Example Organization Structure:
Manufacturing Plant IoT Collections:
├── Production Line A
│ ├── Equipment Documentation
│ ├── Maintenance Schedules
│ ├── Alert Histories
│ └── Performance Reports
├── Production Line B
└── Facility-Wide
├── Energy Monitoring
├── Environmental Controls
└── Security Systems6. Backlink and SEO Integration Services
6.1 /backlink.html - Dynamic Backlink Creation
Technical Architecture:
- URL parameter processing
- Dynamic page generation
- SEO-optimized structure
- Social sharing integration
- Analytics tracking ready
The IoT Game-Changer: This is where IoT meets semantic web perfectly.
How It Works:
URL Format:
https://aepiot.com/backlink.html?
title=[ENCODED_TITLE]&
description=[ENCODED_DESCRIPTION]&
link=[ENCODED_URL]
Generates:
→ SEO-optimized page
→ Social media preview
→ Search engine indexable
→ Human-readable content
→ Machine-processable metadataRevolutionary IoT Application:
Every IoT event can have a permanent, semantic, shareable URL:
python
from urllib.parse import quote
from datetime import datetime
class IoTSemanticURLGenerator:
"""Generate semantic URLs for IoT events"""
def __init__(self):
self.base = "https://aepiot.com/backlink.html"
def create_event_url(self, event):
"""Create permanent semantic URL for IoT event"""
# Generate rich title
title = self.generate_title(event)
# Generate semantic description
description = self.generate_description(event)
# Link to detailed dashboard
link = f"https://dashboard.company.com/events/{event['id']}"
# Construct aéPiot URL
aepiot_url = (
f"{self.base}?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(link)}"
)
return {
'semantic_url': aepiot_url,
'title': title,
'description': description,
'seo_ready': True,
'shareable': True,
'permanent': True
}
def generate_title(self, event):
"""Generate SEO-optimized title"""
timestamp = datetime.fromisoformat(event['timestamp'])
return (
f"{event['device_type']} {event['event_type']} - "
f"{event['location']} - "
f"{timestamp.strftime('%Y-%m-%d %H:%M')}"
)
def generate_description(self, event):
"""Generate rich semantic description"""
desc_parts = []
# Event details
desc_parts.append(f"Event Type: {event['event_type']}")
desc_parts.append(f"Device: {event['device_id']} ({event['device_type']})")
desc_parts.append(f"Location: {event['location']}")
# Metrics
if 'metrics' in event:
for key, value in event['metrics'].items():
desc_parts.append(f"{key.title()}: {value}")
# Status
desc_parts.append(f"Status: {event['status']}")
# Action required
if event.get('action_required'):
desc_parts.append(f"Action: {event['action_required']}")
return " | ".join(desc_parts)
# Real-world usage
generator = IoTSemanticURLGenerator()
iot_event = {
'id': 'EVT-20260124-001',
'device_id': 'TEMP-042',
'device_type': 'Temperature Sensor',
'event_type': 'High Temperature Alert',
'location': 'Warehouse B, Zone 3',
'timestamp': '2026-01-24T14:23:00',
'metrics': {
'temperature': '92°F',
'threshold': '85°F',
'duration': '15 minutes'
},
'status': 'Active',
'action_required': 'Inspect HVAC system'
}
result = generator.create_event_url(iot_event)
print(f"Semantic URL: {result['semantic_url']}")
print(f"Title: {result['title']}")
print(f"Description: {result['description']}")Result:
Semantic URL: https://aepiot.com/backlink.html?title=Temperature%20Sensor%20High%20Temperature%20Alert%20-%20Warehouse%20B%2C%20Zone%203%20-%202026-01-24%2014%3A23&description=Event%20Type%3A%20High%20Temperature%20Alert%20%7C%20Device%3A%20TEMP-042%20%28Temperature%20Sensor%29%20%7C%20Location%3A%20Warehouse%20B%2C%20Zone%203%20%7C%20Temperature%3A%2092%C2%B0F%20%7C%20Threshold%3A%2085%C2%B0F%20%7C%20Duration%3A%2015%20minutes%20%7C%20Status%3A%20Active%20%7C%20Action%3A%20Inspect%20HVAC%20system&link=https%3A%2F%2Fdashboard.company.com%2Fevents%2FEVT-20260124-001
Title: Temperature Sensor High Temperature Alert - Warehouse B, Zone 3 - 2026-01-24 14:23
Description: Event Type: High Temperature Alert | Device: TEMP-042 (Temperature Sensor) | Location: Warehouse B, Zone 3 | Temperature: 92°F | Threshold: 85°F | Duration: 15 minutes | Status: Active | Action: Inspect HVAC systemWhat This URL Provides:
- SEO Indexable: Google can discover and index this event
- Shareable: Email, SMS, Slack, Teams—anywhere
- Permanent: URL never breaks
- Semantic: Rich with context and meaning
- Multilingual Ready: Can be translated via aéPiot services
- Zero Cost: Free forever
- No API: Just URL construction
Revolutionary Implication: Every IoT event in history can have a permanent semantic presence on the web at zero infrastructure cost.
