Complete Implementation
python
import time
from urllib.parse import quote
from datetime import datetime
import qrcode
from enum import Enum
class MachineState(Enum):
RUNNING = "running"
IDLE = "idle"
ERROR = "error"
MAINTENANCE = "maintenance"
class ProductionLineMonitor:
"""
Smart Manufacturing IoT Monitor with aéPiot Integration
Monitors:
- Machine health and status
- Production rates
- Quality metrics
- Maintenance schedules
- Energy consumption
"""
def __init__(self, factory_id, line_id):
self.factory_id = factory_id
self.line_id = line_id
self.machines = {}
# Critical thresholds
self.thresholds = {
'temperature': 85, # Celsius
'vibration': 50, # mm/s
'pressure': 120, # PSI
'rpm': 3000, # Revolutions per minute
'production_rate': 100 # units/hour minimum
}
def monitor_machine(self, machine_id, sensor_data):
"""
Monitor individual machine and generate aéPiot alerts
Args:
machine_id: Unique machine identifier
sensor_data: Dict of sensor readings
Returns:
List of generated aéPiot URLs for alerts
"""
alerts = []
# Check temperature
if sensor_data.get('temperature', 0) > self.thresholds['temperature']:
url = self.generate_temperature_alert(machine_id, sensor_data)
alerts.append(url)
# Generate QR code for maintenance technician
self.generate_maintenance_qr(machine_id, url, "High Temperature")
# Check vibration (predictive maintenance indicator)
if sensor_data.get('vibration', 0) > self.thresholds['vibration']:
url = self.generate_vibration_alert(machine_id, sensor_data)
alerts.append(url)
# Check production rate
if sensor_data.get('production_rate', 0) < self.thresholds['production_rate']:
url = self.generate_production_alert(machine_id, sensor_data)
alerts.append(url)
# Check machine state
if sensor_data.get('state') == MachineState.ERROR.value:
url = self.generate_error_alert(machine_id, sensor_data)
alerts.append(url)
return alerts
def generate_temperature_alert(self, machine_id, sensor_data):
"""Generate temperature alert with aéPiot URL"""
temperature = sensor_data.get('temperature')
threshold = self.thresholds['temperature']
title = f"Temperature Alert - Machine {machine_id}"
description = (
f"Factory {self.factory_id} Line {self.line_id}: "
f"Temperature {temperature}°C exceeds threshold {threshold}°C. "
f"Cooling system inspection required."
)
link = f"https://factory-dashboard.com/{self.factory_id}/machines/{machine_id}/diagnostics"
aepiot_url = self.create_aepiot_url(title, description, link)
# Send to maintenance team
self.notify_maintenance_team(aepiot_url, machine_id, "temperature", priority="high")
return aepiot_url
def generate_vibration_alert(self, machine_id, sensor_data):
"""Generate vibration alert (predictive maintenance)"""
vibration = sensor_data.get('vibration')
threshold = self.thresholds['vibration']
title = f"Predictive Maintenance Alert - Machine {machine_id}"
description = (
f"Vibration {vibration} mm/s exceeds normal range {threshold} mm/s. "
f"Bearing inspection recommended within 48 hours."
)
link = f"https://factory-dashboard.com/{self.factory_id}/machines/{machine_id}/predictive"
aepiot_url = self.create_aepiot_url(title, description, link)
# Schedule predictive maintenance
self.schedule_maintenance(machine_id, aepiot_url, "predictive")
return aepiot_url
def generate_production_alert(self, machine_id, sensor_data):
"""Generate production rate alert"""
actual_rate = sensor_data.get('production_rate')
expected_rate = self.thresholds['production_rate']
efficiency = (actual_rate / expected_rate) * 100
title = f"Production Rate Alert - Machine {machine_id}"
description = (
f"Production rate {actual_rate} units/hr below target {expected_rate} units/hr. "
f"Current efficiency: {efficiency:.1f}%"
)
link = f"https://factory-dashboard.com/{self.factory_id}/machines/{machine_id}/production"
aepiot_url = self.create_aepiot_url(title, description, link)
# Notify production supervisor
self.notify_supervisor(aepiot_url, machine_id, efficiency)
return aepiot_url
def generate_error_alert(self, machine_id, sensor_data):
"""Generate critical error alert"""
error_code = sensor_data.get('error_code', 'UNKNOWN')
error_message = sensor_data.get('error_message', 'Machine error detected')
title = f"CRITICAL: Machine Error - {machine_id}"
description = (
f"Error Code {error_code}: {error_message}. "
f"Machine stopped. Immediate attention required."
