21.2 Self-powered sensors for infrastructure monitoring

Self-powered sensors are revolutionizing infrastructure monitoring. By harnessing energy from their environment, these devices can operate autonomously for extended periods, providing crucial data on structural health without the need for battery replacements or wired power sources.

This technology enables widespread deployment of sensor networks across bridges, buildings, and other critical infrastructure. The ability to continuously monitor structural integrity enhances safety and allows for proactive maintenance, reducing costs and preventing potential failures.

Wireless Sensor Networks and Node Architecture

Fundamentals of Wireless Sensor Networks

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• Wireless sensor networks consist of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions
• Utilize multi-hop communication to transmit data between nodes and to central base stations
• Applications include environmental monitoring, industrial process control, and structural health monitoring
• Network topologies include star, mesh, and tree configurations, each offering different advantages for coverage and reliability
• Challenges involve power management, scalability, and data security in large-scale deployments

Sensor Node Components and Design

• Sensor node architecture comprises four main components: sensing unit, processing unit, communication unit, and power unit
• Sensing unit contains sensors and analog-to-digital converters (ADCs) to measure physical parameters (temperature, vibration, strain)
• Processing unit includes microcontroller or microprocessor to handle data processing and control node operations
• Communication unit consists of radio transceiver for wireless data transmission and reception
• Power unit provides energy to all components, often including energy harvesting and storage mechanisms
• Size and cost constraints influence node design, leading to miniaturization and integration of components

Low-Power Electronics and Energy Efficiency

• Low-power electronics crucial for extending battery life and enabling long-term deployment of sensor nodes
• Utilizes techniques such as dynamic voltage scaling and clock gating to reduce power consumption
• Selection of energy-efficient microcontrollers and transceivers with multiple power modes (active, sleep, deep sleep)
• Implementation of power-aware routing protocols to optimize network-wide energy consumption
• Use of low-power sensors and ADCs to minimize energy consumption during data acquisition
• Careful PCB design and component selection to reduce parasitic power losses

Data Sampling and Transmission Strategies

• Data sampling strategies balance information quality with energy consumption
• Adaptive sampling adjusts sampling rate based on detected events or changes in monitored parameters
• Compressive sensing reduces data volume by acquiring fewer measurements while maintaining signal information
• Data aggregation combines data from multiple nodes to reduce transmission overhead
• Event-driven sampling triggers data collection only when specific conditions are met
• Time synchronization protocols ensure accurate timestamping of sensor data across the network

Energy Harvesting and Management

Energy Harvesting Technologies for Sensor Nodes

• Energy-autonomous sensors utilize ambient energy sources to power their operations
• Solar energy harvesting employs photovoltaic cells to convert light into electrical energy
• Thermoelectric generators exploit temperature gradients to generate power (Seebeck effect)
• Vibration-based energy harvesting uses piezoelectric or electromagnetic transducers to convert mechanical energy
• RF energy harvesting captures electromagnetic waves from ambient radio signals
• Challenges include variability of energy sources and low power density of harvested energy

Power Management and Conversion Circuits

• Power management circuits optimize energy transfer from harvesting sources to sensor node components
• Maximum power point tracking (MPPT) algorithms ensure optimal energy extraction from sources (solar panels)
• DC-DC converters regulate voltage levels to match requirements of different node components
• Low-dropout regulators (LDOs) provide stable voltage supply with minimal power loss
• Power gating techniques disconnect unused circuit blocks to reduce standby power consumption
• Charge pumps enable voltage step-up or step-down for efficient power conversion in low-voltage systems

Energy Storage Technologies and Considerations

• Energy storage crucial for buffering harvested energy and providing power during periods of low energy availability
• Rechargeable batteries (lithium-ion, nickel-metal hydride) offer high energy density but limited cycle life
• Supercapacitors provide rapid charge/discharge capabilities and long cycle life, but lower energy density
• Hybrid systems combine batteries and supercapacitors to leverage advantages of both technologies
• Selection of storage technology depends on application requirements, environmental conditions, and harvesting characteristics
• Charge management circuits protect storage elements from overcharging and deep discharging

Energy Budgeting and Consumption Analysis

• Energy budgeting involves estimating power consumption of each node component and operation
• Power profiling tools measure actual energy consumption of sensor nodes under different operating conditions
• Energy models predict long-term energy availability based on harvesting source characteristics and historical data
• State-of-charge estimation algorithms monitor remaining energy in storage elements to inform operational decisions
• Energy-aware task scheduling allocates energy resources to critical tasks during periods of energy scarcity
• Trade-offs between data quality, sensing frequency, and network lifetime considered in energy budget optimization

Duty Cycling and Power Management Strategies

• Duty cycling reduces average power consumption by alternating between active and sleep states
• Low-power listening protocols minimize energy waste during idle listening periods in wireless communication
• Wake-up receivers allow nodes to remain in ultra-low-power sleep mode until activated by specific radio signals
• Adaptive duty cycling adjusts sleep/wake schedules based on current energy availability and application requirements
• Hierarchical network structures employ different duty cycling strategies for cluster heads and member nodes
• Cross-layer optimization techniques coordinate duty cycling across multiple protocol layers to maximize energy efficiency