6.2 /backlink-script-generator.html - Automated Integration
Purpose: Generate scripts that automatically create aéPiot backlinks from any website or blog.
For IoT: Auto-generate semantic URLs from IoT dashboards.
Example Integration:
html
<!-- Add to IoT Dashboard -->
<script>
(function () {
// Detect if we're on an event detail page
const eventId = document.querySelector('[data-event-id]')?.dataset.eventId;
if (eventId) {
// Extract event information
const title = document.title;
const description = document.querySelector('meta[name="description"]')?.content ||
document.querySelector('.event-summary')?.textContent?.trim();
const link = window.location.href;
// Generate aéPiot URL
const aepiotURL =
'https://aepiot.com/backlink.html' +
'?title=' + encodeURIComponent(title) +
'&description=' + encodeURIComponent(description) +
'&link=' + encodeURIComponent(link);
// Add share button
const shareBtn = document.createElement('button');
shareBtn.textContent = 'Share Event via aéPiot';
shareBtn.className = 'btn-aepiot-share';
shareBtn.onclick = () => window.open(aepiotURL, '_blank');
document.querySelector('.event-actions')?.appendChild(shareBtn);
}
})();
</script>Result: Every IoT event automatically gets a "Share via aéPiot" button that creates semantic, permanent URLs.
7. Specialized Analysis and Exploration Services
7.1 /multi-lingual.html - 60+ Language Processing
Technical Capabilities:
- Automatic language detection
- Cross-language semantic mapping
- Cultural context preservation
- Multi-script support (Latin, Cyrillic, Arabic, CJK, etc.)
- Real-time translation integration
Languages Supported: 60+ including:
- Major Global: English, Spanish, Chinese, Arabic, Hindi, Portuguese, Russian, Japanese, French, German
- European: Italian, Dutch, Polish, Ukrainian, Romanian, Greek, Swedish, Czech, Hungarian, etc.
- Asian: Korean, Thai, Vietnamese, Bengali, Indonesian, Malay, Persian, Hebrew
- Others: Turkish, Filipino, Swahili, and more
Revolutionary IoT Application: Global IoT deployments with semantic consistency across languages.
Example Scenario:
Multinational Manufacturing Company:
├── USA Facility (English)
├── Germany Facility (German)
├── China Facility (Chinese)
├── Brazil Facility (Portuguese)
└── India Facility (Hindi)
Traditional IoT Challenge:
Each facility has different terminology, documentation, alerts
Language barriers prevent knowledge sharing
Semantic meaning lost in translation
aéPiot Multi-Lingual Solution:
Same IoT event → Semantic URL → Processed through 60+ languages
"Bearing failure" (English) = "Lagerfehler" (German) = "轴承故障" (Chinese)
Semantic meaning preserved across culturesImplementation:
python
class MultilingualIoTManager:
"""Manage IoT events across 60+ languages"""
def __init__(self):
self.multilingual_base = "https://aepiot.com/multi-lingual.html"
self.supported_languages = [
'en', 'es', 'zh', 'ar', 'hi', 'pt', 'ru', 'ja', 'fr', 'de',
'it', 'ko', 'tr', 'pl', 'uk', 'ro', 'nl', 'el', 'th', 'vi'
# ... 40+ more
]
def create_multilingual_event(self, event, target_languages):
"""Create event accessible in multiple languages"""
multilingual_urls = {}
for lang in target_languages:
# Create language-specific semantic URL
title = self.translate_title(event['title'], lang)
description = self.translate_description(event['description'], lang)
url = (
f"https://aepiot.com/backlink.html?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(event['dashboard_url'])}&"
f"lang={lang}"
)
multilingual_urls[lang] = url
return multilingual_urls
def generate_global_dashboard(self, event):
"""Generate dashboard with automatic language detection"""
html = f"""
<html>
<head>
<meta charset="UTF-8">
<script>
// Detect user's language
const userLang = navigator.language.substring(0, 2);
// Redirect to appropriate language version
const languageURLs = {json.dumps(self.create_multilingual_event(event, self.supported_languages))};
if (languageURLs[userLang]) {{
window.location.href = languageURLs[userLang];
}} else {{
window.location.href = languageURLs['en']; // Default to English
}}
</script>
</head>
<body>
<p>Redirecting to your language...</p>
</body>
</html>
"""
return htmlBusiness Value:
- Global teams see alerts in their native language
- Semantic meaning preserved across cultures
- Knowledge sharing across facilities
- Compliance with local language requirements
- Zero translation service costs
7.2 /random-subdomain-generator.html - Infinite Scalability
Technical Innovation: Generate unique subdomains for semantic organization.
