Reducing energy consumption in home automation based on stm32F407 microcontroller



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Reducing energy consumption in home automation based on STM32F407 microcontroller
nanomaterials-09-00813
Component
Price
Mikromedia 7 Board
225 Euros Temperature sensor
4 Euros Light dependent resistor
2 Euros Smoke sensor
7 Euros Solid state relay
12 Euros Auxiliary materials
25 Euros Fig. 2. Software implementation flow Authorized licensed use limited to Univ of Texas at Dallas. Downloaded on September 10,2022 at 01:29:13 UTC from IEEE Xplore. Restrictions apply.

The results obtained by implementing this solution are presented in Fig. 3. In 2015 the house was equipped with a heating control system by using a thermostat in each room and a Programmable Logic Controller (PLC). Due to this, the energy consumption was reduced by approximately
10% compared to 2014. In January 2016 the control system described in this paper was mounted in the experimental house. After monitoring energy consumption in the first eight months of this year we found a further reduction in consumption by approximately 15% (line 2016 in Fig. 3). As it can be seen on the graphic representation, the energy consumption also continued the reduction from month 5 onwards, even if during these several months the heating system was turned off. This demonstrates the utility of the lighting subsystem. The light will automatically turnoff in those areas where no movement is detected in time interval of 5 minutes.
V.
C
ONCLUSION AND FUTURE
W
ORK
This paper is presenting a low-cost solution based on
STM32F407 microcontroller, to the problem of energy consumption in home automation. The experimental setup was a newly built house from a four season geographic area. The obtained results show that such a solution as the one presented in this paper can bring a decrease of 15% in the energy consumption. As future work, we plan to connect the system to the internet and create a method of directly interacting with the solution by means of mobile applications. The sensor data will be saved on the cloud and based on different analysis on the data, certain actions will take place.
A
CKNOWLEDGMENT
This paper was partially funded under the Continental Automotive AG project
AC_G_xBU_Academy,
5718/01.03.2012, Additional act 22.
R
EFERENCES
[1]
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