Infratico builds custom sensors for bridge structural health monitoring and road pavement sensor monitoring,
including PEA Sensors for embedded monitoring of pavements.
Bridge Structural Health Monitoring
Custom sensors for bridge assets
Custom sensor hardware for bridge structural health monitoring and continuous infrastructure monitoring.
PEA Sensors
Self-powered monitoring inside smart structures
Low-cost, zero-maintenance, self-powered sensors embedded inside smart structures can self-prognosticate
damage and mechanical failure.
PEA Technical Details
Self-powered sensor capabilities.
01
Self-powered operation
Zero-maintenance, low-cost, self-powered sensors embedded inside smart structures can self-prognosticate damage and mechanical failure. Deployed sensors are designed to operate for over two decades, with early prototype deployments approaching their eighth year of operation.
02
Edge classification
The self-powered approach harvests supplemental energy from the structure under monitoring itself, without requiring direct sunlight or external power sources. Each smart sensor can optionally use Machine Learning or AI techniques to automatically classify patterns within incoming physical stimuli.
03
Continuous monitoring
With a self-powered analog electronic sensing element, local sensor memory can update without gaps caused by traditional ADC sampling limitations. Data is continuously updated at effective sampling rates above 32 ksps. Monitoring results are encrypted at rest.
04
Long-range wireless
Edge computing and local memory allow more energy to be allocated to long-range wireless communication. The system supports 10+ km line-of-sight communication, and comparable operation to a conventional 1 ksps digital acquisition setup can yield 100x savings in wireless transmit energy.
05
Wired or short-range wireless
The same sensor core can also be configured to transmit data over wires or short-range wireless technologies such as backscattering.
06
Flexible form factor
For large volume orders, the PEA sensor core can be manufactured on a custom silicon die with a package size under 5 x 5 mm2. Infratico has prototypes for common built-environment monitoring applications, including a wireless H-gauge strain sensor for embedded pavement monitoring over 20+ years.
Tough-condition deployments
Installed from South America to Alaska.
Quick installation takes only a few minutes per sensor. The sensors are built for tough conditions and have
been installed from South America to Alaska.
Operational Lifespan
25 years
Wireless Range
50 km line-of-sight
Sensitivity (Strain)
5-12000 microstrain
Effective Sampling
64 ksps
Sensitivity (Acceleration)
0.005-32 g
Local Data Storage
1,000 days
Automated Drone Inspection
Autonomous inspection and mapping.
Custom AI-powered drone systems perform long-range mapping, surveying, and corridor mapping for pavements,
bridges, and other infrastructure assets.
Long-range mapping, surveying, and corridor mapping for pavements, bridges, and other infrastructure assets.
Autonomous drones self-fly and navigate in and around bridges and other infrastructure without relying on manual flight paths.
High-resolution scans, NDT support, 3D models, digital twins, finite element analysis, and predictive maintenance planning.
Weigh-in-Motion
Moving load measurement.
Infratico weigh-in-motion systems measure moving loads across a wide range of asset and vehicle types, from
bicycles to the largest commercial aircraft.
The system captures weight data without requiring the vehicle to stop.
Vehicles can remain in motion at speeds up to 60 km/h.
Supports operational awareness and data-driven asset management.
Environmental Monitoring
Conditions around the asset.
Infratico supports environmental monitoring for asset conditions such as temperature, humidity, and related
surrounding conditions.
Infratico Intelligence Platform
Cloud monitoring and anomaly detection.
The Infratico Intelligence Platform brings real-time sensor and asset data into a secure, web-based cloud
environment for continuous infrastructure monitoring.
Real-time sensor and asset data in a secure, web-based cloud environment.
Artificial intelligence, traditional structural analysis techniques, and custom anomaly detection methods.
