Esp32 S3 Cam Development Board With Ov3660 Camera - Esp32-s3-wroom N16r8 Module Wifi Bluetooth Microcontroller Mcu With Dual Type-c And Esp32-s3-core Compatible With Arduino Iot Communication

 

Product Introduction

Are you ready to build intelligent vision and voice-enabled projects in Pakistan? Whether you are a student in Lahore working on an AI-powered security system, a professional developer in Karachi creating an edge-computing device, or a hobbyist in Islamabad experimenting with robotics, the ESP32 S3 CAM Development Board with OV3660 Camera is your complete solution for advanced AI and IoT applications .

The ESP32 S3 CAM Development Board with OV3660 Camera combines a powerful dual-core ESP32-S3 processor with a high-resolution 3MP OV3660 camera sensor . This development board runs at up to 240 MHz and includes 8MB PSRAM and 16MB Flash, giving you the memory and processing power to handle demanding AI models and image processing tasks .

We understand Pakistani innovators need reliable, affordable components. The ESP32 S3 CAM Development Board with OV3660 Camera delivers exceptional value with integrated Wi-Fi and Bluetooth 5.0 LE connectivity, dual-microphone array with noise cancellation, speaker output, and a lithium battery charging circuit . You can access online AI platforms like Edge Impulse, YOLO, and OpenCV for object detection and image recognition .

The OV3660 camera on this board captures images at up to 2048×1536 resolution and features a wide field of view, making the ESP32 S3 CAM Development Board with OV3660 Camera perfect for surveillance, facial recognition, and smart home applications . When you order the ESP32 S3 CAM Development Board with OV3660 Camera, you receive a complete development platform ready for AI vision and voice interaction projects .

Don't let complex vision projects overwhelm you. The ESP32 S3 CAM Development Board with OV3660 Camera integrates all necessary components in a compact design, including a TF card slot for storage expansion . Join innovators across Pakistan choosing the ESP32 S3 CAM Development Board with OV3660 Camera to build next-generation AI solutions.

2️⃣ Key Features

• Process at High Speed: Run AI models at up to 240 MHz with the dual-core 32-bit LX7 processor .

• Capture Detailed Images: Take photos at resolutions up to 2048×1536 with the OV3660 camera .

• Connect Wirelessly: Use built-in 2.4GHz Wi-Fi and Bluetooth 5.0 LE for remote monitoring .

• Store Large Programs: Load complex AI models with 16MB Flash and 8MB PSRAM onboard .

• Recognize Speech Accurately: Use the dual-microphone array with noise cancellation for clear voice input .

• Output Audio Clearly: Connect an external speaker using the onboard 3W audio amplifier .

• Power Flexibly: Run via USB-C or connect a 3.7V lithium battery with onboard charging .

• Expand Storage Easily: Insert a TF card for logging images and data .

• Add a Display: Connect external SPI/QSPI displays using the FPC interface .

• Communicate with Peripherals: Use I2C, UART, and SPI interfaces for sensors and modules .

• Get Night Vision Capability: The infrared-sensitive OV3660 supports low-light and 24/7 monitoring .

• Program Conveniently: Use the USB-C port for power and code uploading .

• Customize Functionality: Use onboard BOOT and PWR buttons for custom controls .

• Access AI Platforms: Integrate with Edge Impulse, YOLOv5, and OpenAI for advanced AI .

• Save Development Time: Start with Arduino IDE or ESP-IDF for easy programming .

• See Status Clearly: Monitor power and user status using onboard LEDs .

• Support OTA Updates: Update firmware wirelessly over Wi-Fi .

• Use External Antenna: Switch to an external antenna for improved signal strength .

• Get Powerful AI Acceleration: Leverage vector instructions for accelerated AI/ML vision tasks .

• Build Professional Projects: Create products from smart cameras to AI assistants.

3️⃣ Advanced Features

• Edge AI Processing: Run on-device neural network inference for real-time object detection and classification without cloud dependency .

• AI Speech Interaction: Integrate with online large models like ChatGPT, Doubao, and DeepSeek for conversational AI .

• MJPEG Video Streaming: Stream real-time video over Wi-Fi with MJPEG encoding for web-based viewing .

• Multi-Object Detection: Use Edge Impulse demos for real-time and simultaneous detection of multiple objects .

