Part 5: Industry-Specific Use Cases and Applications
Real-World Implementation Examples Across Different Industries
Table of Contents - Part 5
- Smart Manufacturing and Industrial IoT
- Smart Building and Facility Management
- Healthcare and Medical IoT
- Agriculture and Environmental Monitoring
- Retail and Logistics
16. Smart Manufacturing and Industrial IoT
16.1 Production Line Monitoring
Scenario: Manufacturing facility with 50+ machines requiring real-time monitoring and maintenance alerts.
Implementation:
python
class ManufacturingIoTManager:
"""Manage IoT integration for manufacturing environment"""
def __init__(self):
self.machines = {}
self.production_thresholds = {
'temperature': 85,
'vibration': 50,
'pressure': 120,
'rpm': 3000
}
def monitor_machine_health(self, machine_id, sensor_data):
"""Monitor machine health and generate alerts"""
alerts = []
# Check each sensor against threshold
for sensor_type, value in sensor_data.items():
threshold = self.production_thresholds.get(sensor_type)
if threshold and value > threshold:
alert_url = self.generate_maintenance_alert(
machine_id,
sensor_type,
value,
threshold
)
alerts.append(alert_url)
return alerts
def generate_maintenance_alert(self, machine_id, sensor_type, value, threshold):
"""Generate aePiot URL for maintenance alert"""
from urllib.parse import quote
title = quote(f"Maintenance Alert - Machine {machine_id}")
description = quote(
f"{sensor_type.title()}: {value} exceeds threshold {threshold} | "
f"Immediate inspection required"
)
link = quote(f"https://factory-dashboard.com/machines/{machine_id}/diagnostics")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
# Send to maintenance team
self.notify_maintenance_team(aepiot_url, machine_id, sensor_type)
# Generate QR code for technician
self.generate_maintenance_qr(aepiot_url, machine_id)
return aepiot_url
def generate_production_report(self, shift='day'):
"""Generate end-of-shift production report with aePiot URLs"""
from urllib.parse import quote
import json
production_data = self.get_shift_data(shift)
report_items = []
for machine_id, data in production_data.items():
title = quote(f"Production Report - Machine {machine_id} ({shift} shift)")
description = quote(
f"Units: {data['units_produced']} | "
f"Downtime: {data['downtime_minutes']}min | "
f"Efficiency: {data['efficiency']}%"
)
link = quote(f"https://factory-dashboard.com/reports/{machine_id}/{shift}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
report_items.append({
'machine_id': machine_id,
'url': aepiot_url,
'performance': data
})
# Send consolidated report to management
self.send_shift_report(report_items, shift)
return report_items
def generate_maintenance_qr(self, aepiot_url, machine_id):
"""Generate QR code for maintenance technician access"""
import qrcode
qr = qrcode.QRCode(version=1, box_size=10, border=4)
qr.add_data(aepiot_url)
qr.make(fit=True)
img = qr.make_image(fill_color="black", back_color="white")
img.save(f"maintenance_qr/machine_{machine_id}_{datetime.now().strftime('%Y%m%d_%H%M')}.png")
# Also print directly to label printer if available
# self.print_maintenance_label(img, machine_id)
return imgReal-World Benefits:
- Maintenance technicians scan QR on machine to instantly access diagnostic data
- Production managers receive daily summary URLs via email
- Quality control team tracks machine performance through aePiot URLs
- Downtime reduced by 30% through faster alert response
16.2 Supply Chain and Inventory Tracking
Implementation:
python
class SupplyChainTracker:
"""Track inventory and shipments with aePiot URLs"""
def track_shipment(self, shipment_id, current_location, iot_sensor_data):
"""Generate tracking URL for shipment"""
from urllib.parse import quote
# Extract sensor data
temperature = iot_sensor_data.get('temperature')
humidity = iot_sensor_data.get('humidity')
shock_events = iot_sensor_data.get('shock_count', 0)
title = quote(f"Shipment Tracking - {shipment_id}")
description = quote(
f"Location: {current_location} | "
f"Temp: {temperature}°F | Humidity: {humidity}% | "
f"Shock Events: {shock_events}"
)
link = quote(f"https://logistics.company.com/shipments/{shipment_id}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
# Send to customer
self.send_customer_update(aepiot_url, shipment_id)
# Check for violations
if temperature > 75 or shock_events > 2:
self.alert_logistics_team(aepiot_url, shipment_id)
return aepiot_url
def warehouse_inventory_status(self, warehouse_id):
"""Generate inventory status URLs for warehouse zones"""
from urllib.parse import quote
zones = self.get_warehouse_zones(warehouse_id)
zone_urls = []
for zone in zones:
sensor_data = self.get_zone_sensors(warehouse_id, zone['zone_id'])
title = quote(f"Inventory - {warehouse_id} Zone {zone['zone_id']}")
description = quote(
f"Items: {zone['item_count']} | "
f"Temp: {sensor_data['temperature']}°F | "
f"Occupancy: {zone['occupancy_percent']}%"
)
link = quote(f"https://warehouse.company.com/{warehouse_id}/zones/{zone['zone_id']}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
zone_urls.append({
'zone_id': zone['zone_id'],
'url': aepiot_url
})
return zone_urls17. Smart Building and Facility Management
17.1 HVAC and Environmental Control
Scenario: Office building with smart HVAC, lighting, and occupancy sensors.
