Contrôleur d'irrigation intelligent BAYYTI-B1 : analyse technique approfondie

System Architecture

The BAYYTI-B1 is a solar-powered, AI-enabled irrigation controller designed for off-grid agricultural applications. Built on Raspberry Pi 4 with custom hardware extensions, it provides enterprise-grade reliability at an affordable price point.

Hardware Specifications

Core Components

• Processor: Raspberry Pi 4 (4GB RAM)
• Storage: 32GB Industrial-grade SD Card
• Power: 50W Solar Panel + 12V 20Ah Battery
• Connectivity: 4G LTE, WiFi, Bluetooth 5.0
• Enclosure: IP67 Weatherproof

Sensor Inputs

• 8x Soil Moisture Sensor Ports (Capacitive)
• 4x Temperature/Humidity Sensor Ports (DHT22)
• 2x Flow Meter Inputs
• 2x Pressure Sensor Inputs
• 1x Rain Sensor Input

Control Outputs

• 8x Solenoid Valve Outputs (24V AC, 10A)
• 4x Pump Control Relays (240V AC, 30A)
• 2x Auxiliary Outputs

Software Architecture

class IrrigationController:
    def __init__(self):
        self.sensors = SensorManager()
        self.valves = ValveController()
        self.ai_engine = AIOptimizer()
        self.cloud = CloudConnector()
    
    async def run_irrigation_cycle(self):
        # Read all sensors
        sensor_data = await self.sensors.read_all()
        
        # Get AI recommendations
        recommendations = self.ai_engine.optimize(sensor_data)
        
        # Execute irrigation
        for zone in recommendations['zones_to_water']:
            await self.valves.open(zone['id'], zone['duration'])
        
        # Log to cloud
        await self.cloud.log_event(sensor_data, recommendations)

AI Optimization Engine

The BAYYTI-B1 uses TensorFlow Lite for on-device AI inference, analyzing multiple factors:

Input Parameters

• Current soil moisture levels (8 zones)
• Soil temperature and ambient temperature
• Humidity levels
• Weather forecast (next 48 hours)
• Historical irrigation data
• Crop type and growth stage
• Evapotranspiration rate

AI Model Training

import tensorflow as tf

model = tf.keras.Sequential([
    tf.keras.layers.Dense(64, activation='relu', input_shape=(15,)),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(32, activation='relu'),
    tf.keras.layers.Dense(8, activation='sigmoid')  # 8 zones
])

model.compile(
    optimizer='adam',
    loss='binary_crossentropy',
    metrics=['accuracy']
)

Mobile App Integration

The BAYYTI mobile app provides complete remote control and monitoring:

Key Features

• Real-time sensor data visualization
• Manual and automatic irrigation control
• Historical data and analytics
• Water usage reports
• Alert notifications
• Multi-user access control

Installation Process

1. Physical Installation

# Mount controller in weatherproof location
# Connect solar panel (50W, 12V)
# Install battery (12V 20Ah)
# Connect 4G antenna

2. Sensor Wiring

Connect soil moisture sensors using shielded cables (max 100m distance):

Sensor Pin Layout:
- Red: VCC (3.3V)
- Black: GND
- Yellow: Signal (Analog)

// Configure via web interface
const config = {
  zones: [
    {
      id: 1,
      name: "Zone A - Vegetables",
      sensorId: "SM001",
      valveId: "V001",
      cropType: "tomatoes",
      minMoisture: 35,
      maxMoisture: 65
    }
  ],
  schedule: {
    mode: "auto",
    maxDailyWatering: 120, // minutes
    preferredTimes: ["06:00", "18:00"]
  }
};