Difference between revisions of "Projets-2016-2017-Plateform Analyse Données IOT"

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** KNX gateway, prepared as a binary image that can be written to an SD card for a RaspberryPI
 
** KNX gateway, prepared as a binary image that can be written to an SD card for a RaspberryPI
 
** Porgramming the Spacelynk in LUA
 
** Porgramming the Spacelynk in LUA
  +
  +
http://www.schneider-electric.fr/fr/product-range/62958-spacelynk/
  +
http://download.schneider-electric.com/files?p_Doc_Ref=ZZ5354_FR
   
 
* Worthwhile data analysis : temperature and energy consumption compared to weather, indoor air quality
 
* Worthwhile data analysis : temperature and energy consumption compared to weather, indoor air quality

Revision as of 00:11, 4 February 2017

Team

  • Supervisors : Daniel Hilaire, Jean-Louis Bergerand, Nicolas Palix, Olivier Richard
  • Members : Estelle Allard, Lambert Rocher
  • Departement : RICM 4, RICM 4, Polytech Grenoble

Week 1 (January 9th - January 15th)

  • Choix du projet et compléments d'informations concernant les objectifs du projet

Week 2 (January 16th - January 22th)

  • Discovery of the project
  • Contatc with Daniel Hilaire and Jean-Louis Bergerand
  • Search for information on Docker and OpenHab
  • Statement of requirements

Exigences

Meeting with Daniel Hilaire and Jean-Louis Bergerand (Wednesday 18/01/2017)

  • Two possible solutions to retrieve data collected by the house sensors :
    • KNX gateway, prepared as a binary image that can be written to an SD card for a RaspberryPI
    • Porgramming the Spacelynk in LUA

http://www.schneider-electric.fr/fr/product-range/62958-spacelynk/ http://download.schneider-electric.com/files?p_Doc_Ref=ZZ5354_FR

  • Worthwhile data analysis : temperature and energy consumption compared to weather, indoor air quality

Week 3 (January 23th- January 29th)

  • Création d'un diagramme des cas d'utilisation

Diagramme des cas d'utilisation

  • Execution of a docker image running influxDB and grafana (dockerfile found on dockerhub).
  • Manual addition of data in the database using the http api.
  • Visualization of these data in a grafana dashboard.