373 WSN and IoT Integration
373.1 Characteristics of Sensor Systems
Sensor systems encompass the complete stack from physical sensing to data interpretation, with characteristics that determine their effectiveness and applicability.
373.1.1 System-Level Characteristics
Scalability: Ability to function effectively as network size grows from tens to thousands of nodes.
Challenges: - Routing complexity increases with node count - Data aggregation and processing load - Network management and configuration - Address space and identifier management
Solutions: - Hierarchical architectures (clustering) - Scalable routing protocols (geographic, hierarchical) - Distributed data aggregation - Self-organizing capabilities
Reliability: Ensuring consistent operation despite node failures, communication errors, and environmental challenges.
Approaches: - Redundancy: Multiple sensors measuring same phenomenon - Multi-path routing: Alternative communication paths - Fault detection and recovery mechanisms - Data validation and error correction
Robustness: Operating effectively under varying conditions, interference, and unexpected events.
Techniques: - Adaptive protocols adjusting to conditions - Interference mitigation - Environmental calibration - Graceful degradation under stress
Latency: Time between event occurrence and system response or user notification.
Factors: - Sensing frequency and processing time - Multi-hop routing delays - Gateway processing and cloud transmission - Application-specific requirements (real-time vs. batch)
Accuracy and Precision: Quality of measurements and consistency of readings.
Considerations: - Sensor calibration and drift - Environmental interference - Data fusion from multiple sensors - Trade-offs with power consumption
373.1.2 Network Characteristics
Topology: Physical and logical arrangement of nodes.
Common Topologies: - Star: Nodes communicate directly with central gateway - Tree/Hierarchical: Multi-level structure with cluster heads - Mesh: Nodes form multi-hop network with multiple paths - Hybrid: Combining topologies for optimization
Density: Number of nodes per unit area.
Implications: - High density: Better coverage, redundancy, but increased interference and complexity - Low density: Energy efficient, but coverage gaps and reduced reliability
Connectivity: Degree to which nodes can communicate directly or through multi-hop paths.
Metrics: - Average node degree (number of neighbors) - Network diameter (maximum hops between nodes) - Connectivity probability
Coverage: Extent to which monitored area is sensed by nodes.
Types: - Area Coverage: Every point in region monitored by at least k sensors - Barrier Coverage: Detecting intrusions crossing monitored boundary - Point Coverage: Monitoring specific locations or targets
In multi-hop WSNs, nodes near the sink (gateway) become βhotspotsβ that relay traffic from all other nodes, depleting their batteries 10-100x faster than edge nodes. When hotspot nodes die, the entire network becomes disconnected despite most nodes having plenty of battery remaining. Prevent this by deploying multiple sinks to distribute load, use mobile sink nodes that relocate periodically, implement energy-aware routing that avoids low-battery nodes, or overprovision hotspot zones with more nodes or mains-powered relays. A 100-node agricultural WSN avoided complete failure by deploying 3 sinks instead of 1, extending network lifetime from 3 months to over 2 years.
373.1.3 Data Characteristics
Data Rates: Volume of data generated and transmitted per time unit.
Variation: - Event-driven: High rates during events, idle otherwise - Periodic: Constant sampling intervals - Query-driven: On-demand measurements
Data Aggregation: Combining data from multiple sources to reduce transmission volume and extract insights.
Techniques: - Compression: Reducing data size before transmission - Fusion: Combining readings from multiple sensors - Summarization: Statistical summaries (average, min, max, variance) - Filtering: Removing redundant or outlier data
Data Quality: Accuracy, completeness, consistency, and timeliness of collected data.
