Hackathon Stuttgart 2018
Hackathon ’18 after video
Winner Teams 2018
Gallery 2018
Winner Teams 18
Best Idea:
Scitlab – Framework for instant apps (e.g. triggered by beacon an instant app opens itself when passing the machines for showing machine data or service cases)
Scitlab provides the user with an all-in-one Solution for apps with a situation and/or location dependent use case. It eleminates the need to manually install the full app, instead it uses ressource friendly, lightweight, transient, webapps with mutiple advantages over conventional app competitors
Used platforms, gadgets:
Adamos, Festo Cobot, Cobi.Bike, Raspberry Pie, iBeacons
Best Pitch:
Robosweep – Combination of bleeding edge technologies to clean the floor in a battle against friends by controlling a vacuuming robot from the phone.
Tired of the annoying task of vacuuming the floor? Make cleaning fun again by combining bleeding edge technologies with the ancient art of sweeping the floor!
Compete against your friends in a battle of cleaning the largest area by controlling a vacuuming robot from your phone.
Used platforms, gadgets:
Bosch IoT Cloud, Firebase, Raspberry Pi, Webcam, Kärcher RC3 Premium, VR “Headset”, MongoDB, REST-API, Websocket, React, Node.js, iOS/Android-App
Best Implementation & Kärcher Challenge:
Awesome Käse – Conversion of a Kärcher cleaning car into an autonomous driving and reacting car
We want to turn the KM50/80 into a robot, which is as most autonomous as possible.
Actuators:
– We attached a handlebar to the steering wheel, so you can steer it with a belt train
– hardware emulation of the accelerator pedal (exchange potentiometer)
Sensors:
– Laser scanner
– Reading the steering angle via potentiometer
The laser scanner at the front detects objects in front of the machine and alerts the driver optically and acoustically when the minimum distance is reached, and initiates emergency braking if required.
The laser data also records a map of the area, which has to be cleaned. Since the position of the robot is known during the whole cleaning process, it can be checked whether the driver drives too often around already cleaned areas.
The map is also the basis for an autonomous drive, even though the autonomy was not implemented until Saturday evening.
By controlling the steering and accelerator pedal, the robot can be remotely controlled via WLAN, with the laser scanner monitoring the drive.
Used platforms, gadgets:
– TCU: reading the speed, audible warning
– Hectorslam (2D mapping library from ROS)
– Laser scanner
– LED strip + Arduino Uno as a display for the driver
– stepper motors (as drive and bearing for the steering belt)
– Holders for laser scanners from Markerbeam
– Mounting drive motors from Makerbeam, cord, expander
– Candump and Cansend (to read the complete Canbus of the KM50/80 and write directly to CanOpen-SDOs)
– Steering angle: potentiometers in self-designed and 3D-printed cogs with custom fit for the steering column
– Tinkerforge Bricks:
- Reimplimantated ROS bridge
- Silent stepper
- Master
- IMU
- ADC
- DAC
Work in progress:
- Voice control via snips
- TeamViewer IoT
- Access to weight monitoring in the seat
- emergency braking
- Autonomous driving by waypoints
Crowd’s Prize:
Cloudrider – Conversion of analog machine displays into digital dashboards
ADAMOS Challenge:
Insert Teamname here –Team service process automation: optimization of the maintenance process through automated spare part recommendation and report generation
Save time and money during the maintenance process by automatized solutions during a spare part changing process.
- Service technician triggered by sensor values
- Automated recognition of changed parts and time of the maintenance,
- Automated report generation
- Automated billing process
Used platforms, gadgets:
Adamos, AWS, Raspberry Pi, Tinkerforge, KonfiPay
Bosch Challenge:
Scooby effect – self managed car with fleetservice interface, budget management and insuring itself
Creating a self managed car with Fleetservice Interface, Budget management and insuring itself. Driving to Service-Stations (Repair, Cleaning, refuel) on its own. Paying bills if in Budget directly, otherwise by manual decision through Fleetservice.
Used platforms, gadgets:
AmigoBot (The Mystery Machine), ROS, Adamos, Konfipay, Getsafe, REST API, Python, Linux, Raspberry PI, Bash, Putty, Node, Vue.js, Vuex and Coca Cola
Festo Challenge:
R.I.C – An interactive game combined with Festo Cobot, Alexa and Philips Hue to keep the elderly active and boost their mobility
An interactive game to keep the elderly active and boost their mobility.
Used platforms, gadgets:
Festo Cobot, Amazon Alexa, Lidar Scanner, Philips Hue
Lenze/logicline Challenge:
#MakeCodingGreatAgain – smart bottle to track personal consumption of liquids which can be combined with COBI.Bike and getsafe insurance
To deliver high performance in your workplace and during your outdoor activities like cycling, you require a proper intake of liquids. In a second scenario, we focus on elderly and hospitalized people. They too require proper monitoring of how much they drink throughout a day.
Therefore, we create a smart bottle that tracks you personal consumption of liquids. It reports your consumption to a cloud backend, can be combined with cycling applications, such as the one provided by COBI.Bike, and can also be used to signal your Getsafe insurance that you care about your physical health to make you eligible for a bonus.
Used platforms, gadgets:
Adamos (not yet implemented at the time of writing), Arduino, COBI.Bike (not yet implemented at the time of writing), Flow sensor, Gyro sensor, Getsafe API, Heroku, internetstores bottle
Finance Challenge:
bikewatch – bike parking which cares for automatically payment; bike will be automatically insured against theft using Heroku and getsafe
Just park & walk away…
… everything around you will take care of your bike
… we will take care of the payment automatically
… your bike will automatically be insured against theft
… you only pay for the time you park
… pay lower fees if there are more bikes around you and the area is considered as safe
Used platforms, gadgets:
– raspberry pi
– heroku
– GetSafe
– MQTT
Summary of pitched Projects ’18
There’s usually a time in the middle of the afternoon, after you’ve noshed your lunch and gotten much of the day’s work under your belt, where you start to hit an energy wall. Sound familiar?
