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When: Monday, May 13 to Wednesday, May 15 2019
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Where: Kühlhaus Berlin 5th floor
- Available hardware
- Available software services
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Available: 3x E-Bikes with COBI.Bike unit and smartphones in HackMC area
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Contact person: coming soon
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COBI.js interfaces: https://cobi-bike.github.io/COBI.js/
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Chrome Simulator: https://chrome.google.com/webstore/detail/cobibike-devkit-simulator/hpdhkapigojggienmiejhblkhenjdbno
- Data from eBike Drive Unit
- Battery range, odometer, assistance modes
- Sensors embedded in mobile device
- GPS, Gyroscope, accelerometer
- External sensors
- Heart rate, cadence, speed
COBI.js - a JavaScript library that abstracts the Bluetooth connections, authentication or CAN BUS and allows the developer to focus on the data
The COBI.Bike app and Hub: https://cobi.bike/product
- Developers can subscribe to the streams of data they wish to access
- Available: 3x Rovers in HackMC area
- Contact person: coming soon
E.g. (live) Sensor Data
- Camera
- Gyroscope
- Ultrasonic sensors
- Infrared sensors
- Temperature
- Humidity
- Retrieve data from database (where it was stored through Eclipse Hono)
- Sending data to vehicle via HONO to vehicle API
- Send data to hosted Eclipse Hono instance
- Eclipse hawkBit and connected App-Store
- Eclipse Che instance to implement applications
- App development and deployment
- Push notifications
- Command & control of Rover
- https://www.eclipse.org/kuksa/
- https://www.eclipse.org/kuksa/resources/
- https://app4mc-rover.github.io/rover-docs/
Programmable dongle to access vehicle diagnosis port. Currently we work on integrating authorization flows into Eclipse Kuksa
- Available: 1x Jaguar I-PACE in front of building
- Contact person: coming soon
CAN Bus data available over HTTP
more information coming soon
- Available: 1x Track in the HackMC area with 4 cars
- Contact person: Pedro Silva
more information coming soon
- Not physically available, only data access on demand
Ask the Bosch IoT Insights Hack Coaches
Devices are typically connected to the Bosch IoT Hub, which pushed data to Bosch IoT Things. Changes of Things are recorded by Bosch IoT Insights and preserved for further analysis.
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Bosch IoT Insights
The easy way to manage your IoT device data
https://bosch-iot-insights.com -
Bosch IoT Things
Managed inventory of digital twins for IoT device assets
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Bosch IoT Hub
Easy and secure device connectivity for the IoT
Find our Hack Coaches on the Marketplace on the 2nd floor.
TBD: Logo, Description
- Contact person: coming soon
https://developer.here.com/documentation/fleet-telematics/dev_guide/topics/use-cases.html
- Gas stations (address, opening hours, div. features)
- Gas prices
- Car wash facilities
- Clever Tanken API
- Hack coach provides credentials
- OnMyWay: An app that shows the user where on his/her way the next e.g. McDonalds, Sanifair, Rewe, baby changing table, kids playground etc. is
- Gas price trend prediction
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Top News Teaser (between 9 and 11)
- URL to original source, image URL
- title, preview text
- publish time
- category
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this is live news data
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it is available for 10 locales, curated by several editorial teams
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it is updated irregularily whenever something interesting or relevant happens
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the content of the specific locales differs
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valid locales are: de-DE, de-AT, de-CH, nl-BE, nl-NL, fr-FR, pl-PL, en-GB, es-ES, it-IT
Requests to REST API:
curl -u 'api:<pw>' http://boschhackathon.topnews.upday.com/api/v1/top-news/{locale}
Password provided by Hack Coach
If you’re dev & sick of building all the messy stuff that comes along with coding production apps, such as connectivity to event-driven messaging platforms, datastores, SaaS apps, etc & want to deploy to a wide range of targets, such as
- serverless compute
- IoT edge devices
- containers
then Project Flogo is for you!
You can use one of our triggers to receive data. Examples triggers are:
- Kafka, MQTT, CoAP, REST, GraphQL, AWS Lambda, Timer, AMQP ...and many others
You can use one of our actions to process or send data back. Examples activities are:
- Log, MQTT, Kafka, AMQP, Trello, Write to File, Pushbullet, Tensorflow, IFTTT, AWS S3, RasPi GPIO
We have selected some of the triggers and activities to participate in the Bosch Mobility Hackathon:
- Send MQTT data: https://github.com/ayh20/flogo-components/tree/master/activity/mqtt
- Send AMQP data: https://github.com/skothari-tibco/amqp10/activity
- Recieve AMQP data: https://github.com/skothari-tibco/amqp10/trigger
- Recieve MQTT data: https://github.com/ayh20/flogo-components/tree/master/trigger/mqtt
...and you can contribute in the development of new triggers and activities as well.
