Wireless Strain Measurement Nodes

Wireless Strain Measurement Nodes for Remote Structural Monitoring

Strain Stress delivers advanced wireless nodes for real-time, cable-free strain tracking across infrastructure

Overview

Wireless strain measurement nodes are revolutionizing the way engineers and infrastructure professionals collect and analyse strain data. These compact, high-performance modules eliminate the need for extensive cabling by transmitting strain readings wirelessly to a centralized system. Ideal for hard-to-access or wide-area installations, wireless nodes deliver real-time structural data with minimal setup and maintenance, making them perfect for bridges, towers, machinery, and dynamic testing environments.
This webpage details the functionality, integration options, and applications of wireless strain nodes. Strain Stress, a B2B provider serving industries across North America, supports customers with scalable wireless monitoring systems that deliver accurate, low-latency strain data—even in challenging environmental conditions. Our systems help clients streamline their testing infrastructure, reduce costs, and gain actionable insights into the health and behaviour of structural assets.

Smart Monitoring Solutions Powered by Trusted Partners

In addition to offering products and systems developed by our team and trusted partners for Wireless Strain Measurement Nodes, we are proud to carry top-tier technologies from Global Advanced Operations Tek Inc. (GAO Tek Inc.) and Global Advanced Operations RFID Inc. (GAO RFID Inc.). These reliable, high-quality products and systems enhance our ability to deliver comprehensive technologies, integrations, and services you can trust. Where relevant, we have provided direct links to select products and systems from GAO Tek Inc. and GAO RFID Inc.

Core Components

Hardware Products (from GAO Tek & GAO RFID)

GAO Tek Wireless Strain Node – Long Range

Transmits strain data over several kilometres, ideal for field deployments in infrastructure and energy sectors.

GAO Tek Battery-Powered Strain Module

Offers extended battery life and easy mounting for use in remote, cable-free monitoring zones.

GAO RFID Strain Node with IoT Integration

Seamlessly connects with RFID and IoT platforms for data logging and real-time monitoring.

GAO RFID Multi-Channel Wireless DAQ Hub

Receives data from multiple wireless nodes and transmits it to cloud or local storage systems.

Software and Systems

GAO Tek Wireless Data Acquisition System

Enables real-time visualization, analysis, and recording of data from distributed wireless strain sensors.

GAO RFID Cloud Monitoring Dashboard

A web-based platform for setting thresholds, alerts, and automated reporting across multiple locations and sensors.

Key Features and Functionalities

Compatibility

Works with

Compatible sensor types

Applications

Industries We Serve

Civil and Structural Engineering

Aerospace and Defense

Oil & Gas and Energy Utilities

Transportation and Rail

Construction and Mining

Research and Development

Relevant U.S. and Canadian Industry Standards

Case Studies

Bridge Expansion Joint Monitoring – Michigan, USA
A civil engineering firm installed wireless strain measurement nodes across multiple expansion joints to monitor live-load behaviour. The system provided real-time alerts during freeze-thaw cycles, reducing inspection frequency and improving maintenance response.
An aerospace R&D centre utilized our long-range wireless nodes to gather dynamic strain data from rotating aircraft parts during wind tunnel testing. Data accuracy remained high despite rapid motion and vibration.
Wireless strain modules were embedded in post-tensioned tendons to track long-term loading in a remote hydropower facility. Data was transmitted via IoT gateway to a central dashboard, ensuring early detection of stress anomalies.

Looking to upgrade to wireless strain monitoring for your next project?

Contact Us today to consult with our engineering team, request a tailored quote, or explore how our wireless strain measurement nodes can reduce complexity and enhance structural insights.
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