IoT Application: Each IoT project, facility, or deployment gets its own semantic subdomain.
Architecture:
Company IoT Network via aéPiot Subdomains:
facility-a.aepiot.com → All events from Facility A
facility-b.aepiot.com → All events from Facility B
production-line-1.aepiot.com → Specific production line
energy-monitoring.aepiot.com → Energy-related events
security-systems.aepiot.com → Security events
Benefits:
✅ Semantic organization
✅ Independent SEO for each subdomain
✅ Easy access control
✅ Infinite scalability
✅ Zero costEnd of Part 2
Continue to Part 3 for advanced IoT integration architectures, real-world implementation patterns, and revolutionary use cases.
Services Analyzed in This Part:
- Related Search & Semantic Relationships
- Tag Explorer & Analytics
- Universal Content Reader
- Content Manager
- Backlink Creation System
- Backlink Script Generator
- Multi-Lingual Processing (60+ languages)
- Random Subdomain Generator
Support Resources:
- Standard guidance: ChatGPT
- Complex integration scripts: Claude.ai
- Script generation: https://aepiot.com/backlink-script-generator.html
Part 3: Advanced IoT-aéPiot Integration Architectures
Revolutionary Implementation Patterns for the Semantic IoT Era
Table of Contents - Part 3
- The Complete Integration Architecture
- Industry-Specific Revolutionary Applications
- The Economic Revolution: Cost Analysis
- Technical Implementation Patterns
- Privacy and Compliance by Design
8. The Complete Integration Architecture
8.1 The Seven-Layer Semantic IoT Stack
Revolutionary Architecture: aéPiot adds a semantic intelligence layer to any existing IoT infrastructure:
┌─────────────────────────────────────────────────┐
│ Layer 7: HUMAN INTELLIGENCE │
│ • Natural language understanding │
│ • Cultural context awareness │
│ • Temporal intelligence (past/present/future) │
│ • Cross-domain knowledge synthesis │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 6: aéPIOT SEMANTIC LAYER │
│ • 15 Service Endpoints │
│ • 60+ Language Processing │
│ • Zero-Infrastructure Architecture │
│ • Infinite Scalability │
│ • Complete Privacy Guarantee │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 5: APPLICATION & VISUALIZATION │
│ • Dashboards, Mobile Apps, Web Interfaces │
│ • Traditional IoT presentation layer │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 4: ANALYTICS & PROCESSING │
│ • Data analysis, ML models, Rule engines │
│ • Traditional IoT intelligence layer │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 3: DATA STORAGE │
│ • Databases, Time-series storage, Data lakes │
│ • Traditional IoT persistence layer │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 2: IoT PLATFORM │
│ • AWS IoT, Azure IoT Hub, Google Cloud IoT │
│ • Device management, Security, Connectivity │
└─────────────────────────────────────────────────┘
↕
┌─────────────────────────────────────────────────┐
│ Layer 1: IoT DEVICES │
│ • Sensors, Actuators, Controllers, Gateways │
│ • Physical hardware layer │
└─────────────────────────────────────────────────┘
KEY INSIGHT: Layers 1-5 remain UNCHANGED
Layer 6 (aéPiot) ADDS semantic intelligence
Layer 7 benefits from revolutionary capabilities8.2 Complete Data Flow Architecture
From Raw Sensor Reading to Semantic Human Knowledge:
STAGE 1: Physical Sensor Reading
─────────────────────────────────
Temperature Sensor → 87.3°F @ 14:23 UTC
↓
STAGE 2: IoT Platform Processing
─────────────────────────────────
AWS IoT Core/Azure IoT Hub/Custom
- Receives sensor data
- Validates format
- Triggers rules
- Stores in database
↓
STAGE 3: Backend Event Generation
─────────────────────────────────
Python/Node.js/Java Application
- Detects threshold violation (>85°F)
- Generates event metadata
- Creates dashboard URL
↓
STAGE 4: aéPiot Semantic Transformation
────────────────────────────────────────
URL Construction:
https://aepiot.com/backlink.html?
