removed temperature

DataService/enhanced_generator.py

@@ -256,7 +256,7 @@ class EnhancedMetroDataGenerator:
                     estimated_hours = random.randint(2, 24)
                 
                 job = {
-                    "job_id": f"JC-{random.randint(10000, 99999)}",
+                    "job_card_id": f"JC-{random.randint(10000, 99999)}",
                     "trainset_id": ts_id,
                     "work_order_number": f"WO-{random.randint(100000, 999999)}",
                     "job_type": random.choice(job_types),
@@ -444,11 +444,6 @@ class EnhancedMetroDataGenerator:
                     "bogie_2": round(random.uniform(0.5, 3.5) / reliability_factor, 2),
                     "unit": "mm/s"
                 },
-                "temperature": {
-                    "motor_1": round(random.uniform(45, 85) + (1 - reliability_factor) * 10, 1),
-                    "motor_2": round(random.uniform(45, 85) + (1 - reliability_factor) * 10, 1),
-                    "unit": "°C"
-                },
                 "overall_condition": "Good" if reliability_factor > 0.85 else "Fair" if reliability_factor > 0.75 else "Poor"
             }
             sensor_data.append(sensors)
@@ -560,8 +555,7 @@ class EnhancedMetroDataGenerator:
         return {
             "date": datetime.now().date().isoformat(),
             "weather": {
-                "condition": random.choice(["Clear", "Cloudy", "Rainy"]),
-                "temperature": round(random.uniform(20, 35), 1)
+                "condition": random.choice(["Clear", "Cloudy", "Rainy"])
             },
             "ridership_forecast": {
                 "expected_passengers": random.randint(80000, 150000),

DataService/synthetic_base.py

@@ -119,13 +119,6 @@ class MetroSyntheticDataGenerator:
                     "bogie_2": round(random.uniform(0.5, 3.5), 2),
                     "unit": "mm/s"
                 },
-                "temperature": {
-                    "motor_1": round(random.uniform(45, 85), 1),
-                    "motor_2": round(random.uniform(45, 85), 1),
-                    "brake_disc": round(random.uniform(25, 120), 1),
-                    "cabin": round(random.uniform(18, 28), 1),
-                    "unit": "°C"
-                },
                 "pressure": {
                     "brake_system": round(random.uniform(5.5, 8.5), 2),
                     "pneumatic_doors": round(random.uniform(6.0, 8.0), 2),
@@ -266,7 +259,6 @@ class MetroSyntheticDataGenerator:
         return {
             "date": datetime.now().date().isoformat(),
             "weather": {
-                "temperature": round(random.uniform(20, 35), 1),
                 "humidity": random.randint(60, 90),
                 "rainfall_mm": round(random.uniform(0, 50), 1),
                 "condition": random.choice(["Clear", "Cloudy", "Rainy", "Stormy"])

docs/FEATURES_NEEDED.md

@@ -213,11 +213,11 @@ The GreedyOptim system uses constraint-based optimization algorithms (GA, PSO, C
 | Feature | Description | Priority | Importance |
 |---------|-------------|----------|------------|
 | `vibration_levels` | Bogie vibration (mm/s) | **LOW** | 2/5 |
-| `temperature_readings` | Motor temperature (°C) | **LOW** | 2/5 |
 | `power_consumption` | Energy usage (kWh) | **LOW** | 2/5 |
 | `door_cycle_count` | Door operations | **LOW** | 2/5 |
 
 **Use Case:** Real-time condition monitoring to update health scores
+**Note:** Temperature data removed - not used for optimization (only as optional constraint: max ~800°C)
 
 ---
 
@@ -499,10 +499,11 @@ dow_cos = cos(2 * π * day_of_week / 7)
 **Nice-to-Have:**
 
 1. **IoT Sensor Streams**
-   - Vibration, temperature, power
+   - Vibration, power consumption
    - Real-time monitoring
    - **Collection Method:** IoT platform integration
    - **Frequency:** Real-time (every second/minute)
+   - **Note:** Temperature excluded (not used in optimization)
 
 2. **External Factors**
    - Weather data
@@ -713,7 +714,7 @@ dow_cos = cos(2 * π * day_of_week / 7)
 4. **IoT Platform** (if available)
    - Real-time sensor data
    - Component health (automated)
-   - Vibration, temperature, etc.
+   - Vibration, power consumption, door cycles, etc.
 
 5. **Contract Management System**
    - Branding contracts