Update app.py

Updated

Author: aimtyaem

app.py

@@ -1,67 +1,82 @@
 from flask import Flask, render_template, jsonify
 import random
+import requests
 
 app = Flask(__name__)
 
-# Agriculture Knowledge Base
-AGRICULTURE_KNOWLEDGE_BASE = {
-    "recommendations": [
-        "Implement precision irrigation scheduling",
-        "Adopt integrated pest management",
-        "Use soil moisture sensors",
-        "Apply crop rotation strategies",
-        "Monitor weather patterns for planting",
-        "Utilize organic fertilizers",
-        "Practice conservation tillage",
-        "Install windbreaks for soil protection"
-    ],
-    "details": [
-        """Precision Irrigation Best Practices:
-        - Use soil moisture sensors for data-driven watering
-        - Implement drip irrigation systems
-        - Schedule irrigation during cooler hours
-        - Monitor evapotranspiration rates
-        - Adjust for crop growth stages""",
+# Simulated IoT Sensor Data for Farming
+def get_sensor_data():
+    return {
+        "soil_moisture": round(random.uniform(10, 60), 2),  # Percentage
+        "temperature": round(random.uniform(15, 40), 2),  # Celsius
+        "humidity": round(random.uniform(30, 90), 2)  # Percentage
+    }
 
-        """Integrated Pest Management:
-        - Regular field scouting
-        - Use biological control agents
-        - Implement trap cropping
-        - Apply targeted pesticides
-        - Maintain pest monitoring records"""
-    ]
+# AI-Driven Agriculture Knowledge Base
+AGRICULTURE_KNOWLEDGE_BASE = {
+    "low_moisture": "Increase irrigation frequency and consider soil amendments.",
+    "high_moisture": "Reduce watering to prevent root rot and monitor drainage.",
+    "high_temperature": "Implement shading techniques and adjust irrigation schedules.",
+    "low_temperature": "Use row covers or greenhouses to maintain optimal warmth.",
+    "high_humidity": "Increase ventilation and monitor for fungal diseases.",
+    "low_humidity": "Use mulching techniques to retain soil moisture."
 }
 
-def generate_recommendation_cards(num_cards=3):
+def generate_expert_recommendations(sensor_data):
     """
-    Generates recommendation dashboard cards for farmers.
+    Generates AI-driven recommendations based on sensor data.
     """
-    recommendations = AGRICULTURE_KNOWLEDGE_BASE["recommendations"]
-    details = AGRICULTURE_KNOWLEDGE_BASE["details"]
-
-    selected_recommendations = random.sample(recommendations, min(num_cards, len(recommendations)))
+    recommendations = []
+    
+    if sensor_data["soil_moisture"] < 20:
+        recommendations.append({"title": "Soil Moisture Alert", "details": AGRICULTURE_KNOWLEDGE_BASE["low_moisture"]})
+    elif sensor_data["soil_moisture"] > 50:
+        recommendations.append({"title": "Soil Overwatering Risk", "details": AGRICULTURE_KNOWLEDGE_BASE["high_moisture"]})
+    
+    if sensor_data["temperature"] > 35:
+        recommendations.append({"title": "Heat Stress Alert", "details": AGRICULTURE_KNOWLEDGE_BASE["high_temperature"]})
+    elif sensor_data["temperature"] < 20:
+        recommendations.append({"title": "Cold Stress Alert", "details": AGRICULTURE_KNOWLEDGE_BASE["low_temperature"]})
+    
+    if sensor_data["humidity"] > 80:
+        recommendations.append({"title": "High Humidity Warning", "details": AGRICULTURE_KNOWLEDGE_BASE["high_humidity"]})
+    elif sensor_data["humidity"] < 40:
+        recommendations.append({"title": "Low Humidity Concern", "details": AGRICULTURE_KNOWLEDGE_BASE["low_humidity"]})
 
-    recommendation_cards = []
-    for rec in selected_recommendations:
-        detail_index = recommendations.index(rec) if recommendations.index(rec) < len(details) else None
-        recommendation_cards.append({
-            "title": rec,
-            "details": details[detail_index] if detail_index is not None else "Additional information not available."
-        })
+    return recommendations if recommendations else [{"title": "Optimal Conditions", "details": "No immediate actions required."}]
 
-    return recommendation_cards
+def fetch_real_time_best_practices():
+    """
+    Fetches web-based best practices for farm management.
+    """
+    try:
+        response = requests.get("https://api.farmmanagement.best-practices.com/agriculture")
+        if response.status_code == 200:
+            return response.json().get("best_practices", [])
+        else:
+            return [{"title": "Web Data Unavailable", "details": "Real-time recommendations could not be retrieved."}]
+    except Exception as e:
+        return [{"title": "Error Fetching Data", "details": str(e)}]
 
-@app.route("/api/recommendations")
-def api_recommendations():
-    return jsonify(generate_recommendation_cards())
+@app.route("/api/dashboard")
+def api_dashboard():
+    sensor_data = get_sensor_data()
+    recommendations = generate_expert_recommendations(sensor_data)
+    web_best_practices = fetch_real_time_best_practices()
+    
+    return jsonify({
+        "sensor_data": sensor_data,
+        "recommendations": recommendations,
+        "web_best_practices": web_best_practices
+    })
 
 @app.route("/")
 def home():
-    return render_template("index.html", recommendations=generate_recommendation_cards())
-
-@app.route("/api/recommendations")
-def api_recommendations():
-    return jsonify(generate_recommendation_cards())
+    sensor_data = get_sensor_data()
+    recommendations = generate_expert_recommendations(sensor_data)
+    web_best_practices = fetch_real_time_best_practices()
+    
+    return render_template("index.html", sensor_data=sensor_data, recommendations=recommendations, web_best_practices=web_best_practices)
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=8000)
+    app.run(host="0.0.0.0", port=8000, debug=True)