Project Hub /Artificial Intelligence & Edge ML/Object Detection & Tracking/How to Build a Parking Space Detection System Using ESP32-CAM with CircuitDigest Cloud

Intermediate

ESP32

Project Specific

3 – 6 Hours

Complete Kit

How to Build a Parking Space Detection System Using ESP32-CAM with CircuitDigest Cloud

Build a smart parking space detection system using an ESP32-CAM to capture images and send them to the CircuitDigest Cloud API for real-time occupancy analysis.

Originally published on CircuitDigest

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

ESP32 CAM WiFi Module Bluetooth with OV2640 Camera Rs. 1,483.00
ESP32 WiFi+Bluetooth CP2102 Development Board Rs. 520.00
Ultrasonic Sensor Module HC-SR04 Rs. 89.00
TowerPro SG90 Mini Servo – 180 degree Rotation – Standard Quality Rs. 179.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
USB to UART/ESP8266 Adapter Programmer for ESP-01 WiFi Modules with CH340G Chip Rs. 99.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

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How It Works

The Parking Space Detection System operates by combining proximity sensing, microcontroller processing, and cloud connectivity to monitor vehicle presence in real time. At the core of the system are the ESP32-CAM and an ESP32 microcontroller working alongside an HC-SR04 ultrasonic sensor and a micro servo motor. The HC-SR04 sensor continuously emits high-frequency sound waves and measures the echo return time to calculate the distance to an object, such as a parked vehicle. Concurrently, the ESP32-CAM can capture visual data of the parking spot. When a change in distance or occupancy is detected, the ESP32 processes this local sensor data and connects to the internet via Wi-Fi to transmit information to the CircuitDigest Cloud API. Based on the cloud analysis or direct sensor triggers, the system can command the micro servo motor to actuate—for instance, simulating a barrier gate opening or closing. Power is distributed across two breadboards using connecting wires to neatly organize the low-voltage DC connections between the sensors, motors, and the ESP32 boards. If using an ESP32-CAM without an onboard USB port, a USB-to-Serial FTDI adapter is utilized to program the microcontroller via the Arduino IDE using the ESP32 Board Support Package.

Why Build This

Develop practical undergraduate-level experience integrating microcontroller hardware with cloud-based IoT APIs for real-time data analysis.

Gain hands-on engineering skills in combining distance sensors and actuators to prototype automated physical systems like smart parking lots.

Learn to manage multi-board microcontroller setups, including bridging serial programming interfaces and handling power distribution on breadboards.

Real-World Application

Smart parking lots, automated garage gate controls, commercial parking management, and real-time urban traffic monitoring.

Skills You'll Learn

Microcontroller programming

Ultrasonic distance measurement

Servo motor actuation

Cloud API integration

Wi-Fi networking with ESP32

Serial communication via FTDI

Safety Precautions

No specific precautions noted for this build — always follow general electronics safety practices.

Technology Tags

ESP32-CAM

CLOUD API

COMPUTER VISION

IOT

WI-FI

ULTRASONIC SENSOR

SERVO MOTOR

HTTPS POST

ARDUINO IDE

Frequently Asked Questions

Why is a USB-to-Serial FTDI adapter needed?

Many ESP32-CAM modules lack an integrated USB port for programming, so an external FTDI adapter is required to connect the board to your computer's USB port for code uploading.

How does the HC-SR04 ultrasonic sensor detect a vehicle?

The sensor sends out an ultrasonic sound pulse and measures how long it takes to bounce off a nearby vehicle and return, allowing the system to calculate distance and infer occupancy.

What is the role of the CircuitDigest Cloud API?

The cloud API receives data and images transmitted over the internet by the ESP32 system, enabling remote monitoring and real-time occupancy analysis of the parking space.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

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