• DVP Camera Interface: Connect to standard 24-pin DVP camera sensors, compatible with OV3660 and other models .

• SPI/QSPI Display Support: Attach LCD displays for HMI applications and visual feedback .

• Echo Cancellation: Process dual microphone audio with echo cancellation for clear voice interaction .

• Low-Power Operation: Optimized for battery-powered projects with efficient power management .

• High-Quality Audio Codec: Include ES8311 audio codec and ES7210 ADC for professional sound processing .

• USB On-The-Go: Connect USB peripherals via the Type-C OTG port for expanded functionality .

• Infrared Night Vision: Enable 24/7 monitoring with 940nm infrared illumination support .

• Wide-Angle Imaging: Capture large scenes with 160° field of view .

• Real-Time Image Filters: Apply edge detection, pixelation, color palettes, and CRT effects in real-time .

• CH32V003 Co-Processor: Use the expansion I/O chip for additional control functions .

• PSRAM Buffering: Utilize 8MB PSRAM for efficient image buffering and processing .

• Software-Reconfigurable GPIO: Access and configure multiple GPIO pins for custom applications .

• Dual Type-C Ports: Use one port for debugging and another for USB host functions .

• Powered USB Hub Support: Connect powered hubs for even more expansion options.

• Secure Boot: Use secure boot features for production-ready applications .

• Bluetooth Mesh: Build mesh networks for large-scale IoT deployments .

4️⃣ Frequently Asked Questions (FAQs)

Q1: What is the ESP32 S3 CAM Development Board with OV3660 Camera?
Answer: It is a compact AI development board combining an ESP32-S3 dual-core processor with an OV3660 3MP camera, dual microphones, speaker output, Wi-Fi, and Bluetooth for vision and voice projects .

Q2: What camera does this board include?
Answer: The board includes the OV3660 camera sensor with 3MP (2048×1536) resolution and infrared sensitivity for night vision applications .

Q3: Can I use this board for face recognition?
Answer: Yes, the ESP32-S3 includes vector instructions for AI acceleration, making it suitable for face detection, object tracking, and image classification .

Q4: How do I program the board?
Answer: You can program the board using the Arduino IDE, ESP-IDF framework, or MicroPython .

Q5: What AI platforms does this board support?
Answer: It supports Edge Impulse, YOLOv5, OpenCV, and online large model platforms like ChatGPT, Doubao, and DeepSeek .

Q6: Does the board include a battery charging circuit?
Answer: Yes, the board includes a lithium battery charging circuit that supports connecting a 3.7V Li-Battery for portable projects .

Q7: Where can I buy this board in Pakistan?
Answer: The ESP32 S3 CAM Development Board with OV3660 Camera is available across Pakistan through major electronics retailers in Lahore, Karachi, Islamabad, and other cities .

Q8: What resolution can the camera achieve?
Answer: The OV3660 camera can capture images at up to 2048×1536 resolution. For video streaming, it supports WVGA and similar resolutions .

Q9: Can I add an external display?
Answer: Yes, the board has an 18-pin SPI/QSPI display interface for connecting external LCD screens .

Q10: Does the board support OTA updates?
Answer: Yes, you can perform Over-The-Air firmware updates via Wi-Fi .

5️⃣ Where It Can Be Used

1. Smart Surveillance: Build 24/7 security cameras with motion detection and infrared night vision .

2. AI Assistant Devices: Create voice-controlled assistants with ChatGPT integration for smart home automation .

3. Facial Recognition Systems: Implement on-device face detection and identification for access control .

4. Edge Vision Applications: Process visual data locally for industrial inspection and quality control .

5. IoT Security Systems: Develop smart doorbells, electronic peepholes, and baby monitors .

6. Robotics Projects: Build robots with computer vision capabilities for navigation and object detection.

7. License Plate Recognition: Deploy automated license plate reading systems at entry points .

8. Agricultural Monitoring: Capture field images for crop health assessment and automated irrigation.

9. Smart Retail: Implement customer counting, shelf monitoring, and theft detection systems.

10. Educational Prototyping: Teach AI and computer vision concepts in universities and workshops across Pakistan.

6️⃣ How to Use

Getting started with the ESP32 S3 CAM Development Board is straightforward. First, download and install the Arduino IDE or ESP-IDF on your computer. Connect the board to your computer using a USB Type-C cable .

