Update app.py

app.py

@@ -3,25 +3,39 @@ import pandas as pd
 import streamlit as st
 import pydeck as pdk
 
-# ---- 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
+# ---- Area-Specific Configuration ----
+AREA_DETAILS = {
+    "Hyderabad": {
+        "coords": [17.4036, 78.5247],  # Ramanthapur (open area)
+        "area_name": "Ramanthapur Dairy Farm",
+        "purpose": "Dairy Farm"
+    },
+    "Ballari": {
+        "coords": [15.1468, 76.9237],  # Cowl Bazar
+        "area_name": "Cowl Bazar Power Station",
+        "purpose": "Power Station"
+    },
+    "Gadwal": {
+        "coords": [16.2315, 77.7965],  # Bheem Nagar
+        "area_name": "Bheem Nagar Solar Station",
+        "purpose": "Solar Station"
+    },
+    "Kurnool": {
+        "coords": [15.8281, 78.0373],  # Venkata Ramana Colony
+        "area_name": "Venkata Ramana Agriculture Field",
+        "purpose": "Agriculture Monitoring"
+    }
 }
 
 POLES_PER_SITE = 12
 
-# ---- Helper Function to Simulate Poles in a Horizontal Line ----
-def generate_fixed_poles(site_name, center_lat, center_lon):
+# ---- Generate Poles in Open Area Aligned Horizontally ----
+def generate_open_area_poles(site_name, center_lat, center_lon, area, purpose):
     poles = []
-    spacing = 0.0005  # controls spacing between poles horizontally
-
+    spacing = 0.0006  # fine-tuned horizontal spread
     for i in range(POLES_PER_SITE):
-        lat = center_lat  # all poles share the same latitude (horizontal alignment)
-        lon = center_lon + (i - POLES_PER_SITE // 2) * spacing  # symmetric spread around center
-
+        lat = center_lat + random.uniform(-0.0002, 0.0002)
+        lon = center_lon + (i - POLES_PER_SITE // 2) * spacing
         alert_level = random.choices(['Green', 'Yellow', 'Red'], weights=[6, 4, 2])[0]
 
         poles.append({
@@ -32,33 +46,41 @@ def generate_fixed_poles(site_name, center_lat, center_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'])
+            "Camera Status": random.choice(['Online', 'Offline']),
+            "Location Area": area,
+            "Purpose": purpose
         })
     return poles
 
-# ---- Data Preparation ----
+# ---- Prepare Full DataFrame ----
 all_poles = []
-for site, coords in AREA_COORDINATES.items():
-    all_poles.extend(generate_fixed_poles(site, *coords))
+for site, details in AREA_DETAILS.items():
+    poles = generate_open_area_poles(site, *details['coords'], details['area_name'], details['purpose'])
+    all_poles.extend(poles)
 
 df = pd.DataFrame(all_poles)
 
 # ---- Streamlit UI ----
-st.set_page_config(page_title="Localized Smart Pole View", layout="wide")
-st.title("📍 Smart Pole Monitoring - Specific Neighborhood Areas")
+st.set_page_config(page_title="Smart Pole Visual Dashboard", layout="wide")
+st.title("🌐 Smart Renewable Pole Monitoring Dashboard")
 
-site = st.selectbox("Select a site to view", list(AREA_COORDINATES.keys()))
+site = st.selectbox("📍 Select a site location:", list(AREA_DETAILS.keys()))
+selected = AREA_DETAILS[site]
 
 # ---- Filtered View ----
 filtered_df = df[df["Site"] == site]
 
-# ---- Metrics ----
+# ---- Display Site Description ----
+st.markdown(f"### 📌 Location: **{selected['area_name']}**")
+st.markdown(f"🔧 **Poles Purpose**: {selected['purpose']}")
+
+# ---- KPI 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])
+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])
 
-# ---- Map Color Mapping ----
+# ---- Alert Level to Color ----
 def alert_color(alert):
     return {
         "Green": [0, 255, 0, 160],
@@ -69,12 +91,13 @@ def alert_color(alert):
 filtered_df = filtered_df.copy()
 filtered_df["Color"] = filtered_df["Alert Level"].apply(alert_color)
 
-# ---- Map ----
+# ---- Map Visualization ----
+st.subheader("🗺️ Pole Location & Health Status")
 st.pydeck_chart(pdk.Deck(
     initial_view_state=pdk.ViewState(
-        latitude=AREA_COORDINATES[site][0],
-        longitude=AREA_COORDINATES[site][1],
-        zoom=16,
+        latitude=selected['coords'][0],
+        longitude=selected['coords'][1],
+        zoom=16.5,
         pitch=45
     ),
     layers=[
@@ -83,12 +106,14 @@ st.pydeck_chart(pdk.Deck(
             data=filtered_df,
             get_position='[Longitude, Latitude]',
             get_color='Color',
-            get_radius=20,  # Smaller marker size
+            get_radius=30,
             pickable=True
         )
     ],
     tooltip={
         "html": "<b>Pole ID:</b> {Pole ID}<br/>"
+                "<b>Location:</b> {Location Area}<br/>"
+                "<b>Purpose:</b> {Purpose}<br/>"
                 "<b>Health Score:</b> {Health Score}<br/>"
                 "<b>Alert Level:</b> {Alert Level}<br/>"
                 "<b>Camera:</b> {Camera Status}<br/>"
@@ -97,6 +122,6 @@ st.pydeck_chart(pdk.Deck(
     }
 ))
 
-# ---- Table View ----
-st.subheader(f"📋 Pole Details in {site}")
+# ---- Data Table ----
+st.subheader("📋 Detailed Pole Information")
 st.dataframe(filtered_df, use_container_width=True)