Create evaluation_dashboard.py

evaluation_dashboard.py

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+import pandas as pd
+import sqlite3
+import gradio as gr
+import matplotlib.pyplot as plt
+
+
+DB_PATH = "traffic_analytics.db"
+
+
+# --------------------------------------------------
+# Load Analytics Data
+# --------------------------------------------------
+
+def load_data():
+
+    conn = sqlite3.connect(DB_PATH)
+
+    query = """
+    SELECT *
+    FROM vehicle_records
+    """
+
+    df = pd.read_sql(query, conn)
+
+    conn.close()
+
+    return df
+
+
+# --------------------------------------------------
+# Calculate Metrics
+# --------------------------------------------------
+
+def calculate_metrics():
+
+    try:
+
+        df = load_data()
+
+        total_vehicles = len(df)
+
+        ev_count = len(
+            df[df["is_ev"] == 1]
+        )
+
+        non_ev_count = total_vehicles - ev_count
+
+        ev_rate = (
+            ev_count / total_vehicles * 100
+            if total_vehicles > 0
+            else 0
+        )
+
+        total_toll = df["original_toll"].sum()
+
+        toll_discount = (
+            df["toll_discount_amount"].sum()
+        )
+
+        total_parking = (
+            df["original_parking"].sum()
+        )
+
+        parking_discount = (
+            df["parking_discount_amount"].sum()
+        )
+
+        govt_incentive = (
+            df["government_incentive"].sum()
+        )
+
+        avg_green_score = (
+            df["green_score"].mean()
+        )
+
+        avg_processing_time = (
+            df["processing_time"].mean()
+            if "processing_time" in df.columns
+            else 0
+        )
+
+        return {
+            "Total Vehicles":
+                total_vehicles,
+
+            "EV Vehicles":
+                ev_count,
+
+            "Non-EV Vehicles":
+                non_ev_count,
+
+            "EV Adoption Rate (%)":
+                round(ev_rate, 2),
+
+            "Total Toll Revenue":
+                round(total_toll, 2),
+
+            "Toll Discounts":
+                round(toll_discount, 2),
+
+            "Total Parking Revenue":
+                round(total_parking, 2),
+
+            "Parking Discounts":
+                round(parking_discount, 2),
+
+            "Govt Incentives":
+                round(govt_incentive, 2),
+
+            "Avg Green Score":
+                round(avg_green_score, 2),
+
+            "Avg Processing Time":
+                round(avg_processing_time, 2)
+        }
+
+    except Exception as e:
+
+        return {
+            "Error": str(e)
+        }
+
+
+# --------------------------------------------------
+# Create Charts
+# --------------------------------------------------
+
+def create_charts():
+
+    df = load_data()
+
+    # EV vs Non-EV
+    plt.figure(figsize=(5, 4))
+
+    counts = [
+        len(df[df["is_ev"] == 1]),
+        len(df[df["is_ev"] == 0])
+    ]
+
+    plt.bar(
+        ["EV", "Non-EV"],
+        counts
+    )
+
+    plt.title("Vehicle Distribution")
+
+    vehicle_chart = "vehicle_distribution.png"
+
+    plt.savefig(vehicle_chart)
+
+    plt.close()
+
+    # Savings Chart
+
+    plt.figure(figsize=(5, 4))
+
+    savings = [
+        df["toll_discount_amount"].sum(),
+        df["parking_discount_amount"].sum()
+    ]
+
+    plt.bar(
+        ["Toll Savings",
+         "Parking Savings"],
+        savings
+    )
+
+    plt.title("Savings Distribution")
+
+    savings_chart = "savings_distribution.png"
+
+    plt.savefig(savings_chart)
+
+    plt.close()
+
+    return vehicle_chart, savings_chart
+
+
+# --------------------------------------------------
+# Dashboard Refresh
+# --------------------------------------------------
+
+def refresh_dashboard():
+
+    metrics = calculate_metrics()
+
+    metric_text = ""
+
+    for key, value in metrics.items():
+
+        metric_text += (
+            f"{key}: {value}\n"
+        )
+
+    chart1, chart2 = create_charts()
+
+    return metric_text, chart1, chart2
+
+
+# --------------------------------------------------
+# Gradio UI
+# --------------------------------------------------
+
+with gr.Blocks() as demo:
+
+    gr.Markdown(
+        "# 🚦 Smart Traffic & EV Analytics Dashboard"
+    )
+
+    refresh_btn = gr.Button(
+        "Refresh Dashboard"
+    )
+
+    metrics_box = gr.Textbox(
+        label="Evaluation Metrics",
+        lines=15
+    )
+
+    vehicle_chart = gr.Image(
+        label="EV vs Non-EV Vehicles"
+    )
+
+    savings_chart = gr.Image(
+        label="Discount Savings"
+    )
+
+    refresh_btn.click(
+        fn=refresh_dashboard,
+        inputs=[],
+        outputs=[
+            metrics_box,
+            vehicle_chart,
+            savings_chart
+        ]
+    )
+
+demo.launch()