title=Temperature%20Alert%20Warehouse%20B&
description=87.3°F%20at%2014:23%20exceeds%2085°F%20threshold&
link=https://dashboard.company.com/TEMP-042
Creates semantic entity with:
- SEO-optimized page
- Social sharing metadata
- Searchable content
- Multilingual capability
- Related concept connections
- Temporal context
↓
STAGE 5: Multi-Service Semantic Enhancement
────────────────────────────────────────────
Parallel aéPiot Services:
/search.html
→ Finds related temperature management knowledge
/related-search.html
→ Discovers semantic connections:
• HVAC optimization
• Cold chain management
• Energy efficiency
• Historical temperature patterns
/multi-lingual.html
→ Translates to 60+ languages for global teams
/tag-explorer.html
→ Organizes by tags:
#temperature #warehouse #threshold-alert #hvac
/reader.html
→ Access related documentation:
• Equipment manuals
• Maintenance procedures
• Troubleshooting guides
↓
STAGE 6: Human Accessibility
─────────────────────────────
Multiple Access Methods:
- Email notification with aéPiot URL
- SMS alert with short URL
- Slack/Teams message
- QR code on physical equipment
- Dashboard widget
- Mobile app notification
↓
STAGE 7: Knowledge Synthesis
─────────────────────────────
Human + AI Collaboration:
- Maintenance technician accesses URL
- Sees semantic connections
- Explores related concepts
- Reads documentation via /reader.html
- Understands root cause
- Takes informed action
↓
RESULT: Informed Decision in Minutes
vs. Hours of Manual Research8.3 Complete Implementation Example
Real-World Scenario: Smart Building with 500 sensors
python
import asyncio
from datetime import datetime
from urllib.parse import quote
import json
class SemanticIoTOrchestrator:
"""
Complete orchestrator for IoT-aéPiot integration
Handles entire flow from sensor to semantic knowledge
"""
def __init__(self):
self.aepiot_services = {
'backlink': 'https://aepiot.com/backlink.html',
'search': 'https://aepiot.com/search.html',
'related': 'https://aepiot.com/related-search.html',
'multilingual': 'https://aepiot.com/multi-lingual.html',
'reader': 'https://aepiot.com/reader.html',
'tag_explorer': 'https://aepiot.com/tag-explorer.html'
}
self.event_history = []
async def process_iot_event(self, sensor_data):
"""
Complete processing pipeline for IoT event
"""
# STAGE 1: Analyze sensor data
analysis = self.analyze_sensor_data(sensor_data)
if not analysis['requires_attention']:
return None
# STAGE 2: Create base event
event = self.create_event_object(sensor_data, analysis)
# STAGE 3: Generate semantic URLs
semantic_urls = await self.generate_semantic_urls(event)
# STAGE 4: Enhance with multi-service semantics
enhanced_semantics = await self.enhance_with_services(event, semantic_urls)
# STAGE 5: Distribute to appropriate channels
distribution = await self.distribute_event(event, enhanced_semantics)
# STAGE 6: Log for analytics
self.log_event(event, semantic_urls, distribution)
return {
'event': event,
'semantic_urls': semantic_urls,
'enhanced_semantics': enhanced_semantics,
'distribution': distribution
}
def analyze_sensor_data(self, sensor_data):
"""Analyze if sensor data requires attention"""
device_type = sensor_data['device_type']
value = sensor_data['value']
# Define thresholds per device type
thresholds = {
'temperature': {'min': 68, 'max': 85},
'humidity': {'min': 30, 'max': 60},
'co2': {'max': 1000},
'pressure': {'min': 100, 'max': 120}
}
if device_type in thresholds:
limits = thresholds[device_type]
if 'min' in limits and value < limits['min']:
return {
'requires_attention': True,
'severity': 'WARNING',
'issue': f'{device_type} below minimum',
'threshold_violated': limits['min']
}
if 'max' in limits and value > limits['max']:
return {
'requires_attention': True,