Have also a look to our showcases with many more triggers, activities and apps
Project Flogo can be downloaded from github and more details can be found here https://github.com/tibcosoftware/flogo
A Web UI to develop with a zero-code approach is available via Docker (highly recommended for the Hackathon): https://hub.docker.com/r/flogo/flogo-docker
You can run Flogo on your laptop, on a edge device like a RasPi, on a container like OpenShift or even on AWS Lambda
The Flogo Web UI comes along with all required components to begin developing, testing and building deployable artifacts from your web browser.
Find our Hack Coaches on the Marketplace on the 2nd floor. We show you how to connect to the Bosch IoT Hub, receive device messages and build something cool!
Wouldn’t it be great to predict when an anomaly is around the corner and alert promptly that condition? By having the availability of a eBike or a RC rover, many sensors that equip those devices are sending data to the Bosch IoT Hub. These data can be used against a Machine Learning Model to detect and raise particular conditions.
Normally a bike has mostly two states, someone is riding the bike or the bike is stationary on its side stand. When the bike is being ridden, it has a velocity, is experiencing 3 dimensional GForces and is “mostly” in a vertical orientation but never horizontal. The bike may not be moving, but still the position is essentially vertical. But what has happened if suddenly the acceleration is negative, the Gforces are excessive and the position is horizontal? It almost certainly indicative that a crash happened. Under these circumstances, a notification can be sent immediately to the Fleet Manager who may want to call you and ask if assistance is needed. All this can be achieved with an event-driven application. This is where Flogo is your friend! Connect to the Bosch IoT Hub with a Flogo event trigger, process incoming sensor data from the eBike and evaluate the data against a Tensorflow-based Machine Learning model to detect various anomalies.
Good driving behaviour is key to getting bonus user points or a discount for the next eBike rental! But how do you identify a good versus a bad driver? An eBike has many sensors, sending data like acceleration, speed, position, inclination. What if the acceleration, the speed and the angle of inclination of the bike can be used to determine driving behaviour? If there are frequent accelerations/decelerations and the angle often changes, that could identify a bad driver. In that case, a message is sent back to the Bosch IoT Hub for further processing.
eBike doesn’t want their money makers to just wander off and never be scene again. How do you discern between a valid rental and theft? Can the acceleration, speed, position, and inclination be used to detect if a bike has been put in a truck?
Nowadays all vehicles are fitted with multiple sensors. They’re used to get feedback of the position, inclination, speed, g-forces, temperatures, etc. But what if a sensor is malfunctioning? If a sensor used to send a reading each 2 seconds and suddenly that reading doesn’t come or the intervall isn’t regular, we may conclude that the sensor has failed or will fail in the near future. By deciding which sensors are the most critical ones, we could monitor if the reading are arriving when expected and eventually raise an alert in order to proceed and replace the faulty sensor.
TBD
Get a Matlab license for the hackathon and get support from the Hack Coaches.
TBD
A real-time data messaging protocol for the decentralised web.
Streamr is building the open source infrastructure that will power the world’s data economy. We believe that creating a decentralized Network and the world’s leading Marketplace to trade, swap and share the world’s information will benefit everyone. People will regain control of the data they produce. Companies will be able to better build, market and monetise their products in the Internet of Things (IoT). And society as a whole will be better off when the value in data is not concentrated in the hands of a few giant companies but distributed amongst everyone who creates it.
- Decentralized P2P network for live data delivery
- Publisher-Subscriber model
- Open ecosystem
Data monetisation layer for live data from connected vehicles, smart city, consumer devices
- You can create an eco-system of
- data sellers providing raw data
- companies extracting higher level information from raw data and reselling it
- refined data consumers
Drag and drop tool for quick data stream visualisations and analysis (charts, maps, code blocks..) Functiallity to call smart contracts and execute ethereum transactions based on incoming data
https://marketplace.streamr.com
https://www.streamr.com/help/api
https://streamr.dev (unofficial community managed tutotials)
In case of any questions find Martin at Trusted IoT Alliance stand.