The theme was Internet of Things (IoT) and this marked the first time that they organized a hackathon specifically for an outside partner, eProseed. All the previous hackathons were internal Oracle events. Initially the plan was for us Oracle folks to go over and mentor teams as needed, but later on, the decision was made to place us as technical resources in a team and actually participate. After some initial hiccups with my own team, I ended up in a team with Lonneke Dikmans (@lonnekedikmans), Karel Bruckman, DJ Ursal and Antonio Aguilar. Here’s what happened next …
If you have ever been to the Netherlands, you probably noticed they like bikes … a lot! This is the first thing you see when you get off the train in Utrecht:
Not exactly organized.
Lonneke’s team’s idea was to solve this with some IoT ingenuity. We tried to solve the following issues:
- For the individual:
- Where can I park my bike, i.e. where are there free bike parking spots?
- Where did I park my bike?
- How do I pay?
- For the city/municipality/parking management company:
- Where are there free parking spots?
- What is the overall usage, for parking management/planning?
- How long has a bike occupied a parking spot, for payment?
The tools at our disposal where a Raspberry PI with a fully loaded GrovePi kit and an Oracle Mobile Cloud Service (MCS) account. We were free to use any other tools as needed, but we decided to stick with these as they were freely available. Plus, we had direct access domain experts on site.
We used sensors in the GrovePi kit to detect a bike’s presence in the bike rack. As soon as we detected a bike being put into the rack, we used a Raspberry Pi camera to take a picture of the (presumably) bike owner and identified the person using her/his own phone. Users of the parking system had to register themselves so we could identify and charge them, but this part we did not build as part of the hackathon. We then sent a notification to the person’s phone using MCS. This notification contained the picture we took, the location of the bike and the time it was parked.
The location of the bike could be traced using a phone app and a web application. This app could also be used to keep track of how long the bike had been parked and how much this was going to cost the the user.
As soon as the bike was removed from the bike rack, another notification would be sent to the bike’s owner through MCS informing her/him of the usage time and how much the charge would be, and the system would automatically charge the user.
Besides the app for end users, we also had a dashboard that could be used by the parking management company. This could be a municipality or a for-profit company. The dashboard web application gave an overview of bike distribution throughout the company’s territory, e.g. the city.
This would allow the company to direct cyclists to places where there were free bike racks. Over time, we would also collect bike rack usage data that could be used to enhance parking infrastructure and overall usage, e.g. with this data you can predict usage peaks and proactively redirect cyclists, plan where more parking is needed or inform city planners on how to avoid “parking hot spots.”
In the end, our entry was good for third place.