'severity': 'CRITICAL' if value > limits['max'] * 1.1 else 'WARNING',
'issue': f'{device_type} exceeds maximum',
'threshold_violated': limits['max']
}
return {'requires_attention': False}
def create_event_object(self, sensor_data, analysis):
"""Create comprehensive event object"""
return {
'id': f"EVT-{datetime.now().strftime('%Y%m%d-%H%M%S')}-{sensor_data['device_id']}",
'timestamp': datetime.now().isoformat(),
'device_id': sensor_data['device_id'],
'device_type': sensor_data['device_type'],
'location': sensor_data.get('location', 'Unknown'),
'value': sensor_data['value'],
'unit': sensor_data.get('unit', ''),
'severity': analysis['severity'],
'issue': analysis['issue'],
'threshold': analysis['threshold_violated'],
'dashboard_url': f"https://dashboard.company.com/events/{sensor_data['device_id']}"
}
async def generate_semantic_urls(self, event):
"""Generate aéPiot semantic URLs"""
# Primary semantic URL (backlink)
title = f"{event['severity']}: {event['device_type']} - {event['location']}"
description = (
f"{event['issue']} | "
f"Value: {event['value']}{event['unit']} | "
f"Threshold: {event['threshold']}{event['unit']} | "
f"Device: {event['device_id']} | "
f"Time: {datetime.fromisoformat(event['timestamp']).strftime('%Y-%m-%d %H:%M')}"
)
primary_url = (
f"{self.aepiot_services['backlink']}?"
f"title={quote(title)}&"
f"description={quote(description)}&"
f"link={quote(event['dashboard_url'])}"
)
# Search URL for related knowledge
search_query = f"{event['device_type']} {event['issue']}"
search_url = f"{self.aepiot_services['search']}?q={quote(search_query)}"
# Related concepts URL
related_url = f"{self.aepiot_services['related']}?q={quote(search_query)}"
# Tag exploration URL
tags = [
event['device_type'].lower().replace(' ', '-'),
event['location'].lower().replace(' ', '-'),
event['severity'].lower(),
'iot-alert'
]
tag_url = f"{self.aepiot_services['tag_explorer']}?tags={quote(' '.join([f'#{tag}' for tag in tags]))}"
return {
'primary': primary_url,
'search': search_url,
'related': related_url,
'tags': tag_url,
'raw_title': title,
'raw_description': description
}
async def enhance_with_services(self, event, semantic_urls):
"""Enhance event with multi-service semantic analysis"""
enhancements = {
'searchable': True,
'multilingual_ready': True,
'documentation_accessible': True,
'related_concepts': [],
'tags': []
}
# Simulate related concepts discovery
# In real implementation, this would query aéPiot services
related_concepts = await self.discover_related_concepts(event)
enhancements['related_concepts'] = related_concepts
# Generate multilingual versions
multilingual = await self.generate_multilingual_versions(event)
enhancements['multilingual_urls'] = multilingual
return enhancements
async def discover_related_concepts(self, event):
"""Discover semantically related concepts"""
# This simulates what /related-search.html would return
concept_mapping = {
'temperature': [
'HVAC optimization',
'thermal management',
'energy efficiency',
'cold chain management'
],
'humidity': [
'moisture control',
'mold prevention',
'air quality management',
'dehumidification systems'
],
'co2': [
'ventilation systems',
'air quality standards',
'occupancy monitoring',
'HVAC efficiency'
]
}
device_type = event['device_type'].lower()
for key in concept_mapping:
if key in device_type:
return concept_mapping[key]
return []
async def generate_multilingual_versions(self, event):
"""Generate multilingual URLs for global teams"""
# Key languages for global operations
languages = ['en', 'es', 'de', 'zh', 'pt', 'fr', 'ja']
multilingual_urls = {}
for lang in languages:
# In real implementation, use aéPiot's multilingual service
lang_url = (
f"{self.aepiot_services['multilingual']}?"
