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import streamlit as st | |
import pandas as pd | |
import random | |
import time | |
st.title("π Astronaut Survival Monitor") | |
# Simulating real-time data updates | |
def get_real_time_data(): | |
return { | |
"Heart Rate (BPM)": random.randint(60, 120), | |
"Oxygen Saturation (%)": round(random.uniform(85, 100), 1), | |
"Blood Pressure (mmHg)": f"{random.randint(90, 120)}/{random.randint(60, 80)}", | |
"Respiratory Rate (BPM)": random.randint(12, 20), | |
"Hydration Level (%)": round(random.uniform(40, 100), 1), | |
"Battery Level (%)": random.randint(10, 100), | |
"Food Supply (Days)": random.randint(1, 10), | |
"Water Supply (Liters)": random.randint(1, 50), | |
} | |
# Survival Time Prediction | |
def predict_survival_time(data): | |
oxygen_factor = data["Oxygen Saturation (%)"] / 100 | |
hydration_factor = data["Hydration Level (%)"] / 100 | |
battery_factor = data["Battery Level (%)"] / 100 | |
food_factor = data["Food Supply (Days)"] / 10 | |
survival_hours = (oxygen_factor + hydration_factor + battery_factor + food_factor) * 10 | |
return round(survival_hours, 2) | |
# Real-time simulation | |
data = get_real_time_data() | |
survival_time = predict_survival_time(data) | |
st.metric("Predicted Survival Time", f"{survival_time} Hours") | |
# Display real-time health and resource data | |
st.write("### Health Metrics") | |
for key, value in data.items(): | |
st.metric(key, value) | |
if data["Oxygen Saturation (%)"] < 90 or data["Battery Level (%)"] < 20: | |
st.warning("π¨ Alert: Low Oxygen or Power Levels Detected!") | |