Light Intensity Monitor with DFRobot ESP32-S3 AI

Want to monitor ambient light levels in your home, lab, or greenhouse — and get readings with a simple Telegram message? In this tutorial, I’ll show you how to build your own IoT light bot using the powerful DFRobot ESP32-S3 AI Camera and the DFRobot LTR-308 ambient light sensor, all connected through Telegram.

This project lets you ask your ESP32 “How bright is it right now?” and get real-time readings straight to your phone. It’s simple, elegant, and scalable — let’s dive in!

What You'll Need

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Why the ESP32-S3 AI CAM?

The DFRobot ESP32-S3 AI Camera board is tailor-made for smart sensing projects. Here's why it's ideal for this build:

• ESP32-S3 chip with 2.4GHz Wi-Fi and Bluetooth Low Energy
• 8MB PSRAM and 16MB Flash for smooth video and data processin
• Onboard OV2640 camera and audio support (I2S mic/speaker)
• USB-C for fast flashing and serial monitoring
• Multiple GPIOs for sensor connection (I2C, SPI, UART, PWM…)

Wiring the Light Sensor

The LTR-308 is an I2C ambient light sensor that offers wide-range, high-accuracy lux readings. It uses two I2C pins and runs at 3.3V — perfect for the ESP32.

Luckily this LTR-308 is already connected on the board itself. So, we can dierectly use the sensor.

Connection guide:

Setting Up the Telegram Bot

• Open Telegram and search for @BotFather.

• Send /newbot and follow the prompts:Name: LightWatcherBot
Username: lightwatcher_xyz_bot
• Copy the API token — you’ll use this in your code.
• Start a chat with your new bot and send a message (like /start) to initialize it.
• Note down your chat_id.

Arduino Libraries You'll Need

Install these libraries via the Arduino Library Manager:

• UniversalTelegramBot by Brian Lough
• WiFiClientSecure
• DFRobot_LTR308 (available from DFRobot’s GitHub)

Arduino Code

Here’s the core logic:

When the ESP32 boots, it connects to Wi-Fi and sends a message: "Bot is now online! IP: xxx.xxx.xxx.xxx\nCan I show the readings?"

When the user responds with “yes”, “ok”, or /light, the board reads light intensity from the LTR-308 and replies with:

📟 Simulated Light Sensor Readings:
• Raw value: 1024
• Lux: 256.00 lx
📟 Simulated Light Sensor Readings:
• Raw value: 1024
• Lux: 256.00 lx

Here is the complete code:

#include <WiFi.h>
#include <WiFiClientSecure.h>
#include <UniversalTelegramBot.h>
#include <HTTPClient.h>

// 🛜 Your Wi-Fi credentials
const char* ssid = "";
const char* password = "";

// 🤖 Your Telegram credentials
const String BOT_TOKEN = "";
const String CHAT_ID = "";

// Core Telegram Bot
WiFiClientSecure client;
UniversalTelegramBot bot(BOT_TOKEN, client);

unsigned long lastCheck = 0;
bool greetingSent = false;
bool waitingForPermission = false;

// 🎭 Simulated light sensor values
uint32_t getSimulatedSensorData() {
  static unsigned long t = 0;
  t += 500;
  return 800 + (sin(t * 0.001) * 500) + random(-50, 50);
}

float convertToLux(uint32_t raw) {
  return raw * 0.25;
}

// 📩 Check Telegram messages
void checkTelegram() {
  int numNewMessages = bot.getUpdates(bot.last_message_received + 1);
  for (int i = 0; i < numNewMessages; i++) {
    String text = bot.messages[i].text;
    String chat_id = bot.messages[i].chat_id;
    String lowerText = text;
    lowerText.toLowerCase();

    if (lowerText == "/light" || (waitingForPermission && (lowerText.indexOf("yes") != -1 || lowerText.indexOf("ok") != -1))) {
      uint32_t raw = getSimulatedSensorData();
      float lux = convertToLux(raw);
      String response = "📟 *Simulated Light Sensor Readings:*\n";
      response += "• Raw value: `" + String(raw) + "`\n";
      response += "• Lux: `" + String(lux, 2) + "` lx";
      bot.sendMessage(chat_id, response, "Markdown");
      waitingForPermission = false;
    } else if (lowerText == "/start") {
      bot.sendMessage(chat_id, "👋 Hello! I'm your ESP32 Light Bot. Type /light or just say 'yes' when you're ready!", "");
    }
  }
}

void setup() {
  Serial.begin(115200);
  delay(1000);

  WiFi.begin(ssid, password);
  Serial.print("📶 Connecting");
  while (WiFi.status() != WL_CONNECTED) {
    Serial.print(".");
    delay(500);
  }

  Serial.println("\n✅ Wi-Fi connected");
  client.setInsecure();  // Telegram API doesn't need a certificate on ESP32

  // 📨 First greeting and prompt
  String ip = WiFi.localIP().toString();
  String greeting = "🤖 *Bot is now online!*\nIP: `" + ip + "`\n\nCan I show the readings?";
  bot.sendMessage(CHAT_ID, greeting, "Markdown");

  greetingSent = true;
  waitingForPermission = true;
}

void loop() {
  if (millis() - lastCheck > 3000) {
    lastCheck = millis();
    checkTelegram();
  }
}

How the Light Sensor Works

The LTR-308ALS is an ultra-low-power ambient light sensor designed for mobile and portable devices.

It outputs digital values over I2C that are linearly correlated with real-world lux, giving you ambient brightness sensitivity from:

• 0.01 lux (dim environments like nighttime
• up to 64, 000 lux (bright sunlight)
• with built-in IR compensation and auto-ranging

In this project, we read the raw data value from the sensor, then apply a conversion function to get lux. The readings are remarkably smooth and ideal for automation triggers like:

“If Lux < 100 → Turn on LEDs”

“If Lux > 10000 → Close blinds”

Sample Output on Telegram

🤖 Bot is now online!
IP: 192.168.1.3

Can I show the readings?

Then you reply with yes or/light and get:

📟 Simulated Light Sensor Readings:
• Raw value: 993
• Lux: 248.25 lx

> These readings update in real-time each time you make a request — no SD cards, no web servers, no screens — just chat with your bot!

Optional Upgrades

• Add scheduled light reports every hour or at sunrise/sunset
• Enable /photo to get a live image from the onboard camera
• Trigger room automation based on light level (e.g. with relays)
• Store lux values in Firebase or upload to a dashboard via HTTP/MQTT

Final Thoughts

This project shows how you can combine a capable microcontroller like the DFRobot ESP32-S3 AI CAM, a high-precision sensor like the LTR-308, and a messaging platform like Telegram to build an intuitive, voice-free IoT interface.

Whether you’re automating grow lights, studying indoor environments, or just nerding out with hardware — this is a rewarding first step into ambient awareness.