Governments are increasingly eager to address the escalating maintenance needs of aging critical infrastructure, including rail, bridges, mines, dams, and older buildings. Safety concerns, amplified by disastrous incidents like the 2018 Morandi Bridge collapse, which resulted in 43 casualties and a staggering US$450 million in damages, have sparked a preference for “predictive maintenance” over “maintenance after failure” approaches.
The surge in extreme weather events linked to climate change has also laid bare additional vulnerabilities in aging and strained post-war infrastructure. A greater variety of sensor and connectivity types alongside more advanced data analytics software platforms is enabling the Structural Health Monitoring (SHM) market to expand.
ABI Research says SHM sensors will reach 22.9 million connections by 2030, with a CAGR of 18% for wired retrofitted sensors and 28% for wireless retrofitted sensors.
“The greater variety of IoT sensor hardware has made it much easier for asset owners to integrate sensors into their operations, shifting away from expensive and bulky implementations to lower cost and easy-to-install solutions,” says Maryam Zafar, IoT markets analyst at ABI Research.
“Vendors are increasingly investing in software and analytics platforms to extract meaningful information from large volumes of data. Enhanced software intelligence is key, offering actionable information that adds significant value and enables more efficient predictive maintenance.” Maryam Zafar
Innovation is happening on two fronts in the SHM market. First, it is happening on the hardware edge with a shift to smaller data loggers and DAQs, greater edge processing capabilities, and a more extensive variety of sensors and technologies.
Second, it is happening with the software. Many companies seek an analytics platform, often compatible with other third-party sensors. Vendors also want to see how Artificial Intelligence (AI) can improve predictive capabilities and generate more value for asset owners and managers.
One of the biggest markets for SHM is the rail industry, as demand for rail transport is expected to double in the next two decades.
As demand for passenger and freight travel increases, so does the need to prevent delays. By digitizing rail infrastructure and monitoring critical areas of concern, such as rail tracks, switches, and slopes, rail operators know when failures will happen and can implement more efficient predictive maintenance strategies. Wireless sensor technology is essential here.
“The lack of awareness in this market combined with expensive technologies means that this market has hitherto seen low penetration. New technologies should change this, shifting from end-of-life maintenance to solutions designed into projects,” says Zafar.
“Technology vendors should ensure they are taking advantage of new technology opportunities and understand how they should position themselves to target the great variety of markets within the SHM ecosystem,” she concluded.
Eugen Boglaru is an AI aficionado covering the fascinating and rapidly advancing field of Artificial Intelligence. From machine learning breakthroughs to ethical considerations, Eugen provides readers with a deep dive into the world of AI, demystifying complex concepts and exploring the transformative impact of intelligent technologies.
