and weekends to make a comparison for each car par zone.
Description of Use Getting the off-street car park location and capacity.
Description of Use Getting the on-street car park usage data in 2014
Description of Use Getting the on-street car park usage data in 2015
Description of Use Getting the on-street car park usage in 2016.
Description of Use Getting the on-street car park usage in 2017
Description of Use Getting on-street car park bay restrictions.
Description of Use Getting on-street car park bay locations.
Description of Use Getting real-time on-street car park status.
Go to Challenge | 21 teams have entered this challenge.
Go to Challenge | 27 teams have entered this challenge.
Eligibility: The winning entry will: * Be an interactive/gamified solution * Use time based data to show change across the city * Use at least one City of Melbourne Open Dataset
Go to Challenge | 10 teams have entered this challenge.
Go to Challenge | 17 teams have entered this challenge.
Eligibility: Use at least two data sets (at least one from data.gov.au) to help government make a decision that will improve services for people. Any code produced for your entry must be published on github under an open license. If your entry is not software, you will need to show the working behind your use of data along with any calculations and analysis you did. You must indicate which specific government agency (at any level of government) can take action based on your entry.
Go to Challenge | 58 teams have entered this challenge.
Eligibility: The winning entry will: * Visualise a comparison of car parking with other potential uses of on-street car parks. * This will quantify the economic contribution of an on- and off- street space and what it could contribute were it put to alternate uses. * Use at least one City of Melbourne Open Dataset
Go to Challenge | 8 teams have entered this challenge.
Go to Challenge | 61 teams have entered this challenge.
