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Figure 7. Detecting car speed and visualizing it through ThinkSpeak.

Figure 7 Detecting car speed and visualizing it through ThinkSpeak.

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Figure 1. The proposed system's architecture. extra LDR sensor with each light bar to ensure that the lights operate correctly. If the lights aren't functioning correctly, send the data to a central database through an Esp8266 NodeMCU so that responsible personnel car respond fast. Once a week, we clean the street light poles using a servo motor. For a given distance, we employ two IR sensors to determine the speed of the cars. Each bar has an MQ135 sensor that collects data on the ait quality surrounding the poles and sends it to ThingSpeak, where we can view the processed data graphically. The Arduino Uno is employed as a processing unit in our system. This section discusses the components that comprise the overall system. Figure 1 shows the proposed system architecture and figure 2 illustrates the various hardware components used in the system.
Figure 1. The proposed system's architecture. extra LDR sensor with each light bar to ensure that the lights operate correctly. If the lights aren't functioning correctly, send the data to a central database through an Esp8266 NodeMCU so that responsible personnel car respond fast. Once a week, we clean the street light poles using a servo motor. For a given distance, we employ two IR sensors to determine the speed of the cars. Each bar has an MQ135 sensor that collects data on the ait quality surrounding the poles and sends it to ThingSpeak, where we can view the processed data graphically. The Arduino Uno is employed as a processing unit in our system. This section discusses the components that comprise the overall system. Figure 1 shows the proposed system architecture and figure 2 illustrates the various hardware components used in the system.
Figure 2. List of Components (a) Arduino Uno (b) NodeMCU (¢) Ultrasonic Sensor (d) Servo Motor (e) LDR (f) MQ-135 Sensor (g) IR Sensor. IR sensor: The infrared sensor monitors and detects infrared radiation in the surroundings. It detects movemen within a specific range (Wikipedia., 2005). To measure vehicle speed, we employ two infrared sensors in out system. When cats pass over the two infrared sensors, we divide the constant distance by the time to pass through these infrared sensors. Software requitements
Figure 2. List of Components (a) Arduino Uno (b) NodeMCU (¢) Ultrasonic Sensor (d) Servo Motor (e) LDR (f) MQ-135 Sensor (g) IR Sensor. IR sensor: The infrared sensor monitors and detects infrared radiation in the surroundings. It detects movemen within a specific range (Wikipedia., 2005). To measure vehicle speed, we employ two infrared sensors in out system. When cats pass over the two infrared sensors, we divide the constant distance by the time to pass through these infrared sensors. Software requitements
Figure 3. The proposed system's flowchart. The suggested system automatically runs and maintains the streetlights with little human intervention. First, an ultrasonic sensor was put to detect the items and their distance from the sensor.
Figure 3. The proposed system's flowchart. The suggested system automatically runs and maintains the streetlights with little human intervention. First, an ultrasonic sensor was put to detect the items and their distance from the sensor.
Figure 4. Connecting solar panel with Arduino Uno. Uses of Solar Energy: We proposed to use a solar panel to collect solar energy during the day. A battery is usec to store the solar energy to power up the whole system at a time when needed. The system will be able to get full power from solar energy.
Figure 4. Connecting solar panel with Arduino Uno. Uses of Solar Energy: We proposed to use a solar panel to collect solar energy during the day. A battery is usec to store the solar energy to power up the whole system at a time when needed. The system will be able to get full power from solar energy.
Saha, S. et al. (2022). Self-Power Driven IOT-Based Smart Street Lighting System (SSLS). Khulna University Studies, Special Issue ICSTEMA4IR): 120-132. Figure 5. Light’s brightness is (a) 0 (turn off) on the day (b) 50 when the object’s distance is 50 units away at night (c) 100 when the object’s distance is 35 units away at night (d) 180 when the object’s distance is 25 units away at night (e) 255 when the object’s distance is 15 units away at night (f) when the object’s distance is far away at night.
Saha, S. et al. (2022). Self-Power Driven IOT-Based Smart Street Lighting System (SSLS). Khulna University Studies, Special Issue ICSTEMA4IR): 120-132. Figure 5. Light’s brightness is (a) 0 (turn off) on the day (b) 50 when the object’s distance is 50 units away at night (c) 100 when the object’s distance is 35 units away at night (d) 180 when the object’s distance is 25 units away at night (e) 255 when the object’s distance is 15 units away at night (f) when the object’s distance is far away at night.
Table 1. Status of the street light
Table 1. Status of the street light
Figure 6. Air quality monitoring using ThinkgSpeak. Saha, S. et al. (2022). Self-Power Driven IOT-Based Smart Street Lighting System (SSLS). Khulna University Studies, Special Issue (ICSTEM4IR) 120-132.
Figure 6. Air quality monitoring using ThinkgSpeak. Saha, S. et al. (2022). Self-Power Driven IOT-Based Smart Street Lighting System (SSLS). Khulna University Studies, Special Issue (ICSTEM4IR) 120-132.
Table 2. Comparative Analysis with other existing works
Table 2. Comparative Analysis with other existing works
Figure 8. Servo motor connected to the system
Figure 8. Servo motor connected to the system
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Computer ScienceAutomotive EngineeringSmart Lighting
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