Implementation:
python
class SmartBuildingManager:
"""Manage smart building IoT with aePiot integration"""
def __init__(self, building_id):
self.building_id = building_id
self.comfort_thresholds = {
'temperature_min': 68,
'temperature_max': 74,
'humidity_min': 30,
'humidity_max': 60,
'co2_max': 1000
}
def monitor_room_comfort(self, room_id, sensor_data):
"""Monitor room environmental conditions"""
from urllib.parse import quote
issues = []
# Check temperature
temp = sensor_data.get('temperature')
if temp:
if temp < self.comfort_thresholds['temperature_min']:
issues.append(f"Temperature too low: {temp}°F")
elif temp > self.comfort_thresholds['temperature_max']:
issues.append(f"Temperature too high: {temp}°F")
# Check humidity
humidity = sensor_data.get('humidity')
if humidity:
if humidity < self.comfort_thresholds['humidity_min']:
issues.append(f"Humidity too low: {humidity}%")
elif humidity > self.comfort_thresholds['humidity_max']:
issues.append(f"Humidity too high: {humidity}%")
# Check CO2
co2 = sensor_data.get('co2')
if co2 and co2 > self.comfort_thresholds['co2_max']:
issues.append(f"CO2 elevated: {co2}ppm")
# Generate alert if issues found
if issues:
title = quote(f"Environmental Alert - {self.building_id} Room {room_id}")
description = quote(" | ".join(issues))
link = quote(f"https://building-management.com/{self.building_id}/rooms/{room_id}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
# Send to facilities team
self.notify_facilities(aepiot_url, room_id, issues)
return aepiot_url
return None
def energy_consumption_report(self, period='daily'):
"""Generate energy consumption report"""
from urllib.parse import quote
consumption_data = self.get_consumption_data(period)
title = quote(f"{period.title()} Energy Report - {self.building_id}")
description = quote(
f"Total: {consumption_data['total_kwh']} kWh | "
f"HVAC: {consumption_data['hvac_percent']}% | "
f"Lighting: {consumption_data['lighting_percent']}% | "
f"Cost: ${consumption_data['cost']}"
)
link = quote(f"https://building-management.com/{self.building_id}/energy/{period}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
return aepiot_url
def occupancy_tracking(self):
"""Track building occupancy with aePiot URLs for each floor"""
from urllib.parse import quote
floors = self.get_floor_occupancy()
floor_urls = []
for floor_num, occupancy_data in floors.items():
title = quote(f"Occupancy - Floor {floor_num}")
description = quote(
f"Current: {occupancy_data['current']} people | "
f"Capacity: {occupancy_data['capacity']} | "
f"Utilization: {occupancy_data['utilization_percent']}%"
)
link = quote(f"https://building-management.com/{self.building_id}/floors/{floor_num}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
floor_urls.append({
'floor': floor_num,
'url': aepiot_url,
'data': occupancy_data
})
return floor_urls17.2 Security and Access Control
Implementation:
python
class BuildingSecurityIoT:
"""Security system integration with aePiot"""
def door_access_event(self, door_id, access_data):
"""Log door access with aePiot URL"""
from urllib.parse import quote
badge_id = access_data.get('badge_id', 'Unknown')
timestamp = access_data.get('timestamp')
access_granted = access_data.get('granted', False)
status = "Granted" if access_granted else "DENIED"
title = quote(f"Access {status} - Door {door_id}")
description = quote(
f"Badge: {badge_id} | "
f"Time: {timestamp} | "
f"Status: {status}"
)
link = quote(f"https://security.company.com/access-log/{door_id}/{timestamp}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
# If access denied, alert security
if not access_granted:
self.alert_security_team(aepiot_url, door_id, badge_id)
# Log for audit trail
self.log_access_event(aepiot_url, door_id, access_data)
return aepiot_url
def security_camera_motion(self, camera_id, motion_data):
"""Handle motion detection from security camera"""
from urllib.parse import quote
location = motion_data.get('location')
confidence = motion_data.get('confidence', 0)
timestamp = motion_data.get('timestamp')
title = quote(f"Motion Detected - Camera {camera_id}")
description = quote(
f"Location: {location} | "
f"Confidence: {confidence}% | "
f"Time: {timestamp}"
)
link = quote(f"https://security.company.com/cameras/{camera_id}/events/{timestamp}")
aepiot_url = f"https://aepiot.com/backlink.html?title={title}&description={description}&link={link}"
# High confidence motion in restricted area
if confidence > 80 and self.is_restricted_area(location):
self.alert_security_immediate(aepiot_url, camera_id)
return aepiot_url