Tech-driven maintenance, the cornerstone to long-term structural resilience

Encardio Rite’s Arushi Bhalla details how technology is transforming structural inspection from reactive checks to data-driven oversight. She walks us through how this shift is making infrastructure safer, more resilient, and future-ready.

What tech-enabled solutions are currently available for structural inspection?
Structural inspection has entered a new era defined by precision, automation, and foresight. Advanced tools are replacing subjective assessments with objective, high-resolution data, enabling smarter and more efficient asset management. Key technological advancements include drones, remote sensing technologies like LiDAR, thermal imaging, and InSAR, which enable access to hard-to-reach zones to detect cracks, moisture intrusion, and even millimetric shifts from space. LiDAR and photogrammetry generate accurate 3D models, while thermal cameras reveal subsurface defects. InSAR tracks slow structural displacements, providing critical early warning signals for instability in bridges, dams, and slopes.

Similarly, AI and computer vision are transforming data into insights. Trained on extensive defect libraries, these systems consistently detect corrosion, cracks, or spalling, removing human variability from inspections. The next frontier is predictive AI. These models analyse historical trends, material data, sensor inputs, and environmental factors to forecast potential failure points, helping engineers act before safety is compromised. IoT-based Structural Health Monitoring (SHM) complements this with real-time data from strain gauges, accelerometers, and fibre optics. These systems alert teams when thresholds are breached and feed data into predictive engines.

For internal integrity, non-destructive tools such as ground-penetrating radar (GPR) and ultrasound can uncover rebar positions, hidden voids, and internal fractures without harming the structure.

Can you provide a real-world example of how these tech-driven inspections guarantee a higher level of accuracy?
At Bogibeel Bridge in Assam, India’s longest rail-cum-road bridge, we faced a uniquely complex challenge. Long spans, extreme winds, seismic activity, and foundation depths over 40 m demanded a monitoring strategy that could visualise problems beyond human eyes. We deployed an integrated suite of sensors, including strain gauges, tiltmeters, accelerometers, temperature sensors, and seismometers, all connected to rugged data logging systems designed for real-time use in harsh conditions. With over 900 sensors collecting continuous data, we remotely monitored every shift in load, tilt, and stress. The system delivered an unprecedented level of insight, enabling safe and uninterrupted operations without requiring physical access to the bridge. 

How are drones enabling the identification of structural faults, leaks, and other exterior damages?
Equipped with high-resolution cameras, thermal imaging, LiDAR, and other advanced sensors, drones can access hard-to-reach or hazardous areas without the need for scaffolding, shutdowns, or manual inspection. They collect detailed visual and thermal data that can reveal surface cracks, corrosion, water ingress, misalignments, or material degradation with a high level of accuracy. Our team has successfully executed a wide range of drone-enabled tasks, including pre-construction surveys, topographic mapping, and data analysis for large-scale projects, such as the Stormwater Tunnel in Dubai and along nearly the entire alignment of the Etihad Rail, spanning from the Emirate of Dubai to Fujairah, covering a total length exceeding 140 km.

Drone-based inspections, when integrated with ground-based monitoring systems, offer a comprehensive view of the structural condition. This synergy empowers asset owners and engineers to make timely, informed decisions that ensure safety and long-term resilience.

How are tools like virtual and augmented reality allowing for remote consultations and providing real-time guidance to technicians during complex repair tasks?
These technologies empower experts to remotely guide technicians through intricate procedures, reducing the need for physical presence and minimising delays, especially in hard-to-reach or high-risk areas. For example, AR enables technicians to overlay digital information, such as repair instructions, 3D models, and live sensor data, onto physical assets, providing precise, context-aware support on-site. VR creates immersive environments for training, remote inspections, and walkthroughs, enabling teams to understand and simulate scenarios before entering the field.

How is Encardio leveraging technology for the predictive maintenance of large-scale infrastructure, such as roads and bridges?
Predictive maintenance is critical for large-scale infrastructure because these assets are complex, high-investment systems that must operate safely and reliably for decades. Unlike traditional preventive maintenance, which relies on fixed schedules, predictive maintenance leverages real-time data and analytics to foresee potential failures before they occur, enabling timely interventions that prevent downtime or damage. At the Anji Khad Bridge – India’s first cable-stayed rail bridge, located in the seismically active, rugged Himalayan region – for example, Encardio implemented a comprehensive Structural Health Monitoring (SHM) system tailored for long-term performance and predictive maintenance. We deployed a wide array of precision sensors across critical components, including the deck, pylon, cables, and foundations. These included vibrating wire strain gauges, load cells, temperature sensors, tiltmeters, and displacement sensors, all connected to an automated data acquisition system. The real-time data collected was fed into a centralised platform, allowing engineers to monitor structural behaviour continuously and identify anomalies before they evolved into failures.

Can you shed some light on how “digital twin” technology enables the accurate planning of maintenance activities for bridges?
By creating a real-time, virtual replica of a physical structure, a digital twin enables engineers to visualise structural behaviour, simulate deterioration under different loads or environmental conditions, and integrate sensor data into a unified model. This has allowed for more informed and timely maintenance planning, as asset managers can pinpoint areas of concern, test interventions virtually, and prioritise repairs based on accurate, continuously updated structural insights.

For more details, visit: https://www.encardio.com/