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Last week me and some colleagues took part in a hackathon here in Växjö. This hackathon was one of many events that took place during something called Digitala veckan, an entire week packed with IT-related events around the Linneaus university region. For those of you new to the concept, a hackathon is basically a competition in which programmers hacks away at a problem in a limited amount of time. In this particular hackathon, the challenge was to combine open data sources on the web and produce something useful for making our environment better. While HRM had two teams enlisted in the competition, this blog post is about our contribution. Say hello to Trash Friend.
The rationale for Trash Friend came to us while struggling hard figuring out what to do. We had been provided a list of example open data sources in-line with the overall environmental theme, but the data sources were admittedly not all that great and not always up to date. Moreover, our friends in the other HRM team were hacking away like crazy right from the start with a pretty neat idea, which made at least me feel a bit stressed out. We did come up with a few kick ass ideas right from the start too, but the open data sources were not fitting in nicely in any of those. What to do?
Figuring out what to do
After some headache we finally settled on an idea that were nicely motivated by another colleague of ours during a coffee break. One of the provided open data sources contain information about cars entering one of the recycling stations in Norremark, Växjö, and while brainstorming he said something like:
”They should have a webcam over at that recycling station. The queues can be terrible over there and you never know until you actually get there.”
Now, we did not have access to a webcam or any live data, but we did have access to the data set I just mentioned, which contained statistics over the course of a few months. It included data such as the time of visitors entering the station, the length of the cars (!) and the speed of the cars passing through the sensor. The latter two were not that useful for us, but the time of entry had some potential. Although there were no information about when cars left the recycling station, you could take a wild guess and say that the average time for a visitor staying at the recycling station is, say, fifteen minutes. Not that we actually had any coverage for that estimation, but for a hackathon such as this that estimation was perfectly fine.
With the time of entry and an estimation of how long visitors were hanging out at the recycling station, we could take a particular point in time, for example at three o’clock Friday afternoon, and calculate the expected number of visitors at that time. The algorithm we used to calculate that approximation was to historically look at the visitors to the station at that time on that particular weekday. From all of these occurrences we simply came up with an average to make the approximation somewhat reliable, that is, taking all Friday afternoons at three o’clock into account.
So, the idea we had was to make recycling easier for citizens and to relieve them from long queues at the recycling station. Such a tool has the potential to be beneficial in several ways:
- Avoid a high load of visitors; if a citizen has a way to find out that the queue to the recycling station is long s/he can decide to wait before deciding to pay a visit.
- Reduce the emission level at the station; cars in queue means that there will be more emissions, which leads to our next point.
- Improve the work environment for employees at the station; less emissions and less visitors at peak hours.
There are probably more points to such a list, but let us settle for those and head over to implementation details.
With the algorithm in place for calculating the number of visitors at the recycling station at a given point in time, we had one more crucial nut to crack – the information had to be super-easy to get a hold of. Would a web site do? For some cases yes, but remembering the URL of that particular site you tend to visit occasionally would not cut it. We wanted something that was just there when you needed it. Perhaps a notification could pop up in your smart phone when things are looking okay at the recycling station? Notifications are nice and all, but how could we possibly know when the citizen wants to recycle their trash? No, we needed something accessible that the citizen could consult when needed. And for this purpose a widget felt just right.
We finally settled on an architecture that involved three central components, described in more detail below.
RESTful web service
As the recycling central station data was encoded in a csv-file, we decided to crunch it and expose it in a format more suitable for our needs (i.e. JSON) via a simple RESTful web service. The technologies we chose for these tasks were Java and Spring Boot. With Spring Boot we had a RESTful web service up and running in no time, which was perfect for the time pressure we had during the hackathon. Aside from the recycling station data, service we build also included weather data. The weather data was fetched from an open weather data API and adjusted to the needs of the widget to inform the citizen about the weather conditions at the station. I mean, it is no fun to recycle your trash when it is raining.
Trash Friend Widget
The widget was developed for Android using Android Studio. This was the first time for me developing a widget, but after a while I got a hang of it and the result came out quite okay for a UI novice like me. As seen in the screenshot below, the widget presents a colored cycle to the far left. This icon indicates the status on the recycling station with one of the three colors red, yellow and green. A red circle tells you that you should wait your visit to the station for a later time, a yellow circle means that you probably will be in queue for a little while and, finally, a green circle means thumbs up, you should stop what you are doing and head over there right away.
|The Trash Friend Widget|
For a more concrete approximation (if there is such a thing) the text to the far right tells you the approximated number of visitors at the station at the present time. Finally, the weather icon show the weather conditions over at the station at the present moment. The information in the widget is updated every 30 minutes, which in my mind is acceptable as we are not dealing with live data (at least regarding visitor data).
But what if the queues are terrible right now? When should I go? To answer this question, the user simply taps the widget to launch the Trash Friend web application.
Trash Friend web application
The purpose of the Trash Friend web application is to answer questions just like the ones asked in the closing sentences of the previous section. When the widget is tapped, the default browser in your mobile phone fires up with an overview of the expected load of visitors at specific times throughout the current day (see figure below).
|The Trash Friend web application|
One can easily switch to a weekly overview by tapping the button ”Veckoöversikt” in order to see how the situation at the recycling station is expected to be later on during the week. This web application was developed using the Ionic Framework to make it mobile friendly right from the start.
So there you have it. In just a couple of hours we went from frustrated to pretty satisfied with what we had produced. And while we did not win the hackathon (due to stiff competition of course ;)) we pulled through and produced something that, if polished a bit, at least in my mind would be a valuable tool for citizens living near this large recycling station. If all recycling stations in Växjö would start to gather entry data it would be quite easy to improve the design to let citizens select their station to track in their widget. In Android, the way to configure widgets is to flip them over and adjust its settings. Imagine if available stations were available in a list in which you could select the station to track? A tap on the widget would then, naturally, direct the browser to the statistics at that particular station.
That’s all for this time, keep hacking! 🙂 By the way, the code we wrote is MIT licensed and available on GitHub.