)
link = f"https://factory-dashboard.com/{self.factory_id}/machines/{machine_id}/error/{error_code}"
aepiot_url = self.create_aepiot_url(title, description, link)
# Multi-channel urgent notification
self.urgent_notification(aepiot_url, machine_id, error_code)
return aepiot_url
def generate_shift_report(self, shift_id, shift_data):
"""Generate end-of-shift production report"""
# Aggregate shift data
total_production = shift_data.get('total_units', 0)
downtime_minutes = shift_data.get('downtime_minutes', 0)
quality_rate = shift_data.get('quality_rate', 100)
energy_consumption = shift_data.get('energy_kwh', 0)
title = f"Shift Report - Line {self.line_id} - Shift {shift_id}"
description = (
f"Production: {total_production} units | "
f"Downtime: {downtime_minutes}min | "
f"Quality: {quality_rate}% | "
f"Energy: {energy_consumption}kWh"
)
link = f"https://factory-dashboard.com/{self.factory_id}/reports/shift/{shift_id}"
aepiot_url = self.create_aepiot_url(title, description, link)
# Send to management
self.send_shift_report_email(aepiot_url, shift_id, shift_data)
return aepiot_url
def generate_maintenance_qr(self, machine_id, aepiot_url, issue_type):
"""Generate QR code for physical machine label"""
qr = qrcode.QRCode(
version=1,
error_correction=qrcode.constants.ERROR_CORRECT_H,
box_size=10,
border=4
)
qr.add_data(aepiot_url)
qr.make(fit=True)
img = qr.make_image(fill_color="black", back_color="white")
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
filename = f"maintenance_qr_{machine_id}_{issue_type}_{timestamp}.png"
img.save(f"qr_codes/{filename}")
# Optionally print to label printer
# self.print_to_label_printer(img, machine_id)
return filename
def create_aepiot_url(self, title, description, link):
"""Create aéPiot URL with proper encoding"""
return (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Notification methods (implement based on your infrastructure)
def notify_maintenance_team(self, url, machine_id, issue_type, priority="normal"):
"""Send notification to maintenance team"""
# SMS, email, mobile push, etc.
pass
def notify_supervisor(self, url, machine_id, efficiency):
"""Notify production supervisor"""
pass
def urgent_notification(self, url, machine_id, error_code):
"""Multi-channel urgent notification"""
pass
def schedule_maintenance(self, machine_id, url, maintenance_type):
"""Schedule predictive maintenance"""
pass
def send_shift_report_email(self, url, shift_id, shift_data):
"""Email shift report to management"""
pass6.2 Supply Chain and Asset Tracking
python
class SupplyChainTracker:
"""
Track assets through supply chain with aéPiot
Use Cases:
- Shipment tracking
- Temperature-controlled logistics
- Warehouse inventory
- Fleet management
"""
def track_shipment(self, shipment_id, iot_sensor_data):
"""Track shipment with environmental monitoring"""
# Extract sensor data
temperature = iot_sensor_data.get('temperature')
humidity = iot_sensor_data.get('humidity')
location = iot_sensor_data.get('gps_location', 'Unknown')
shock_events = iot_sensor_data.get('shock_count', 0)
# Check compliance
violations = []
if temperature:
if temperature < 35 or temperature > 45: # Cold chain example
violations.append(f"Temperature {temperature}°F out of range (35-45°F)")
if shock_events > 3:
violations.append(f"Excessive shock events: {shock_events}")
# Generate tracking URL
status = "VIOLATION" if violations else "Normal"
title = f"Shipment Tracking - {shipment_id} [{status}]"
description = (
f"Location: {location} | "
f"Temp: {temperature}°F | Humidity: {humidity}% | "
f"Shock Events: {shock_events}"
)
if violations:
description += " | VIOLATIONS: " + "; ".join(violations)
link = f"https://logistics.company.com/shipments/{shipment_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# If violations, alert logistics coordinator
if violations:
self.alert_logistics_violation(aepiot_url, shipment_id, violations)
# Update customer tracking
self.update_customer_tracking(aepiot_url, shipment_id)
return aepiot_urlChapter 7: Smart Buildings and Facility Management
7.1 Comprehensive Building Automation
python
class SmartBuildingManager:
"""
Smart building IoT management with aéPiot
Manages:
- HVAC systems
- Lighting control
- Occupancy monitoring
- Energy management
- Security systems
- Environmental quality
"""
def __init__(self, building_id):
self.building_id = building_id
# Comfort thresholds
self.comfort_ranges = {
'temperature_min': 68, # Fahrenheit
'temperature_max': 74,
'humidity_min': 30, # Percent
'humidity_max': 60,
