Inspiration

Using public transport is such a hassle and most of the times it's uncomfortable - there are sweaty people everywhere, it's noisy and there is seat available to sit!

Enter ComFi or Comfort Fidelity, we are committed to improving public transport and saving energy too! No more congested trains and buses - at least not for the users of ComFi. Transport authorities love us too, since we give them necessary data to optimize their "fleet". Obviously the government is totally for it as we distribute people over many vehicles and improve the cities infrastructure.

What it does

the Intel Edison kit with noise and temperature sensors to calculate the amount of people and the temperature in the vehicle and therefore we give suggestions for the users to maybe avoid the next full bus to take the train that is empty. Furthermore we know when there are very few people in the vehicle and if the temperature is low, which means that the AC is turned on too high. By turning the AC off then we can save money and energy for the transport authority. As we are also using Here maps for navigation we can get all the related traffic and transit data from the REST API

We collected data of all the rooms in the hackathon & created chart with temperature, light, sound, vibrations, noise level.

How we built it

Intel Edison, grove starter plus kit

Grove sensors used,

  • Grove - Temperature Sensor V1.2
  • Grove - Sound Sensor
  • Grove - Piezo Vibration Sensor
  • Grove - Light Sensor
  • Grove - 3-Axis Digital Accelerometer(1.5g)

Challenges we ran into

Integrating everting into iOS, relayr and Edison

  • Enabling Relayr iOS SDK to be able to use data from the Edison board on a iOS device in real time.
  • Finding the consumable format of the sensor output data.

Accomplishments that we're proud of

We built it today!

Extra: Anaylsis of a quite room in the hackathon based on our collected data in all the rooms.

What we learned

Time goes by fast when you're discussing too many ideas.

What's next for ComFi

Integrating more features, making the algorithm better for every day use.

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