ParkMate

logo
main page
matching result
searching result
matching page
searching page
listing page
loading animation
feedback

Inspiration

The journey to home or work is never easy in sydney. Train disruptions, long commute hours, the pressure of catching COVID in a public area, and of course, the-never-available on-street parking spots in the city. The City of Sydney has once recorded an extremely low ratio of parking spaces available per person employed in the CBD (12 spaces being available for every 100 workers). While a driver on average would spend around 3,000 hours in his or her life in finding car spaces, the urban planning policies and the price of building car spaces, are stopping the government in providing more car spots for drivers. Subsequently, people like white-collar workers and holiday drivers often have unpleasant driving experiences in the not-so-vivid-sydney.

On the other side of the problem, companies who have their parking lot and individuals who own their car space(s), are desiring a car space management system. They want to utilise their assets in a commercial sense, however, the existing solutions often fail them as they are not flexible, unstable and ingenuine. Hence, ParkMate is created to deal with this tangled chronic issue.

What it does

ParkMate is a website (hopefully an app in the future) that provides the ‘search and book’ function of the available listed car spots. The owners of parking lots can register their spaces through ParkMate to get potential rental deals and the estimated rental value of the area in real time. The match function allows the flexibility in finding a car space available in drivers’ preferred schedules (i.e., every Monday, Tuesday and Friday), in response to change of work mode.

How we built it

ParkMate was built using React Javascript. We use Google Map API to fetch all the map, route data for users to do listing/finding/matching. When users are trying to do finding/matching, ParkMate will recommend the best matching result based on other parking’s location and review. . We have also tried to include the mathematical model to predict the best rental price based on the market’s demand in real time. Besides, we have used different react libraries to style it, such as antd, mui, emotion.

Besides, we have spent much time finding a way to integrate the mathematical model into the product to increase the matching accuracy.

Challenges we ran into

We are a team of 2.5 people since, very unfortunately, one of our teammates got COVID the day before the hackathon. It is difficult for a small-sized team to come up with a solid problem and a sound solution at the beginning.

Time limit pushes us to a next level, we are very sleep-deprived but have enjoyed the most out of it.

Accomplishments that we're proud of

We are most proud of the dispersion of the specialisation of our team, we all have our own profession and we still managed to allocate the work in an effective manner.

We are able to think big and further, in terms of technical complexity and prospects of the app development. Putting our thoughts ahead of the status quo of a problem is an awesome way to do problem-solving!

What we learned

We have learned to use different google map api to integrate the auto-completion and map functions to our product. Also, we have learned how to use massive react libraries to style our design.

It was challenging but fun to learn and think of different crazy ideas with a tight time limit.

What's next for ParkMate

ParkMate has a long-term vision in developing its capability, we aim to

Improve algorithm for higher accuracy in matching the right user
Develop an app for better UI and UX
Integrate machine learning to filter, hide and suspend suspicious or underperformed accounts