Just like the last two years, I’ve sacrificed one of my weekends to fly to HackZurich, one of the largest hackathons in europe. I brought a couple of my fellow students and the plan to create something fancy during the 40 hours of coding time available. But for some reason, we couldn’t really agree on any project – so we tackled a very unsexy topic: elevators.
What’s wrong with elevators?
I have no idea. We just felt like the logic that is currently in use to control elevators could use some improvements. Currently, elevators stop on the level where the last person got out. That works ok and consumes the least amount of energy. However, it’s not very clever. Think about an office building where 50 people would start their work day in the 3rd level, all arriving at about 9 am. People would have to request elevators back to the ground floor when they arrive every time.
A smarter logic
Our approach changes the behaviour of elevators when they are not in use. Take the office example mentioned above. Our control logic would send idle elevators straight back to the ground floor, ready to lift the upcoming group of people up. We predict the levels that idle elevators should move to by looking into the past. We are tracking on which levels people requested elevators (depending on the time of day) and assign each level a score. Based on that score, we can evaluate which level we should send elevators to.
Above you can see a comparison of our smart elevator logic (left) and the default elevator logic (right) at 200x speed. We use gaussian distribution to generate a number of people (rendered as squares) that work at specific times on specific levels.
Imagine a building with 6 levels, 4 elevators and 500 people using the elevators over the course of a day. With the default logic, we measured an average waiting time of 27.6 seconds. With our smarter logic, the average waiting time dropped to 14.8 seconds! This time saving adds up if you think about it in the long term.
The Apps World came all the way to Berlin this week, so I decided to check it out and was happily surprised that there was a hackathon ongoing when I arrived! Of course I joined, together with my fellow student Jonas Pohlamnn. Spoiler: great success!
The Albert device
One of the sponsors was Wincor Nixdorf – the company behind the Albert, an Interactive Multifunctional Payment Device that runs Android (see above image). You can imagine a lot of retail stores having these devices in the future – we created an app for the albert that customers and sellers will benefit from.
The ReMerchant app
ReMerchant allows you to track and identify customers in stores using nothing but the Albert device. It uses Bluetooth and assigns the unique addresses to customers. When a device comes in range of the Albert, it can detect the associated customer.
Knowing which customers are near by is a huge thing for stores. Store owners can prepare items based on the last purchases of that user, they can track in which other stores the customer has spent money and on which items, they can provide an overall more personal customer treatment. If you can’t imagine all the possible advantages of this, take a look at our presentation slides.
The jury did see the potential of our prototype and rewarded us generously. As usual, the app is open-source and available on GitHub, feel free to check it out:
I’ve spent the past 48 hours at the HPI Hackathon sponsored by eBay Kleinanzeigen and mobile.de, but this time I organised the event together with 2 of my fellow students. Of course I couldn’t resist and hacked together a little app together with Jakob Frick, the so called Estirator!
The app will show you a bunch of eBay item listings, but only one at a time and without mentioning the price of that item. You now have to estimate a price for each item, just based on the photo and title.
After you have done that, the app will show you all the items that you have previously estimated – but this time it will tell you the real price.
But, what’s the point?
The estimated prices from each user are coming together in a cloud database hosted on the Google App Engine. It can generate a ranking of items that are currently available on eBay, sorted by how much under worth they are sold.
Advantage for users: After they have contributed to the database by estimating items, they can find super cheap offers within seconds.
Advantage for sellers: They can get an idea of how much customers are willing to spent for their products.
Advantage for eBay: Possible A/B testing for product photos and their influence on the customer.
The app is open-source and available on GitHub, feel free to check it out:
You probably know about FarmVille, a game where you can build a farm in your browser. The problem is that you only have a virtual farm so you will never eat your harvested fruits. Remote farming provides the possibility to plant, water, fertilize, and harvest your own plants in real life taking into account concepts like social media and gamification. This app enables you to monitor the growth of your plants by checking live sensor data and even lets you watch the plants grow using a Webcam – literally.
Together with 4 of my fellow students I participated at this years InnoJam in Berlin, a coding challenge contest where you get to learn about SAP technologies and partner with participants to build a prototype solution for a real-life business scenario or need. The theme was Internet of Things for the Agricultural Industry, so we came up with Remote Farm – and won the InnoJam.
By winning the InnoJam we won the possibility to pitch our idea in front of a few thousand people at the SAP TechEd && d-code DemoJam. Six well prepared teams competed with us on stage, all having only 6 minutes to give a live demonstration of the apps. And it was up to the audience to choose the winner (with the help of the Clap-o-meter). We managed to convince the audience and also took home the prestigious DemoJam medal. You can take a look at the video of our demo presentation and at the live studio interview with Craig Cmehil, Global Director Developer Relations at SAP.
Get rid of your presenter and instead use your smartwatch to switch between slides. Skip the current track on your computer while sitting on your couch. Turn on the lights in your flat when you come home. Hook your smartwatch up to Arduino, Raspberry Pi or any other IoT-ready device and use it for whatever you want.
Remotify is an Android Wear application that has been developed in 40 hours during the HackZurich hackathon by Leo Kotschenreuther, Fabio Niephaus an Stephan Schultz. It allows you to control any device with Internet access. Watch the demo video above to get a sense of what this prototype can be used for. It was nominated as finalist out of 101 other porjects from 350 participants and won the Google award as the best application with support for Android Wear.
Remote Control Collection Integration
The app matches well with the Remote Control Collection app for Android, which already has a community of over 1 million users that like the idea of home automation. For that reason, Remotify will be part of the Remote Control Collection and provide support for Android Wear, extending the usability even further. It will be available for users through the beta community on Google Plus.