Tezislər / Theses

THE 3
rd
 INTERNATIONAL SCIENTIFIC CONFERENCES OF STUDENTS AND YOUNG RESEARCHERS 
dedicated to the 99
th
anniversary of the National Leader of Azerbaijan Heydar Aliyev
263
the user and at the same time will save the energy by dimming the light to 
the required level for the specified activity.
Comparison with existing proposals 
We investigated several methods to solve the problems existing in 
other light control systems. [3, 6, 7]
“Hot-spots”: Different intensity values in various parts of the room must 
be considered. Mainly the areas near the windows are brighter than the 
remaining parts of the room. 
“Cross-talk”: This includes the interaction between the controllers and 
the lamps. A decrease in one of the several lamps must not affect the 
remaining lamps utilized to lighten different areas of the room.
We considered using fixed sensors that is more comfortable for the user 
than carrying it which is proposed by [4]. [2] stresses the demand for an 
efficient application for mobile control. With the help of Machine Learning we 
intend to code this mobile app. Moreover, this light control system and mobile 
application must be adjusted to be used by several users as members of a 
family can be busy with different actions at the same time. 
Additional factors to be considered include long durability and less 
number of sensors [1, 5, 6], application areas (residential, office, laboratory, 
etc.), various types of lamps. 
Methodology 
The number of sensors
is quite important factor, because it directly 
affects the cost and complexity of the system. 
1. The first case is when there are different external light sources. Here, the 
sensors should work during the whole process, because it is not possible 
to exactly predict which light source is going to be on or off at what time.
2. The second case is for the places where external light sources (The Sun 
or street lights) do not affect the interior space lighting, for example 
where there are thick curtains or no windows. In this situation we can 
predict illuminance in the room without using sensors. From the tabular 
data which illustrates the dependency of light source intensity and the 
lighting in the room, we can get the necessary information.
3. The third case is when the only external light source is the Sun. By 
knowing the sunrise and sunset times, after sunset the situation will be 
the same as the second case. That is why we can turn off the sensors 
and use only tabular data tables. 
4. The remaining one comes across mainly in the offices - having more 
than one workspace. In this scenario, the people in various workspaces 
can choose different activities, that is why their wanted light intensity will 
be different as well. Separate sensors and light sources have to be 
installed for each and every workspace. 

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