A brief nap in the early afternoon can reduce fatigue, improve brain function, and even improve physical performance.
Sound amazing? Hold on! There’s much that you can do wrong!
How Long Should a Good Nap Be? When Should You Nap?
The solution: HappyNappy not only reminds you at the right time to take a nap but also ensures that you wake up in the right moment – by calculating the perfect duration with your daily activity history, health data, and in-nap live data from your Apple Watch!
For the perfect wakeup-experience you can connect Phillips Hue Lights, Alexa Music, or catch a crazy Spheroball in your room.
The better the nap, the better your health, the happier your life.
And to top it off, HappyNappy is connected to your Health-Insurance to get lower costs for healthier naps.
Used platforms, gadgets:
iPhone, Apple Watch, Spheroball, Alexa, Phillips Hue, NodeJS, TinkerForge
sensory kit for mobile measurement of fine dust, air pressure, humidity& temperature
easy to attach on a drone, e-bike, etc
data collection in our database
real-time visualization (browser, app, COBI application,…)
Used platforms, gadgets:
REACT, cordova, influxdb, Node-RED, Aduino Pro Mini, SIM800L, SDS011, BOSCH BME280, GPS, COBI e-bike application,
mutiple advantages over conventional app competitors
Save time and money during the maintenance process by automatized solutions during a spare part changing process.
- Service technician triggered by sensor values
- Automated recognition of changed parts and time of the maintenance,
- Automated report generation
- Automated billing process
Used platforms, gadgets:
Adamos, AWS, Raspberry Pi, Tinkerforge, KonfiPay
With multiple Data inputs like Gyroscopes, speed and position, we detect if the driver of a bike has an accident and automatically notify help in case an accident occurs.
Used platforms, gadgets:
Arduino, CobiBike, NodeJs, Glitch.com, MongoDB,
IBM Bluemix Cloud with Node-Red. PLC connected via MQTT to IBM Bluemix Cloud. Controlling of the PLC via Node-Red and Amazon Alexa.
Used platforms, gadgets:
Amazon Echo, Node-Red, PLC, MQTT, IBM Bluemix Cloud
Komutigi is an app that captures the route of employees on their bikes and gives the company the opportunity to pedal kilometers together. This information can be used for different Uscases.
- Who is the busiest cyclist in the company? Who is the most industrious cyclist in the team, even if the outside temperature is below 3 degrees Celsius?
Collect trophies and compare yourself with your colleagues.
- Your company takes over the bicycle insurance for you if you have come more than x times in the month with the bicycle. Safe on the way to work.
- Your company donates an amount to an environmental fund for every kilometer driven by employees on their way to work. Doing good together.
Used platforms, gadgets:
Cobi.Bike, Heroku, getSafe*, Comfipay*
*Wenn wir noch dazu kommen
Innovative stock trading with innovative user interfaces. Buy and sell stock using a Sphero Bot, an eBike, and get instant Feedback via Sphero Bot or Philips Hue light color and intensity.
Used platforms, gadgets:
- Adamos cloud platform
- Sphero Bot
- Heroku
- QuickFix – CATS – Börse Stuttgart
- Philips Hue
- COBI
An awesome AR-App for multiple players where the fate of the world is at stake. There will be one true hero and the others fight against him in the role of wild monsters. The controls of each player are unique, including gesture control, a classical joystick and a controller-app. In addition the dynamic monsters there are static monsters and obstacles to overcome in order to save the world.
Used platforms, gadgets:
Sphero Mini, Sphero 2.0, Raspberry Pi 3, UDDO-Board, AmigoBot, Kinematic Wristband, Tinkerforge(Master,WIFI 2.0, JoyStick,Accelerometer), Node.Js,Android,ROS,React,Unity-3D,TypeScript
Creating a self managed car with Fleetservice Interface, Budget management and insuring itself. Driving to Service-Stations (Repair, Cleaning, refuel) on its own. Paying bills if in Budget directly, otherwise by manual decision through Fleetservice.
Used platforms, gadgets:
AmigoBot (The Mystery Machine), ROS, Adamos, Konfipay, Getsafe, REST API, Python, Linux, Raspberry PI, Bash, Putty, Node, Vue.js, Vuex and Coca Cola
We want to turn the KM50/80 into a robot, which is as most autonomous as possible.
Actuators:
– We attached a handlebar to the steering wheel, so you can steer with a belt train
– hardware emulation of the accelerator pedal (exchange potentiometer)
Sensors:
– Laser scanner
– Reading the steering angle via potentiometer
The laser scanner at the front detects objects in front of the machine and alerts the driver optically and acoustically when the minimum distance is reached, and initiates emergency braking if required.
The laser data also records a map of the area which has to be cleaned. Since the position of the robot is known during the whole cleaning process, it can be checked whether the driver drives too often around already cleaned areas.
The map is also the basis for an autonomous drive, even though the autonomy was not implemented until Saturday evening.
By controlling the steering and accelerator pedal, the robot can be remotely controlled via WLAN, with the laser scanner monitoring the drive.
Used platforms, gadgets:
– TCU: reading the speed, audible warning
– Hectorslam (2D mapping library from ROS)
– Laser scanner
– LED strip + Arduino Uno as a display for the driver
– stepper motors (as drive and bearing for the steering belt)
– Holders for laser scanners from Markerbeam
– Mounting drive motors from Makerbeam, cord, expander
– Candump and Cansend (