Quality Factors: - Sensor calibration and accuracy - Missing data handling - Outlier detection and correction - Timestamp synchronization
373.1.4 Security Characteristics
Threats: - Eavesdropping on wireless communications - Node capture and tampering - Denial of service attacks - False data injection - Routing attacks
Security Requirements: - Confidentiality: Protecting data from unauthorized access - Integrity: Ensuring data authenticity and preventing tampering - Authentication: Verifying node and user identities - Availability: Ensuring network remains operational
Security Mechanisms: - Encryption (AES, lightweight ciphers) - Message authentication codes (MAC) - Secure key management and distribution - Intrusion detection systems - Physical tamper resistance
373.2 WSN Deployment Sizing Guide
Practical guidance for planning WSN deployments based on application requirements:
373.2.1 Agricultural Monitoring Example
Requirements: - Field: 100 hectares (1 kmΒ²) - Sensors: Soil moisture, temperature, humidity - Coverage: 1 sensor per 50m Γ 50m grid - Lifetime: 2 years without battery replacement - Budget: $50,000
Deployment Calculation:
Area Coverage:
1,000,000 mΒ² / (50m Γ 50m per sensor) = 400 sensor nodes
Network Topology:
- 400 sensors organized into 20 clusters (20 nodes each)
- 20 cluster heads (solar-powered gateways)
- 1 main gateway with cellular uplink to cloud
Hardware Selection:
Sensor Node: Arduino + LoRa + Soil sensor
- Cost: $35/node Γ 400 = $14,000
- Battery: 2Γ AA (3000 mAh) β 2-year life at 1% duty cycle
Cluster Head: Raspberry Pi + LoRa + Solar
- Cost: $120/node Γ 20 = $2,400
- Power: Solar panel + battery (infinite lifetime)
Main Gateway: Industrial PC + 4G LTE
- Cost: $800 Γ 1 = $800
- Connectivity: $50/month Γ 24 months = $1,200
Total Cost: $14,000 + $2,400 + $800 + $1,200 = $18,400 (within budget!)
Data Flow:
400 sensors β (LoRa) β 20 cluster heads β (Wi-Fi) β Main gateway β (4G) β Cloud
Traffic: 400 sensors Γ 1 msg/10min Γ 50 bytes = 120 KB/hour β 3 MB/day
Cellular cost: 3 MB/day Γ 30 days = 90 MB/month (~$50/month)373.2.2 Industrial Monitoring Example
Requirements: - Factory: 10,000 mΒ² (single building) - Sensors: Temperature, vibration, gas detection - Coverage: 100 sensors (critical equipment monitoring) - Latency: <1 second for gas alerts - Uptime: 99.9% (mission-critical)
Deployment Calculation:
Reliability Requirements:
99.9% uptime = 8.76 hours/year downtime max
β Requires redundant architecture
Network Topology:
- 100 sensors (mains-powered, no battery constraint)
- 2 redundant gateways (active-active failover)
- Gigabit Ethernet backbone (factory LAN)
- Cloud backup (optional)
Hardware Selection:
Sensor Node: ESP32 + Zigbee + Industrial sensors
- Cost: $60/node Γ 100 = $6,000
- Power: 5V DC from factory power
- Network: Zigbee mesh (2.4 GHz)
Gateway: Dell Edge Gateway 5000 (ruggedized)
- Cost: $1,200 Γ 2 (redundancy) = $2,400
- Connectivity: Dual Ethernet (primary + backup)
- Monitoring: Automatic failover (<1 second)
Local Server: Industrial PC (on-premise data storage)
- Cost: $3,000 Γ 1 = $3,000
- Purpose: Local SCADA, no cloud dependency
Total Cost: $6,000 + $2,400 + $3,000 = $11,400
Latency Analysis:
Sensor detects gas leak β Zigbee mesh (10ms) β Gateway (5ms processing) β
Ethernet (1ms) β Local alarm system (TOTAL: <20ms) β Meets <1s requirement
No cloud dependency β 99.9% uptime achievable (only local failures, not internet)373.2.3 Sizing Rules of Thumb
| Metric | Low Density | Medium Density | High Density |
|---|---|---|---|
| Node spacing | 100m | 50m | 20m |
| Nodes per gateway | 10-20 | 50-100 | 200-500 |
| Gateway spacing | 500m (outdoor) | 50m (indoor) | 20m (dense indoor) |
| Cluster size | 5-10 nodes | 20-30 nodes | 50-100 nodes |
| Battery lifetime | 5 years (outdoor) | 2-3 years (frequent reporting) | Mains power (critical) |
373.3 Whatβs Next?
Continue your WSN journey:
- WSN Deployment Sizing: Apply WSN concepts to deployment planning
- WSN Energy Management: Optimize energy consumption
- WSN Common Mistakes: Learn from real-world failures