Update app.py

app.py

@@ -2,143 +2,98 @@ import random
 import pandas as pd
 import streamlit as st
 import pydeck as pdk
-from datetime import datetime, timedelta
 
-# ---- Constants ----
-POLES_PER_SITE = 12
-SITES = {
-    "Hyderabad": [17.385044, 78.486671],
-    "Gadwal": [16.2351, 77.8052],
-    "Kurnool": [15.8281, 78.0373],
-    "Ballari": [15.1394, 76.9214]  # Corrected Ballari location
+# ---- Fixed Coordinates for Specific Local Areas ----
+AREA_COORDINATES = {
+    "Hyderabad": [17.4036, 78.5247],          # Ramanthapur
+    "Ballari": [15.1468, 76.9237],            # Cowl Bazar
+    "Gadwal": [16.2315, 77.7965],             # Bheem Nagar
+    "Kurnool": [15.8281, 78.0373]             # Venkata Ramana Colony
 }
 
-# ---- Helper Functions ----
-def simulate_pole(pole_id, site_name):
-    lat, lon = SITES[site_name]  # FIXED: Use constant location without random offset
-    solar_kwh = round(random.uniform(3.0, 7.5), 2)
-    wind_kwh = round(random.uniform(0.5, 2.0), 2)
-    power_required = round(random.uniform(4.0, 8.0), 2)
-    total_power = solar_kwh + wind_kwh
-    power_status = 'Sufficient' if total_power >= power_required else 'Insufficient'
-
-    tilt_angle = round(random.uniform(0, 45), 2)
-    vibration = round(random.uniform(0, 5), 2)
-    camera_status = random.choice(['Online', 'Offline'])
-
-    alert_level = 'Green'
-    anomaly_details = []
-    if tilt_angle > 30 or vibration > 3:
-        alert_level = 'Yellow'
-        anomaly_details.append("Tilt or Vibration threshold exceeded.")
-    if tilt_angle > 40 or vibration > 4.5:
-        alert_level = 'Red'
-        anomaly_details.append("Critical tilt or vibration detected.")
-
-    health_score = max(0, 100 - (tilt_angle + vibration * 10))
-    timestamp = datetime.now() - timedelta(hours=random.randint(0, 6))
+POLES_PER_SITE = 12
 
-    return {
-        'Pole ID': f'{site_name[:3].upper()}-{pole_id:03}',
-        'Site': site_name,
-        'Latitude': lat,
-        'Longitude': lon,
-        'Solar (kWh)': solar_kwh,
-        'Wind (kWh)': wind_kwh,
-        'Power Required (kWh)': power_required,
-        'Total Power (kWh)': total_power,
-        'Power Status': power_status,
-        'Tilt Angle (°)': tilt_angle,
-        'Vibration (g)': vibration,
-        'Camera Status': camera_status,
-        'Health Score': round(health_score, 2),
-        'Alert Level': alert_level,
-        'Anomalies': "; ".join(anomaly_details),
-        'Last Checked': timestamp.strftime('%Y-%m-%d %H:%M:%S')
-    }
+# ---- Helper Function to Simulate Poles in a Tight Area ----
+def generate_fixed_poles(site_name, center_lat, center_lon):
+    poles = []
+    for i in range(POLES_PER_SITE):
+        lat = center_lat + random.uniform(-0.001, 0.001)
+        lon = center_lon + random.uniform(-0.001, 0.001)
+        alert_level = random.choices(['Green', 'Yellow', 'Red'], weights=[6, 4, 2])[0]
+
+        poles.append({
+            "Pole ID": f"{site_name[:3].upper()}-{i+1:03}",
+            "Site": site_name,
+            "Latitude": lat,
+            "Longitude": lon,
+            "Alert Level": alert_level,
+            "Health Score": round(random.uniform(70, 100), 2),
+            "Power Status": random.choice(['Sufficient', 'Insufficient']),
+            "Camera Status": random.choice(['Online', 'Offline'])
+        })
+    return poles
+
+# ---- Data Preparation ----
+all_poles = []
+for site, coords in AREA_COORDINATES.items():
+    all_poles.extend(generate_fixed_poles(site, *coords))
+
+df = pd.DataFrame(all_poles)
 
 # ---- Streamlit UI ----
-st.set_page_config(page_title="Smart Pole Monitoring", layout="wide")
-st.title("\U0001F30D Smart Renewable Pole Monitoring - Multi-Site")
-
-selected_site = st.text_input("Enter site to view (Hyderabad, Gadwal, Kurnool, Ballari):", "Hyderabad")
+st.set_page_config(page_title="Localized Smart Pole View", layout="wide")
+st.title("📍 Smart Pole Monitoring - Specific Neighborhood Areas")
 
-if selected_site in SITES:
-    with st.spinner(f"Simulating poles at {selected_site}..."):
-        poles_data = [simulate_pole(i + 1, site) for site in SITES for i in range(POLES_PER_SITE)]
-        df = pd.DataFrame(poles_data)
-        site_df = df[df['Site'] == selected_site]
+site = st.selectbox("Select a site to view", list(AREA_COORDINATES.keys()))
 