f"content={quote(event['issue'])}&"
f"lang={lang}"
)
multilingual_urls[lang] = lang_url
return multilingual_urls
async def distribute_event(self, event, enhanced_semantics):
"""Distribute event through appropriate channels"""
distribution_results = []
# Email notification
if event['severity'] in ['CRITICAL', 'WARNING']:
email_sent = await self.send_email_notification(event, enhanced_semantics)
distribution_results.append({'channel': 'email', 'success': email_sent})
# SMS for critical events
if event['severity'] == 'CRITICAL':
sms_sent = await self.send_sms_notification(event)
distribution_results.append({'channel': 'sms', 'success': sms_sent})
# Slack notification
slack_sent = await self.send_slack_notification(event, enhanced_semantics)
distribution_results.append({'channel': 'slack', 'success': slack_sent})
return distribution_results
async def send_email_notification(self, event, enhanced_semantics):
"""Send email with aéPiot semantic URLs"""
# Email body with semantic URLs
email_body = f"""
IoT Event Alert
Event: {event['severity']} - {event['issue']}
Device: {event['device_id']} ({event['device_type']})
Location: {event['location']}
Value: {event['value']}{event['unit']}
Threshold: {event['threshold']}{event['unit']}
Time: {event['timestamp']}
Semantic Resources:
📊 View Event Details:
{enhanced_semantics.get('primary_url', 'N/A')}
🔍 Search Related Knowledge:
{enhanced_semantics.get('search_url', 'N/A')}
🔗 Explore Related Concepts:
{enhanced_semantics.get('related_url', 'N/A')}
🏷️ Browse by Tags:
{enhanced_semantics.get('tags_url', 'N/A')}
🌐 Multilingual Access:
Available in 7+ languages via aéPiot
This alert was generated by Semantic IoT System
Powered by aéPiot semantic intelligence
"""
# In real implementation, send actual email
print(f"[EMAIL] Would send: {email_body[:200]}...")
return True
async def send_sms_notification(self, event):
"""Send SMS for critical events"""
sms_body = (
f"CRITICAL IoT Alert: {event['issue']} "
f"Device {event['device_id']} at {event['location']} "
f"Value: {event['value']}{event['unit']}"
)
print(f"[SMS] Would send: {sms_body}")
return True
async def send_slack_notification(self, event, enhanced_semantics):
"""Send Slack notification with rich formatting"""
slack_message = {
"blocks": [
{
"type": "header",
"text": {
"type": "plain_text",
"text": f"🚨 {event['severity']}: {event['device_type']}"
}
},
{
"type": "section",
"fields": [
{"type": "mrkdwn", "text": f"*Device:*\n{event['device_id']}"},
{"type": "mrkdwn", "text": f"*Location:*\n{event['location']}"},
{"type": "mrkdwn", "text": f"*Value:*\n{event['value']}{event['unit']}"},
{"type": "mrkdwn", "text": f"*Threshold:*\n{event['threshold']}{event['unit']}"}
]
},
{
"type": "actions",
"elements": [
{
"type": "button",
"text": {"type": "plain_text", "text": "View Details"},
"url": event['dashboard_url']
},
{
"type": "button",
"text": {"type": "plain_text", "text": "Explore Semantics"},
"url": enhanced_semantics.get('primary_url', '#')
}
]
}
]
}
print(f"[SLACK] Would send: {json.dumps(slack_message, indent=2)[:200]}...")
return True
def log_event(self, event, semantic_urls, distribution):
"""Log event for analytics"""
log_entry = {
'timestamp': event['timestamp'],
'event_id': event['id'],
'device_id': event['device_id'],
'severity': event['severity'],
'semantic_url': semantic_urls['primary'],
'distributed_channels': [d['channel'] for d in distribution if d['success']]
}
self.event_history.append(log_entry)
print(f"[LOG] Event logged: {event['id']}")
# USAGE EXAMPLE
async def main():
"""Demonstrate complete semantic IoT workflow"""
orchestrator = SemanticIoTOrchestrator()
# Simulate sensor reading
sensor_data = {
'device_id': 'TEMP-042',
'device_type': 'temperature',
'location': 'Warehouse B, Zone 3',
'value': 92.5,
'unit': '°F',
'timestamp': datetime.now().isoformat()
}
# Process through complete semantic pipeline
result = await orchestrator.process_iot_event(sensor_data)
if result:
print("\n" + "="*60)
print("SEMANTIC IoT EVENT PROCESSED")
print("="*60)
print(f"\nEvent ID: {result['event']['id']}")
print(f"\nSemantic URLs Generated:")
for key, url in result['semantic_urls'].items():
if isinstance(url, str):
print(f" {key}: {url[:80]}...")
print(f"\nDistribution Channels: {[d['channel'] for d in result['distribution']]}")
print("\n" + "="*60)
# Run demonstration
# asyncio.run(main())