'co2_max': 1000, # PPM
'light_min': 300, # Lux
'noise_max': 55 # dB
}
def monitor_room(self, room_id, sensor_data):
"""Monitor room environmental conditions"""
issues = []
# Temperature check
temp = sensor_data.get('temperature')
if temp:
if temp < self.comfort_ranges['temperature_min']:
issues.append(f"Temperature too low: {temp}°F")
elif temp > self.comfort_ranges['temperature_max']:
issues.append(f"Temperature too high: {temp}°F")
# Humidity check
humidity = sensor_data.get('humidity')
if humidity:
if humidity < self.comfort_ranges['humidity_min']:
issues.append(f"Humidity too low: {humidity}%")
elif humidity > self.comfort_ranges['humidity_max']:
issues.append(f"Humidity too high: {humidity}%")
# Air quality check
co2 = sensor_data.get('co2')
if co2 and co2 > self.comfort_ranges['co2_max']:
issues.append(f"CO2 elevated: {co2}ppm - Increase ventilation")
# Light level check
light = sensor_data.get('light_lux')
if light and light < self.comfort_ranges['light_min']:
issues.append(f"Insufficient lighting: {light}lux")
if issues:
title = f"Environmental Alert - {self.building_id} Room {room_id}"
description = " | ".join(issues)
link = f"https://building-mgmt.com/{self.building_id}/rooms/{room_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Notify facilities management
self.notify_facilities(aepiot_url, room_id, issues)
return aepiot_url
return None
def energy_consumption_report(self, period='daily'):
"""Generate energy consumption report with aéPiot URL"""
consumption_data = self.get_consumption_data(period)
title = f"{period.title()} Energy Report - {self.building_id}"
description = (
f"Total: {consumption_data['total_kwh']:.1f} kWh | "
f"HVAC: {consumption_data['hvac_percent']:.0f}% | "
f"Lighting: {consumption_data['lighting_percent']:.0f}% | "
f"Equipment: {consumption_data['equipment_percent']:.0f}% | "
f"Cost: ${consumption_data['cost']:.2f}"
)
link = f"https://building-mgmt.com/{self.building_id}/energy/{period}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Email to building manager
self.email_energy_report(aepiot_url, period, consumption_data)
return aepiot_url
def occupancy_tracking(self):
"""Track building occupancy by floor"""
floors_data = self.get_floor_occupancy()
urls = []
for floor_num, occupancy in floors_data.items():
title = f"Occupancy - Floor {floor_num}"
description = (
f"Current: {occupancy['current']} people | "
f"Capacity: {occupancy['capacity']} | "
f"Utilization: {occupancy['utilization_percent']:.0f}%"
)
link = f"https://building-mgmt.com/{self.building_id}/floors/{floor_num}/occupancy"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
urls.append({
'floor': floor_num,
'url': aepiot_url,
'data': occupancy
})
return urlsChapter 8: Agriculture and Environmental Monitoring
8.1 Precision Agriculture with aéPiot
python
class PrecisionAgricultureMonitor:
"""
Agricultural IoT monitoring with aéPiot semantic layer
Monitors:
- Soil moisture
- Weather conditions
- Irrigation systems
- Crop health
- Livestock conditions
"""
def monitor_soil_moisture(self, field_id, zone_id, sensor_data):
"""Monitor soil moisture and irrigation needs"""
moisture = sensor_data.get('moisture_percent')
soil_temp = sensor_data.get('soil_temperature')
crop_type = sensor_data.get('crop_type', 'General')
# Crop-specific thresholds
thresholds = {
'corn': 60,
'wheat': 55,
'soybeans': 65,
'vegetables': 70
}
min_moisture = thresholds.get(crop_type.lower(), 60)
if moisture and moisture < min_moisture:
title = f"Irrigation Required - Field {field_id} Zone {zone_id}"
description = (
f"Crop: {crop_type} | "
f"Soil Moisture: {moisture}% (Min: {min_moisture}%) | "
f"Soil Temp: {soil_temp}°F | "
f"Action: Start irrigation"
)
link = f"https://farm-mgmt.com/fields/{field_id}/zones/{zone_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Send to farm manager mobile app
self.send_mobile_notification(aepiot_url, field_id, zone_id)
# Auto-trigger irrigation if enabled
if self.auto_irrigation_enabled(field_id):
self.activate_irrigation(field_id, zone_id)
return aepiot_url
return None
def weather_station_monitoring(self, station_id, weather_data):
"""Monitor weather conditions"""
alerts = []
# High wind alert
if weather_data.get('wind_speed', 0) > 35:
alerts.append(f"High wind: {weather_data['wind_speed']} mph")
# Heavy rain alert
if weather_data.get('rainfall', 0) > 2:
alerts.append(f"Heavy rain: {weather_data['rainfall']} inches")
# Frost warning
if weather_data.get('temperature', 100) < 32:
alerts.append("FROST WARNING - Protect sensitive crops")
