Project description

Helvar provides excellent smart light solutions for office spaces. The system of indoor lights generates and collects much of informative real-time data like brightness levels, power consumption and so on. To access that data, the user has to go through the API which is hard for a non-coder. In addition, it can get difficult to keep track of each smart light with the ID and not the position. To solve this matter we created a dynamic and interactive interface based on Helvar’s office indoor map.

Here are the key features-

  • Target audience is office admin/maintenance engineer who can query information about the lights remotely and even control light settings.
  • Based on original office map, it is easy to locate light source. Map is scalable and zoomable.
  • Information available-
    • Device ID
    • Current Light Level
    • Current Power Consumption
    • Light Level summary over last 3 days
    • Power Consumption summary over last 3 days
    • Live video feed from infrared cameras which shows amount of people detected
  • Controls available-
    • Slider to update Light Level

Use Cases-

  • Office admin can check average number of people in the office and can increase/decrease light levels accordingly.
  • Office admin can monitor power consumption of lights using the charts and check up on a light if a strange trend is detected.

This project is a prototype for a more advanced and scalable system with features like-

  • Smart notification: when strange trends are detected in a light source, the user will get a notification in the dashboard.
  • Find meeting space: using the camera and trends of how many people are in a space at given times, optimal meeting space can be found.
  • Scalable map creation: the base indoor map will be created using beacon technology.
  • Smart configuration of lights (please check the simulated images): Based on historical human activities, lights can be configured automatically in each day


  • Backend code is processed in Python.
  • Camera information processed using OpenCV.
  • Web dashboard works with Django framework.
  • Maps are created using Leaflet JS library.
  • Interface is built with Bootstrap.
  • To run app type ./ runserver and open http://localhost:8000/
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