Sanjayraju30's picture
Update app.py
30b7530 verified
raw
history blame
6.31 kB
import random
import pandas as pd
import streamlit as st
import pydeck as pdk
from datetime import datetime, timedelta
import time
# ---- Constants ----
POLES_PER_SITE = 12
SITES = {
"Hyderabad": [17.385044, 78.486671],
"Gadwal": [16.2351, 77.8052],
"Kurnool": [15.8281, 78.0373],
"Ballari": [12.9716, 77.5946]
}
# ---- Helper Functions ----
def generate_location(base_lat, base_lon):
return [
base_lat + random.uniform(-0.02, 0.02),
base_lon + random.uniform(-0.02, 0.02)
]
def simulate_pole(pole_id, site_name):
lat, lon = generate_location(*SITES[site_name])
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))
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 (Β°)': 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')
}
# ---- Streamlit UI ----
st.set_page_config(page_title="Smart Pole Monitoring", layout="wide")
st.title("🌍 Smart Renewable Pole Monitoring - Multi-Site")
selected_site = st.text_input("Enter site to view (Hyderabad, Gadwal, Kurnool, Ballari):", "Hyderabad")
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]
# 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])
# Table View
st.subheader(f"πŸ“‹ 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())
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("πŸ“Š Energy Generation Comparison")
st.bar_chart(site_df[['Solar (kWh)', 'Wind (kWh)']].mean())
st.subheader("πŸ“ˆ Tilt vs. Vibration")
st.scatter_chart(site_df[['Tilt Angle (Β°)', 'Vibration (g)']])
# ---- Map Section with Tooltip and Blinking Effect ----
st.subheader("πŸ“ Pole Alert Levels (Green, Yellow, Red)")
def alert_level_to_color(alert_level):
if alert_level == 'Red':
return [255, 0, 0, 160] # Red
elif alert_level == 'Yellow':
return [255, 255, 0, 160] # Yellow
else:
return [0, 255, 0, 160] # Green
# Function to make Red poles blink by changing radius
def get_radius(alert, t):
if alert == 'Red':
return 200 + 100 * abs((t % 2) - 1) # alternate between 100 and 300
else:
return 100
t = int(time.time()) # current time in seconds
site_df['Radius'] = site_df['Alert Level'].apply(lambda x: get_radius(x, t))
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='Radius', # dynamic radius for blinking
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"
}
}
))
st.markdown("<h3 style='text-align: center;'>Click on a pole to view details</h3>", unsafe_allow_html=True)
# Auto-refresh to trigger blinking effect
time.sleep(1) # 1 second blink
st.experimental_rerun()
else:
st.info("No poles data available for this site.")
else:
st.warning("Invalid site. Please enter one of: Hyderabad, Gadwal, Kurnool, Ballari")