# Extreme heat
if weather_data.get('temperature', 0) > 100:
alerts.append(f"Extreme heat: {weather_data['temperature']}°F - Increase irrigation")
if alerts:
title = f"Weather Alert - Station {station_id}"
description = " | ".join(alerts)
link = f"https://farm-weather.com/stations/{station_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Urgent notification to farmers
self.urgent_weather_alert(aepiot_url, station_id, alerts)
return aepiot_url
return None
def livestock_monitoring(self, barn_id, sensor_data):
"""Monitor barn conditions for livestock"""
temperature = sensor_data.get('temperature')
humidity = sensor_data.get('humidity')
ammonia = sensor_data.get('ammonia_ppm', 0)
issues = []
# Temperature comfort range for cattle
if temperature:
if temperature < 40 or temperature > 80:
issues.append(f"Temperature: {temperature}°F (out of comfort range)")
# Ammonia threshold
if ammonia > 25:
issues.append(f"Ammonia: {ammonia}ppm (ventilation needed)")
# Humidity
if humidity:
if humidity > 70:
issues.append(f"High humidity: {humidity}%")
if issues:
title = f"Barn Conditions Alert - {barn_id}"
description = " | ".join(issues)
link = f"https://livestock-mgmt.com/barns/{barn_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Alert farm staff
self.alert_barn_staff(aepiot_url, barn_id, issues)
return aepiot_url
return NoneChapter 9: Healthcare and Medical Facility IoT
9.1 HIPAA-Compliant Medical IoT Implementation
CRITICAL: Healthcare implementations must comply with HIPAA, GDPR, and health data regulations.
python
import hashlib
import secrets
class MedicalIoTManager:
"""
HIPAA-compliant medical IoT integration
IMPORTANT:
- NEVER include PHI in aéPiot URLs
- Always use reference IDs
- Link to authenticated dashboards only
- Maintain audit trails
"""
def __init__(self):
self.reference_mapping = {} # Store in secure database
def vital_signs_alert(self, patient_reference, alert_type, severity):
"""Generate alert URL without PHI"""
# Use non-identifying reference ID
title = f"Patient Alert - Ref: {patient_reference}"
description = (
f"Alert Type: {alert_type} | "
f"Severity: {severity} | "
f"Immediate review required"
)
# Link to secure, authenticated dashboard
link = f"https://secure-medical-portal.hospital.com/alerts/{patient_reference}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Send only to authorized medical staff
self.notify_authorized_staff(aepiot_url, patient_reference, alert_type)
# Audit trail
self.log_hipaa_compliant_access(patient_reference, aepiot_url)
return aepiot_url
def equipment_maintenance_alert(self, equipment_id, maintenance_type):
"""Medical equipment maintenance alerts (non-PHI)"""
title = f"Equipment Maintenance - {equipment_id}"
description = (
f"Type: {maintenance_type} | "
f"Priority: HIGH | "
f"Schedule service immediately"
)
link = f"https://hospital-equipment.com/maintenance/{equipment_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Send to biomedical engineering team
self.notify_biomed_team(aepiot_url, equipment_id)
return aepiot_url
def medication_storage_monitoring(self, storage_id, sensor_data):
"""Monitor medication refrigerator/storage"""
temperature = sensor_data.get('temperature')
door_status = sensor_data.get('door_open', False)
# Medication storage standards
temp_min, temp_max = 36, 46 # Fahrenheit
alerts = []
if temperature:
if temperature < temp_min or temperature > temp_max:
alerts.append(f"Temperature {temperature}°F out of range ({temp_min}-{temp_max}°F)")
if door_status:
alerts.append("Door open - temperature stability at risk")
if alerts:
title = f"CRITICAL: Medication Storage - {storage_id}"
description = " | ".join(alerts)
link = f"https://hospital-pharmacy.com/storage/{storage_id}"
aepiot_url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
# Critical alert to pharmacy staff
self.critical_pharmacy_alert(aepiot_url, storage_id)
return aepiot_url
return None
def generate_patient_reference_id(self, patient_internal_id):
"""Generate non-reversible reference ID"""
# Generate secure random reference
salt = secrets.token_hex(16)
combined = f"{patient_internal_id}_{salt}_{datetime.now().isoformat()}"
reference_id = hashlib.sha256(combined.encode()).hexdigest()[:16]
# Store mapping securely (use encrypted database)
self.store_secure_mapping(reference_id, patient_internal_id)
return reference_idEnd of Part 3
This completes industry-specific applications. The document continues in Part 4 with scaling strategies, performance optimization, and future evolution.
