r/esp8266

I've been working on a Smart Irrigation System using an ESP32 + machine learning, and I've finally got the main pipeline working end-to-end.

The system uses an ESP32, capacitive soil-moisture sensor, and DHT11 to collect environmental data. The readings are sent to a web dashboard, which communicates with a Flask API that runs the ML model and returns an irrigation prediction.

The overall pipeline is:

ESP32 sensors → Web Dashboard → Flask API → ML Model → Irrigation Prediction

The project currently includes:

• Real-time soil moisture monitoring
• Temperature and humidity monitoring
• Web dashboard hosted by the ESP32
• ML model for irrigation prediction
• Model evaluation with a confusion matrix
• Feature-importance analysis
• Flask inference server
• API communication between the dashboard and ML model

The first screenshot shows the live dashboard, including the sensor readings and AI irrigation prediction section.

The second shows part of the JavaScript/API integration and project structure, where the dashboard communicates with the ML inference server.

One thing I found particularly interesting was getting the ESP32, web interface, API, and ML model to actually communicate with each other. The AI prediction wouldn't load until the inference server was running, which made the entire pipeline click for me.

This started as a simple ESP32 soil-moisture monitoring project, but I gradually expanded it into a complete IoT + AI system.

I'm planning to improve it further by collecting more real-world data and adding additional environmental inputs such as light intensity.

I'd appreciate feedback from the ESP32 community, especially on the hardware setup, system architecture, and how I could improve the project further.

🔗 GitHub (Full Video and Requirements) :

https://github.com/aqib-ai-ml/ai-powered-smart-irrigation

For years, edge AI has promised intelligence everywhere. In practice, most "edge AI" still means sending data to the cloud, relying on large Linux systems, or requiring expensive accelerator hardware.

SuperESP changes that.

Built on Atome LM v2, SuperESP transforms a standard ESP32 into a tiny AI appliance capable of running twelve practical applications entirely offline.

No GPUs.

No subscriptions.

No datacenter.

Just a microcontroller that costs less than a cup of coffee.

Every claim is verifiable and tied to a script.

What SuperESP Actually Is

SuperESP is not another chatbot squeezed onto a microcontroller.

It is a collection of specialized ternary AI models designed to classify events, patterns, behaviors, and anomalies directly on the device.

The current release includes:

Agriculture monitoring

Voice commands

Motion recognition

Gesture detection

Sound event classification

Machine anomaly detection

Air quality analysis

Energy monitoring

Occupancy estimation

Wearable activity tracking

Water leak detection

Predictive maintenance

It comes also with :

+ ESP32 OS

+ Universal Installer

Check out everything :

https://github.com/TilelliLab/atome-lm

Its for a high school project, a smart laser security system.

Idk why am always having this error, i tried everything and it still shows this.

Sorry for the code being AI generated, its my first time ever doing such a project...

CODE:

// --- Pin Definitions ---
const int LDR_ANALOG_PIN  = A0; // Analog light reading (A0)
const int BUZZER_PIN      = 12; // Active Alarm Buzzer (GPIO12 / D6)
const int LED_GREEN       = 5;  // System Armed Indicator (GPIO5 / D1)
const int LED_RED         = 4;  // Interruption Indicator (GPIO4 / D2)
const int ROOM_LIGHTS_PIN = 0;  // Transistor Base (GPIO0 / D3)
// Initial threshold estimate (we will adjust this after checking readings)
int lightThreshold = 500; 
void setup() {
  Serial.begin(115200);
  pinMode(BUZZER_PIN, OUTPUT);
  pinMode(LED_GREEN, OUTPUT);
  pinMode(LED_RED, OUTPUT);
  pinMode(ROOM_LIGHTS_PIN, OUTPUT);
  // Set initial state
  digitalWrite(BUZZER_PIN, LOW);
  digitalWrite(LED_GREEN, HIGH);
  digitalWrite(LED_RED, LOW);
  digitalWrite(ROOM_LIGHTS_PIN, LOW);
  Serial.println("\n==========================================");
  Serial.println("  Smart Laser Tripwire System Initialized ");
  Serial.println("==========================================");
}
void loop() {
  int ldrValue = analogRead(LDR_ANALOG_PIN);
  Serial.print("LDR Raw Value: ");
  Serial.println(ldrValue);
  // Logic check: if light level changes significantly
  if (ldrValue > lightThreshold) {
// Laser beam broken (Darker / Tripped)
digitalWrite(LED_GREEN, LOW);
digitalWrite(LED_RED, HIGH);
digitalWrite(BUZZER_PIN, HIGH);       // Sound alarm
digitalWrite(ROOM_LIGHTS_PIN, HIGH);  // Turn ON white room LEDs
  } else {
// Normal state (Laser hitting LDR)
digitalWrite(LED_GREEN, HIGH);
digitalWrite(LED_RED, LOW);
digitalWrite(BUZZER_PIN, LOW);        // Silence alarm
digitalWrite(ROOM_LIGHTS_PIN, LOW);   // Keep room LEDs OFF
  }
  delay(200);
}