availability to drivers through the Blynk IoT platform in real time. The system was designed, simulated, and

tested using integrated hardware and software components, with results showing reliable detection and

efficient data transmission to the user interface. The project demonstrates a scalable, cost-effective solution

suitable for commercial and residential applications.

The exponential rise in private vehicle ownership in urban areas has created critical challenges in parking

management and traffic control. Insufficient parking spaces, coupled with limited visibility of available slots,

lead to time wastage, fuel consumption, and carbon emissions. The concept of smart parking systems

integrates sensors and IoT connectivity to provide real-time monitoring of parking availability, thereby

Recent studies emphasize the integration of low-cost microcontrollers such as Arduino Uno and NodeMCU

ESP8266 for real-time monitoring due to their flexibility and compatibility with IoT platforms [6]. Infrared

and ultrasonic sensors are commonly used for vehicle detection owing to their accuracy and affordability [7].

The Blynk application offers a practical interface for visualizing IoT data, allowing remote monitoring and

control [8]. However, many existing systems suffer from high power consumption, poor scalability, or limited

communication range.

This study focuses on developing an IoT-enabled car parking monitoring system capable of detecting and

displaying parking availability via a mobile application. The objectives of this research are: (1) to design and

implement an IoT-based car parking system using Arduino and NodeMCU; and (2) to monitor available

parking spaces in real time through the Blynk application. The project aims to enhance user convenience,

Each parking slot is equipped with an IR sensor module comprising a transmitter and receiver pair. The

Arduino Uno interprets the signals and communicates with NodeMCU. The system is programmed using the

Arduino IDE with separate codes for Arduino and NodeMCU, which handle sensor logic and data

transmission, respectively. The Blynk application displays slot availability using LED widgets labeled Slot 1–

Slot 6. The flowchart of the project is depicted in Figure 1.

The system successfully detected vehicle presence using IR sensors and transmitted real-time data to the Blynk

app with minimal delay. Testing showed 100% detection accuracy under controlled conditions and 95% under

ambient light. The Wi-Fi connection remained stable within a 10-meter range. The total hardware cost was

Two sets of codes were developed: one for the Arduino Uno and another for the NodeMCU ESP8266 Wi-Fi

module. The Arduino Uno program manages the parking detection system using IR sensors, while the

NodeMCU ESP8266 functions as the IoT communication platform. The Blynk application enables real-time

monitoring of the parking system via Wi-Fi connectivity.

3(a)

3(b)

Fig. 3 (a) and (b) The prototype of the system

Fig. 5 (a) and (b) The Blynk application output indicates activation of the LED for Parking Slot 1 after the

system is executed.

By reducing search time for parking, the system helps lower fuel consumption and CO₂ emissions, aligning

with Sustainable Development Goal 11. Limitations include dependence on Wi-Fi stability and sensor

performance under strong sunlight. Future work may incorporate ultrasonic sensors and LoRa communication

for enhanced range and precision.

Engineering Research & Technology (IJERT), vol.9, no. 6, pp. 1–5,

monitoring. IEEE Sensors Journal, vol. 10, no. 10, pp.1666–1671,

Comput. Eng. Technol., vol. 1, no. 2, pp. 91–95.

Ethernet. Procedia Computer Science, vol.47, pp.133–141.

SDG Knowledge Platform.