🏭 פרויקט לימודי: מערכת חיישנים תעשייתית

# ==============================================
# סימולטור חיישנים תעשייתיים
# קובץ: sensor_simulator.py
# ==============================================
import random
import csv
from datetime import datetime, timedelta

def generate_sensor_data(num_samples=100):
    """יוצר נתוני חיישנים מדומים עם רעש אקראי רציף"""
    data = []
    start_time = datetime.now()
    
    for i in range(num_samples):
        timestamp = start_time + timedelta(seconds=i)
        
        # טמפרטורה: בסיס 50°C עם רעש גאוסיאני
        temperature = round(50 + random.gauss(0, 10), 2)
        temperature = max(20, min(80, temperature))
        
        # לחץ: בסיס 5.5 bar
        pressure = round(5.5 + random.gauss(0, 1.5), 2)
        pressure = max(1, min(10, pressure))
        
        # רטט: בסיס 2.5 mm/s
        vibration = round(2.5 + random.gauss(0, 0.8), 2)
        vibration = max(0, min(5, vibration))
        
        data.append({
            'timestamp': timestamp.strftime('%Y-%m-%d %H:%M:%S'),
            'temperature': temperature,
            'pressure': pressure,
            'vibration': vibration
        })
    return data

def save_to_csv(data, filename='sensor_data.csv'):
    with open(filename, 'w', newline='', encoding='utf-8') as file:
        fieldnames = ['timestamp', 'temperature', 'pressure', 'vibration']
        writer = csv.DictWriter(file, fieldnames=fieldnames)
        writer.writeheader()
        writer.writerows(data)
    print(f"✅ נשמרו {len(data)} דגימות לקובץ {filename}")

if __name__ == "__main__":
    sensor_data = generate_sensor_data(100)
    save_to_csv(sensor_data)

# ==============================================
# ניתוח נתוני חיישנים
# קובץ: data_analysis.py
# ==============================================
import pandas as pd

def analyze_sensor_data(filename='sensor_data.csv'):
    df = pd.read_csv(filename)
    
    print("\n� סטטיסטיקות מערכת:")
    print("-" * 30)
    for col in ['temperature', 'pressure', 'vibration']:
        print(f"{col.capitalize()}: Mean={df[col].mean():.2f}, Max={df[col].max():.2f}")
    
    # זיהוי חריגות
    critical_temp = df[df['temperature'] > 70]
    print(f"\n⚠️ התראות קריטיות: {len(critical_temp)} דגימות מעל 70°C")
    return df

if __name__ == "__main__":
    analyze_sensor_data()

# ==============================================
# דשבורד חיישנים - Streamlit
# קובץ: dashboard.py
# ==============================================
import streamlit as st
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

st.set_page_config(page_title="🏭 Industrial Dashboard", layout="wide")
st.title("🏭 ניטור חיישנים תעשייתי")

df = pd.read_csv('sensor_data.csv')
df['timestamp'] = pd.to_datetime(df['timestamp'])

# KPIs
cols = st.columns(3)
cols[0].metric("🌡️ טמפרטורה", f"{df['temperature'].mean():.1f}°C")
cols[1].metric("🔧 לחץ", f"{df['pressure'].mean():.1f} bar")
cols[2].metric("📳 רטט", f"{df['vibration'].mean():.2f} mm/s")

# Charts
fig = make_subplots(rows=3, cols=1, shared_xaxes=True)
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['temperature'], name="Temp"), row=1, col=1)
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['pressure'], name="Pressure"), row=2, col=1)
fig.add_trace(go.Scatter(x=df['timestamp'], y=df['vibration'], name="Vibration"), row=3, col=1)

st.plotly_chart(fig, use_container_width=True)

from fastapi import FastAPI
from pydantic import BaseModel
import csv, os, datetime

app = FastAPI(title="Industrial Edge API")
@app.post("/sensor")
def receive_data(r: Reading):
    ts = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    with open('realtime_data.csv', 'a', newline='') as f:
        writer = csv.writer(f)
        writer.writerow([ts, r.temperature, r.pressure, r.vibration])
    return {"status": "received", "timestamp": ts, "data": r.dict()}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

import requests, time, random

def send_data():
    while True:
        data = {
            "temperature": round(random.uniform(20, 100), 2),
            "pressure": round(random.uniform(0, 15), 2),
            "vibration": round(random.uniform(0, 5), 2)
        }
        try:
            r = requests.post("http://localhost:8000/sensor", json=data)
            print(f"Sent: {data} | Status: {r.status_code}")
        except:
            print("Connection failed...")
        time.sleep(1)

if __name__ == "__main__":
    send_data()

import streamlit as st
import pandas as pd
import plotly.express as px
import time

st.set_page_config(page_title="Industrial Dashboard", layout="wide")
st.title("🏭 Real-Time Factory Monitor")

def load_data():
    return pd.read_csv('realtime_data.csv', names=['time', 'temp', 'pres', 'vib'])

placeholder = st.empty()

while True:
    try:
        df = load_data()
        with placeholder.container():
            kpi1, kpi2, kpi3 = st.columns(3)
            kpi1.metric("Temperature", f"{df['temp'].iloc[-1]}°C")
            kpi2.metric("Pressure", f"{df['pres'].iloc[-1]} bar")
            kpi3.metric("Vibration", f"{df['vib'].iloc[-1]} mm/s")
            
            fig = px.line(df.tail(20), x='time', y=['temp', 'pres', 'vib'], title="Sensor Trends")
            st.plotly_chart(fig, use_container_width=True)
    except:
        st.info("Waiting for sensor data...")
    time.sleep(1)