-    # Summary Metrics
-    col1, col2, col3 = st.columns(3)
-    col1.metric("Total Poles", site_df.shape[0])
-    col2.metric("Red Alerts", site_df[site_df['Alert Level'] == 'Red'].shape[0])
-    col3.metric("Power Insufficiencies", site_df[site_df['Power Status'] == 'Insufficient'].shape[0])
+# ---- Filtered View ----
+filtered_df = df[df["Site"] == site]
 
-    # Table View
-    st.subheader(f"\U0001F4CB Pole Data Table for {selected_site}")
-    with st.expander("Filter Options"):
-        alert_filter = st.multiselect("Alert Level", options=site_df['Alert Level'].unique(), default=site_df['Alert Level'].unique())
-        camera_filter = st.multiselect("Camera Status", options=site_df['Camera Status'].unique(), default=site_df['Camera Status'].unique())
+# ---- Metrics ----
+col1, col2, col3 = st.columns(3)
+col1.metric("Total Poles", POLES_PER_SITE)
+col2.metric("Red Alerts", filtered_df[filtered_df["Alert Level"] == "Red"].shape[0])
+col3.metric("Offline Cameras", filtered_df[filtered_df["Camera Status"] == "Offline"].shape[0])
 
-    filtered_df = site_df[(site_df['Alert Level'].isin(alert_filter)) & (site_df['Camera Status'].isin(camera_filter))]
-    st.dataframe(filtered_df, use_container_width=True)
-
-    # Charts
-    st.subheader("\U0001F4CA Energy Generation Comparison")
-    st.bar_chart(site_df[['Solar (kWh)', 'Wind (kWh)']].mean())
-
-    st.subheader("\U0001F4C8 Tilt vs. Vibration")
-    st.scatter_chart(site_df[['Tilt Angle (°)', 'Vibration (g)']])
-
-    # ---- Map Section with Tooltip ----
-    st.subheader("\U0001F4CD Pole Alert Levels (Green, Yellow, Red)")
-
-    def alert_level_to_color(alert_level):
-        if alert_level == 'Red':
-            return [255, 0, 0, 160]
-        elif alert_level == 'Yellow':
-            return [255, 255, 0, 160]
-        else:
-            return [0, 255, 0, 160]
-
-    if not site_df.empty:
-        site_df = site_df.copy()
-        site_df['Color'] = site_df['Alert Level'].apply(alert_level_to_color)
-
-        st.pydeck_chart(pdk.Deck(
-            initial_view_state=pdk.ViewState(
-                latitude=SITES[selected_site][0],
-                longitude=SITES[selected_site][1],
-                zoom=12,
-                pitch=50
-            ),
-            layers=[
-                pdk.Layer(
-                    'ScatterplotLayer',
-                    data=site_df,
-                    get_position='[Longitude, Latitude]',
-                    get_color='Color',
-                    get_radius=100,
-                    pickable=True
-                )
-            ],
-            tooltip={
-                "html": "<b>Pole ID:</b> {Pole ID}<br/>"
-                        "<b>Health Score:</b> {Health Score}<br/>"
-                        "<b>Alert Level:</b> {Alert Level}<br/>"
-                        "<b>Power Status:</b> {Power Status}<br/>"
-                        "<b>Camera Status:</b> {Camera Status}<br/>"
-                        "<b>Last Checked:</b> {Last Checked}",
-                "style": {
-                    "backgroundColor": "black",
-                    "color": "white"
-                }
-            }
-        ))
+# ---- Map Color Mapping ----
+def alert_color(alert):
+    return {
+        "Green": [0, 255, 0, 160],
+        "Yellow": [255, 255, 0, 160],
+        "Red": [255, 0, 0, 160]
+    }[alert]
+
+filtered_df = filtered_df.copy()
+filtered_df["Color"] = filtered_df["Alert Level"].apply(alert_color)
+
+# ---- Map ----
+st.pydeck_chart(pdk.Deck(
+    initial_view_state=pdk.ViewState(
+        latitude=AREA_COORDINATES[site][0],
+        longitude=AREA_COORDINATES[site][1],
+        zoom=15,
+        pitch=45
+    ),
+    layers=[
+        pdk.Layer(
+            "ScatterplotLayer",
+            data=filtered_df,
+            get_position='[Longitude, Latitude]',
+            get_color='Color',
+            get_radius=100,
+            pickable=True
+        )
+    ],
+    tooltip={
+        "html": "<b>Pole ID:</b> {Pole ID}<br/>"
+                "<b>Health Score:</b> {Health Score}<br/>"
+                "<b>Alert Level:</b> {Alert Level}<br/>"
+                "<b>Camera:</b> {Camera Status}<br/>"
+                "<b>Power:</b> {Power Status}",
+        "style": {"color": "white", "backgroundColor": "black"}
+    }
+))
 
-        st.markdown("<h3 style='text-align: center;'>Click on a pole to view details</h3>", unsafe_allow_html=True)
-    else:
-        st.info("No poles data available for this site.")
-else:
-    st.warning("Invalid site. Please enter one of: Hyderabad, Gadwal, Kurnool, Ballari")
+# ---- Table View ----
+st.subheader(f"📋 Pole Details in {site}")
+st.dataframe(filtered_df, use_container_width=True)