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
264
Model 
 
The diagram above shows the workflow of the system.
1. 
Application.
Applications can be in different forms - mobile app, web 
page or simple Arduino controlled buttons.
2. 
Database
and 
ML model. 
When the user makes his or her decision of 
activity, the data is sent to not only the MCU, but also to the Database. 
Data contains three columns - the time of the day, the day of the week 
and selected activity. After having the sufficient amount of data in the 
database, the collected data will be sent to the ML model. The model is 
a recommendation system and it will predict the user activity based on the 
time of the day and day of the week. The result of the recommendation 
system is presented to the user and he or she can select it. 
3. 
MCU, sensor, light source
. Microcontroller (MCU) is the brain of the 
process. It takes two inputs and returns one output. The first input is the 
selected activity of the user and the second input is the output of the light 
sensor. MCU compares the value of the sensor and the light intensity 
equivalent of the selected activity. The difference between the mentioned 
values is sent to the light source and the light source provides that 
needed light sensitivity. 
Conclusion 
To sum up, the thesis addressed the light controlling problem. It helps 
to reduce energy consumption and improve user comfort which are today’s 
major focus globally.
References 
[1]
Bai, Y.W.; Ku, Y.T. Automatic room light intensity detection and control using a 
microprocessor and light sensors. 
[2]
Control of light Intensity via Microcontroller for the Efficiency of Electrical Energy 
[3] O’Reilly, F.; Buckley, J. Use of Wireless Sensor Networks for Fluorescent Lighting Control 
with Daylight Substitution 
[4]
Pan, M.S.; Yeh, L.W.; Chen, Y.A.; Lin, Y.H.; Tseng, Y.C. A wsn-based intelligent light 
control system considering user activities and profiles. 
[5] Park, H.; Srivastava, M.B.; Burke, J. Design and Implementation of a Wireless Sensor 
Network for Intelligent Light Control. 
[6]
Wen, Y.J.; Granderson, J.; Agogino, A.M. Towards Embedded Wireless-Networked 
Intelligent Daylighting Systems for Commercial Buildings. 

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