TY - GEN
T1 - Smart and green street lighting system based on arduino and RF wireless module
AU - Jabbar, Waheb A.
AU - Yuzaidi, Muhamad Aznawi Bin
AU - Yan, Kong Qi
AU - Bustaman, Ummu Sakinah Binti Mohd
AU - Hashim, Yasir
AU - Alariqi, Hani Taha
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Street lights consume a huge amount of electric energy due to their conventional control systems that automatically turn ON and OFF either using timers or light dependent resistor (LDR). In addition, such systems use a high power pulps, which is not a good option for energy saving, thus it causes a huge waste of energy in the whole world. Green and Smart Street Lighting System, is necessity to overcome such issues, especially with the emergence of Smart City. Therefore, this project aims to design a smart and green street lighting system (SGStreet-LS) for saving energy and utilizing renewable energy sources efficiently. The proposed system composes powerful ideas and concept to smoothly and efficiently control the operation of street lightings based on the sunlight availability and the motion detection by exploiting Arduino-based controllers with RF wireless communication support. It also utilizes low power LEDs that supplied from solar panels to replace the conventional high power lights. Also a part of this project is to study the relationship of energy and environment based on the emission of CO2level in the experiment, and validate the compatibility of real implementation of SGStreet-LS. In order to switching lights ON, there are to conditions to be satisfied: LDR sensor detects lower level of lights intensity (darkness situations), and PIR motion sensor detects the presence of an object in the street (vehicle/human). Otherwise, the street's lights will be switched OFF. As a result, by implementing SGStreet-LS, the electricity consumption for the street's lights can be reduced in addition to lowering CO2level by using renewable energy sources. The lights turn on before pedestrians and vehicles come and turn off or reduce brightness when there is no one.
AB - Street lights consume a huge amount of electric energy due to their conventional control systems that automatically turn ON and OFF either using timers or light dependent resistor (LDR). In addition, such systems use a high power pulps, which is not a good option for energy saving, thus it causes a huge waste of energy in the whole world. Green and Smart Street Lighting System, is necessity to overcome such issues, especially with the emergence of Smart City. Therefore, this project aims to design a smart and green street lighting system (SGStreet-LS) for saving energy and utilizing renewable energy sources efficiently. The proposed system composes powerful ideas and concept to smoothly and efficiently control the operation of street lightings based on the sunlight availability and the motion detection by exploiting Arduino-based controllers with RF wireless communication support. It also utilizes low power LEDs that supplied from solar panels to replace the conventional high power lights. Also a part of this project is to study the relationship of energy and environment based on the emission of CO2level in the experiment, and validate the compatibility of real implementation of SGStreet-LS. In order to switching lights ON, there are to conditions to be satisfied: LDR sensor detects lower level of lights intensity (darkness situations), and PIR motion sensor detects the presence of an object in the street (vehicle/human). Otherwise, the street's lights will be switched OFF. As a result, by implementing SGStreet-LS, the electricity consumption for the street's lights can be reduced in addition to lowering CO2level by using renewable energy sources. The lights turn on before pedestrians and vehicles come and turn off or reduce brightness when there is no one.
KW - Arduino
KW - Green Technology
KW - LDR
KW - PIR
KW - Street Light
UR - http://www.scopus.com/inward/record.url?scp=85074987055&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074987055&partnerID=8YFLogxK
U2 - 10.1109/ICMSAO.2019.8880451
DO - 10.1109/ICMSAO.2019.8880451
M3 - Conference contribution
SN - 9781538676844
T3 - 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019
BT - 2019 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019
Y2 - 15 April 2019 through 17 April 2019
ER -