Open the Arduino IDE and navigate to Tools > Board > Board Manager. Install the ESP32 board package by searching for "ESP32" and selecting the latest version from Espressif Systems. Select your board as "ESP32S3 Dev Module" from the Tools menu and choose the correct COM port .

To test your camera, load an example sketch from the ESP32 library. Go to File > Examples > ESP32 > Camera and select the CameraWebServer example. This sketch turns your board into a web server that streams live video. Enter your WiFi credentials and upload the sketch .

For safety, handle the board with care and avoid static discharge. When connecting external components, power off the board first. Use the battery header carefully for portable applications .

For maintenance, store the board in a cool, dry place. Clean the camera lens gently with a microfiber cloth. Keep the board's firmware updated for optimal performance.

Example Code

////////////////////////////////////////////////

#include "esp_camera.h"
#include <WiFi.h>
#include "esp_http_server.h"

// Replace with your network credentials
const char* ssid = "Digilog";// Router ssid name or wifi name of your home/office
const char* password = "DIGILOGPK";// password of your home/office wifi

// GOOUUU ESP32-S3 CAM N16R8 pin configuration
#define PWDN_GPIO_NUM     -1
#define RESET_GPIO_NUM    -1
#define XCLK_GPIO_NUM     15
#define SIOD_GPIO_NUM     4
#define SIOC_GPIO_NUM     5
#define Y9_GPIO_NUM       16
#define Y8_GPIO_NUM       17
#define Y7_GPIO_NUM       18
#define Y6_GPIO_NUM       12
#define Y5_GPIO_NUM       10
#define Y4_GPIO_NUM       8
#define Y3_GPIO_NUM       9
#define Y2_GPIO_NUM       11
#define VSYNC_GPIO_NUM    6
#define HREF_GPIO_NUM     7
#define PCLK_GPIO_NUM     13

#define LED_GPIO_NUM      21

httpd_handle_t camera_httpd = NULL;

// Control variables
int jpeg_quality = 12;
int frame_delay = 30;
framesize_t frame_size = FRAMESIZE_VGA;

static esp_err_t capture_handler(httpd_req_t *req) {
    camera_fb_t * fb = NULL;
    
    digitalWrite(LED_GPIO_NUM, HIGH);
    
    fb = esp_camera_fb_get();
    if (!fb) {
        digitalWrite(LED_GPIO_NUM, LOW);
        httpd_resp_send_500(req);
        return ESP_FAIL;
    }
    
    httpd_resp_set_type(req, "image/jpeg");
    httpd_resp_send(req, (const char *)fb->buf, fb->len);
    
    esp_camera_fb_return(fb);
    digitalWrite(LED_GPIO_NUM, LOW);
    
    return ESP_OK;
}

static esp_err_t stream_handler(httpd_req_t *req) {
    camera_fb_t * fb = NULL;
    esp_err_t res = ESP_OK;
    char part_buf[64];
    
    httpd_resp_set_type(req, "multipart/x-mixed-replace;boundary=frame");
    
    while(true) {
        fb = esp_camera_fb_get();
        if (!fb) {
            Serial.println("Camera capture failed");
            res = ESP_FAIL;
            break;
        }
        
        size_t hlen = snprintf(part_buf, 64, "Content-Type: image/jpeg\r\nContent-Length: %u\r\n\r\n", fb->len);
        
        res = httpd_resp_send_chunk(req, "--frame\r\n", 8);
        res = httpd_resp_send_chunk(req, part_buf, hlen);
        res = httpd_resp_send_chunk(req, (const char *)fb->buf, fb->len);
        res = httpd_resp_send_chunk(req, "\r\n", 2);
        esp_camera_fb_return(fb);
        
        if (res != ESP_OK) break;
        
