The intelligent light control system, located in a room equipped for this purpose
at the Department of Control Engineering and Information Technology gives its users the
ability to remotely set a desired light level. The light control system adjusts the
illumination of the given room to the level set by the user by controlling the LED light
sources and getting feedback from the sensors, thus also eliminating the effect of
disturbance light sources. In this BSc thesis, I am going to extend this system with a selfdiagnostic
feature.
The self-diagnosis module has been written in C++, and can be executed on an
Arduino board. The major factors at the selection of the method were the time constants
of the illumination sensors, the noise tolerance, and the configurability to the
experimental room.
I also implemented and integrated a data logging feature into the system. This
allows the recording of various signals from the sensors (measured illumination and
presence), and the control values of the LED panels. Furthermore, this logging system is
able to log the results of the self-diagnosis tests.
The principal consideration during the design of the database model behind the
data logging feature was to reduce the amount of the redundant data, and that the model
remain easily extensible.
A web interface for the database has been also designed and realized to display
the saved records. The users can visualize data in form of tables in general, but some
selected signals can be also represented in the form of charts.