Spaces:
Sleeping
Sleeping
File size: 2,947 Bytes
32841d3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
import streamlit as st
import pandas as pd
import plotly.express as px
import numpy as np
import time
# Simulated data (you can replace this with data from salesforce_integration.py or simulator.py)
def generate_mock_data(n=100):
np.random.seed(42)
data = {
"PoleID": [f"Pole_{i:05}" for i in range(n)],
"Site": np.random.choice(["Site 1", "Site 2", "Site 3", "Site 4"], n),
"SolarGen(kWh)": np.random.uniform(2.0, 6.0, n),
"WindGen(kWh)": np.random.uniform(0.5, 2.0, n),
"Tilt(°)": np.random.uniform(0, 15, n),
"Vibration(g)": np.random.uniform(0, 3, n),
"CameraStatus": np.random.choice(["Online", "Offline"], n),
"PowerSufficient": np.random.choice(["Yes", "No"], n),
}
df = pd.DataFrame(data)
# Rule-based alert level
df["Anomalies"] = df.apply(lambda row: [
"LowSolarOutput" if row["SolarGen(kWh)"] < 4.0 else "",
"LowWindOutput" if row["WindGen(kWh)"] < 0.7 else "",
"PoleTiltRisk" if row["Tilt(°)"] > 10 else "",
"VibrationAlert" if row["Vibration(g)"] > 2.0 else "",
"CameraOffline" if row["CameraStatus"] == "Offline" else "",
"PowerInsufficient" if row["PowerSufficient"] == "No" else "",
], axis=1)
df["Anomalies"] = df["Anomalies"].apply(lambda x: [a for a in x if a])
df["AlertLevel"] = df["Anomalies"].apply(lambda x: "Green" if len(x) == 0 else "Yellow" if len(x) == 1 else "Red")
return df
# Visuals
def show_heatmap(df):
st.subheader("🌡️ Fault Distribution Heatmap")
map_data = df.groupby(['Site', 'AlertLevel']).size().reset_index(name="Count")
fig = px.density_heatmap(
map_data, x="Site", y="AlertLevel", z="Count", color_continuous_scale="Reds", title="Alerts per Site"
)
st.plotly_chart(fig, use_container_width=True)
def show_red_alerts(df):
st.subheader("🚨 Blinking Red Alert Poles")
red_df = df[df["AlertLevel"] == "Red"]
if red_df.empty:
st.success("No red alerts right now!")
return
for _, row in red_df.iterrows():
with st.container():
st.markdown(
f"<div style='padding:8px; background-color:#ffcccc; animation: blink 1s infinite;'>"
f"<strong>{row['PoleID']}</strong>: {', '.join(row['Anomalies'])}</div>",
unsafe_allow_html=True
)
st.markdown(
"""
<style>
@keyframes blink {
50% { background-color: #ff4d4d; }
}
</style>
""",
unsafe_allow_html=True
)
# Main
st.set_page_config("VIEP Heatmap Dashboard", layout="wide")
st.title("🌍 Vedavathi Smart Pole Monitoring Dashboard")
df = generate_mock_data()
# Filters
alert_filter = st.selectbox("Filter by Alert Level", ["All", "Green", "Yellow", "Red"])
if alert_filter != "All":
df = df[df["AlertLevel"] == alert_filter]
# Views
show_heatmap(df)
show_red_alerts(df)
|