        vTaskDelay(frame_delay / portTICK_PERIOD_MS);
    }
    return res;
}

static esp_err_t index_handler(httpd_req_t *req) {
    const char* html = R"rawliteral(
<!DOCTYPE html>
<html>
<head><title>ESP32-CAM Control</title>
<style>
body{font-family:Arial;margin:20px;}
.controls{margin:20px 0;padding:10px;border:1px solid #ccc;}
button{padding:8px 15px;margin:5px;background:#007bff;color:white;border:none;cursor:pointer;}
button:hover{background:#0056b3;}
#stream{max-width:100%;border:1px solid #333;}
</style>
</head>
<body>
<h1>ESP32-CAM Live Stream</h1>
<div class="controls">
<h3>Quality Control</h3>
<button onclick="setQuality(5)">High Quality</button>
<button onclick="setQuality(12)">Medium Quality</button>
<button onclick="setQuality(20)">Low Quality</button>
</div>
<div class="controls">
<h3>Speed Control</h3>
<button onclick="setSpeed(10)">Fast (10ms)</button>
<button onclick="setSpeed(30)">Normal (30ms)</button>
<button onclick="setSpeed(50)">Slow (50ms)</button>
</div>
<div class="controls">
<h3>Resolution</h3>
<button onclick="setResolution(6)">VGA (640x480)</button>
<button onclick="setResolution(5)">QVGA (320x240)</button>
<button onclick="setResolution(8)">SVGA (800x600)</button>
</div>
<img id="stream" src="/stream">
<script>
function setQuality(q) {
  fetch('/control?quality=' + q);
}
function setSpeed(s) {
  fetch('/control?speed=' + s);
}
function setResolution(r) {
  fetch('/control?resolution=' + r).then(() => {
    document.getElementById('stream').src = '/stream?' + Date.now();
  });
}
</script>
</body>
</html>
)rawliteral";
    
    httpd_resp_set_type(req, "text/html");
    httpd_resp_send(req, html, strlen(html));
    return ESP_OK;
}

static esp_err_t control_handler(httpd_req_t *req) {
    char query[200];
    if (httpd_req_get_url_query_str(req, query, sizeof(query)) == ESP_OK) {
        char param[32];
        
        if (httpd_query_key_value(query, "quality", param, sizeof(param)) == ESP_OK) {
            jpeg_quality = atoi(param);
            sensor_t * s = esp_camera_sensor_get();
            s->set_quality(s, jpeg_quality);
        }
        
        if (httpd_query_key_value(query, "speed", param, sizeof(param)) == ESP_OK) {
            frame_delay = atoi(param);
        }
        
        if (httpd_query_key_value(query, "resolution", param, sizeof(param)) == ESP_OK) {
            framesize_t new_size = (framesize_t)atoi(param);
            sensor_t * s = esp_camera_sensor_get();
            s->set_framesize(s, new_size);
        }
    }
    
    httpd_resp_send(req, "OK", 2);
    return ESP_OK;
}

void setup() {
    Serial.begin(115200);
    
    pinMode(LED_GPIO_NUM, OUTPUT);
    digitalWrite(LED_GPIO_NUM, LOW);
    
    camera_config_t config;
    config.ledc_channel = LEDC_CHANNEL_0;
    config.ledc_timer = LEDC_TIMER_0;
    config.pin_d0 = Y2_GPIO_NUM;
    config.pin_d1 = Y3_GPIO_NUM;
    config.pin_d2 = Y4_GPIO_NUM;
    config.pin_d3 = Y5_GPIO_NUM;
    config.pin_d4 = Y6_GPIO_NUM;
    config.pin_d5 = Y7_GPIO_NUM;
    config.pin_d6 = Y8_GPIO_NUM;
    config.pin_d7 = Y9_GPIO_NUM;
    config.pin_xclk = XCLK_GPIO_NUM;
    config.pin_pclk = PCLK_GPIO_NUM;
    config.pin_vsync = VSYNC_GPIO_NUM;
    config.pin_href = HREF_GPIO_NUM;
    config.pin_sscb_sda = SIOD_GPIO_NUM;
    config.pin_sscb_scl = SIOC_GPIO_NUM;
    config.pin_pwdn = PWDN_GPIO_NUM;
    config.pin_reset = RESET_GPIO_NUM;
    config.xclk_freq_hz = 20000000;
    config.pixel_format = PIXFORMAT_JPEG;
    config.frame_size = frame_size;
    config.jpeg_quality = jpeg_quality;
    config.fb_count = 1;
    
    esp_err_t err = esp_camera_init(&config);
    if (err != ESP_OK) {
        Serial.printf("Camera init failed with error 0x%x", err);
        return;
    }
    
    WiFi.begin(ssid, password);
    while (WiFi.status() != WL_CONNECTED) {
        delay(1000);
        Serial.println("Connecting to WiFi...");
    }
    Serial.println("WiFi connected");
    Serial.print("Camera Ready! Use 'http://");
    Serial.print(WiFi.localIP());
    Serial.println("' to connect");
    
    httpd_config_t config_httpd = HTTPD_DEFAULT_CONFIG();
    
    httpd_uri_t index_uri = {.uri = "/", .method = HTTP_GET, .handler = index_handler, .user_ctx = NULL};
    httpd_uri_t capture_uri = {.uri = "/capture", .method = HTTP_GET, .handler = capture_handler, .user_ctx = NULL};
    httpd_uri_t stream_uri = {.uri = "/stream", .method = HTTP_GET, .handler = stream_handler, .user_ctx = NULL};
    httpd_uri_t control_uri = {.uri = "/control", .method = HTTP_GET, .handler = control_handler, .user_ctx = NULL};
    
    httpd_start(&camera_httpd, &config_httpd);
    httpd_register_uri_handler(camera_httpd, &index_uri);
    httpd_register_uri_handler(camera_httpd, &capture_uri);
    httpd_register_uri_handler(camera_httpd, &stream_uri);
    httpd_register_uri_handler(camera_httpd, &control_uri);
}

void loop() {
    delay(1000);
}

//============================

This module offers low power consumption and real-time processing, making it ideal for edge AI and computer vision tasks. Perfect for DIY makers, educators, and professionals working on camera-enabled IoT systems.

7️⃣ Advantages

• Complete Integration: Combines camera, microphones, audio amplifier, Wi-Fi, and Bluetooth in one board .

• AI Processing Power: Dual-core processor with vector instructions accelerates AI and vision tasks .

• Excellent Memory Capacity: 16MB Flash and 8MB PSRAM support large AI models .

• Versatile Connectivity: Wi-Fi, Bluetooth, USB-C, I2C, UART, and SPI interfaces .

• Professional Audio: Dual-microphone array with noise cancellation and audio amplifier .

• Portable Power Support: Battery charging circuit enables portable, battery-powered projects .

• Night Vision Ready: Infrared-sensitive camera supports 24/7 surveillance .

• Wide Software Support: Compatible with Arduino, ESP-IDF, MicroPython, and AI platforms .

• Expandable Storage: TF card slot for image and data logging .

• Cost-Effective: Offers professional AI features at an affordable price for the Pakistani market.

8️⃣ Disadvantages

• Power Consumption: High-performance AI processing consumes more battery than simpler boards.

• Camera Resolution Limitations: The OV3660 sensor, while capable of high resolution, may have limitations in low-light conditions .

• Complex Setup: Advanced features require familiarity with the ESP-IDF framework.

• Limited Library Support: Some Arduino libraries may not fully support all board features.

• Antenna Limitations: The onboard ceramic antenna may have limited range in congested environments.

• Requires External Speaker: The speaker is often sold separately .

• Display Not Included: External display is optional and requires separate purchase .

• Surface-Mount Components: Repairing the board requires specialized equipment.

• Learning Curve: AI implementation requires machine learning knowledge.

• Potential Overheating: High-performance operations can cause the board to heat up.

9️⃣ City-Wise Sales Coverage in Punjab

We deliver the ESP32 S3 CAM Development Board with OV3660 Camera across all of Punjab, ensuring students, professionals, and businesses have access to this powerful AI vision platform. Our complete coverage includes major cities like Lahore, Faisalabad, Rawalpindi, Multan, and Gujranwala. We also serve Sialkot, Bahawalpur, Sargodha, Rahim Yar Khan, Sheikhupura, Jhang, Dera Ghazi Khan, Gujrat, Okara, Kasur, Sahiwal, Khanewal, Chiniot, Pakpattan, and Vehari. No matter where you are in the province, your next AI vision project is just an order away.

ESP32 S3 CAM with OV3660 Camera - AI Vision Board Pakistan
Buy ESP32 S3 CAM Development Board with OV3660 Camera in Pakistan. AI-enabled with 3MP camera, dual mic, Wi-Fi & Bluetooth. Perfect for edge AI & IoT projects.
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