Sentra offers IoT sensors and DAQ devices: Wireless (Tilt90, Vibration Meter, GNSS), Wired (Strain Gauges, Accelerometers), Data Loggers (Vibrating Wire, Digital RS485, PicoNode), Communications (4G Gateway, Repeater, Thread). All IP68-rated, −40°C to +80°C. Full range →
LoRaWAN range: Open terrain up to 15 km, City up to 4 km, Underground up to 2 km, Tunnel up to 4 km. 4G gateway with 3G/2G fallback. Edge variant stores data locally.
Battery life: Edge loggers up to 25 yrs, Tiltmeters 5–10 yrs, Digital loggers up to 10 yrs, GNSS up to 10 yrs. Batteries user-replaceable. Solar options available.
Yes — IP68 rated, −40°C to +85°C, surge protected (IEC61000-4-5 Class 2). Deployed in mines, tunnels, coastal bridges, deserts with minimal maintenance.
LoRaWAN, 4G LTE (3G/2G fallback), RS485 ModBus RTU, Bluetooth, Ethernet (RJ45). 128 AES encryption. Supports CMT Cloud and CMT Edge.
Single 4G Gateway supports 1,000+ devices. Cloud: 300 msg/min. Edge: 30 msg/min. Ideal for dams, city-wide bridge networks, mine walls, multi-site assets.
Tilt90: ±0.005° accuracy. GNSS: mm-precision with RTK. Vibration: 3-axis PPV with MEMS. Factory-calibrated, auto temp compensation.
Via Mobile App (Bluetooth), USB-C, or over-the-air via CMT. No laptop needed. Maintenance: inspections + battery swap every 5–10 yrs.
Yes. Sentra sensors support open standards including MQTT, HTTP/S, and ModBus RTU, enabling integration with AWS IoT, Azure IoT Hub, ThingWorx, and custom platforms. Our REST API and webhook connectors allow real-time data forwarding to any third-party dashboard or analytics engine. For enterprise deployments, we provide integration documentation and technical support throughout the onboarding process.
Sampling rates are configurable per sensor and application: Vibration meters up to 200 Hz, Tiltmeters from 30 seconds to 24 hours, Strain gauges from 1 second to 24 hours, GNSS from 1 second (RTK) to 24 hours. Data resolution is 16–24 bit depending on the sensor type. Edge gateways apply configurable averaging, filtering, and threshold-based event recording to balance data fidelity with bandwidth and power consumption.
Structural Health Monitoring (SHM) is the continuous, real-time assessment of a structure's integrity using embedded or surface-mounted sensors. Sentra's SHM solution combines:
- High-fidelity sensors — GNSS, accelerometers, tiltmeters, vibrating wire strain gauges, crack gauges, and temperature sensors deployed at critical structural points
- Edge-enabled data acquisition — Our gateways and data loggers collect, pre-process, and securely transmit data 24/7
- Cloud analytics & AI — Machine learning models detect anomalies, trend structural behaviour, and flag conditions requiring intervention
- Real-time dashboards & alerting — Multi-tier alerts (warning, alert, critical) delivered via SMS, email, and dashboard notifications
Our SHM programmes are tailored to each structure's specific failure modes — fatigue cracking in steel bridges, differential settlement in foundations, concrete spalling in flyovers, or seepage-driven instability in dams. We start with a site survey and risk assessment, then design a bespoke instrumentation plan. Learn more about SHM →
Sentra's solutions are deployed across a wide range of industries and infrastructure asset types:
- Railway Networks — Bridges, viaducts, embankments, and track monitoring under live rail traffic
- Road Bridges & Highways — Flyovers, cable-stayed bridges, major crossings, and adjacent excavation impacts
- Buildings & High-Rise Structures — Tall structures, deep basements, and construction-induced movement
- Dams & Reservoirs — Embankment, gravity, and arch dams with seepage and deformation monitoring
- Mining — Open pit wall stability, tailings dam surveillance, and underground workings
- Ports & Marine — Wharves, jetties, and marine structures in corrosive environments
- Construction & Tunnelling — Deep excavations, TBM tunnelling, and cut-and-cover works
- Industrial Facilities — Pump houses, manufacturing plants, and critical equipment monitoring
Each sector has unique monitoring requirements — our engineers design solution packages specific to each asset type and regulatory framework. Explore all solutions →
Sentra's bridge inspection service combines traditional engineering assessment with advanced technology to deliver comprehensive condition reports:
- Drone-based aerial surveys — High-resolution visual and thermal imaging of deck surfaces, bearings, expansion joints, and superstructure elements — reaching areas inaccessible by conventional inspection
- Underwater ROV inspections — Submersible inspections of piers, pile caps, and foundations in river and marine environments
- Non-destructive testing (NDT) — Ultrasonic testing, ground-penetrating radar, and acoustic emission testing for internal defect detection
- Load rating & capacity assessment — Structural analysis against current codes and traffic loading standards
Inspections can be delivered as one-off assessments or integrated into a continuous monitoring programme. All findings are documented with photographic evidence, defect mapping, and prioritised maintenance recommendations. Learn more →
Asset monitoring uses IoT sensors to continuously track the health and performance of industrial and infrastructure equipment — pumps, motors, conveyors, transformers, and rotating machinery. Sentra's asset monitoring solution:
- Deploys vibration, temperature, pressure, flow, and power sensors on critical assets
- Transmits data via edge-processing gateways to a real-time multi-asset dashboard
- Generates composite health scores for each asset, making condition data accessible to maintenance teams
- Provides predictive failure alerts 2–4 weeks before expected failure, enabling planned intervention rather than emergency repairs
Typical outcomes include a 35% reduction in unplanned downtime, a 20–40% reduction in maintenance costs, and extended equipment lifecycle. The platform integrates with existing CMMS (Maximo, SAP PM) and SCADA systems. Learn more →
Geotechnical monitoring measures ground behaviour — settlement, lateral movement, pore water pressure, and vibration — using instruments installed in or on the ground. It is required in the following scenarios:
- Construction activities — Deep excavations, tunnelling (TBM/NATM), piling, and embankment construction where ground movement could affect adjacent structures
- Long-term infrastructure operation — Slopes, dams, mine tailings, and embankments that require permanent ground stability surveillance
- Regulatory compliance — Planning authorities frequently mandate geotechnical monitoring as a condition of consent for major projects
Sentra deploys the full range of subsurface instruments: inclinometers, piezometers, settlement sensors, tiltmeters, and seismographs — all connected via IoT data acquisition to a real-time cloud dashboard with three-tier alerting (Amber, Amber+, Red) configured against design trigger levels. Learn more →
Non-Destructive Testing (NDT) refers to inspection techniques that evaluate material properties, detect defects, and assess structural integrity without damaging the asset. Sentra's NDT capabilities include:
- Ultrasonic Testing (UT) — Detects internal flaws, corrosion thinning, and crack depth in steel and concrete structures
- Ground-Penetrating Radar (GPR) — Subsurface imaging for rebar location, void detection, and thickness assessment in concrete and pavements
- Acoustic Emission (AE) — Real-time monitoring of crack propagation and active damage mechanisms in stressed components
- Rebound Hammer & Core Testing — Concrete strength estimation and material verification
NDT is often used as part of a wider condition assessment programme, complementing long-term IoT monitoring with detailed periodic inspections. Learn more →
Fatigue is the progressive, localised structural damage that occurs when a material is subjected to repeated loading cycles — from traffic on bridges, wind on towers, or operational loads on machinery. Sentra's fatigue and residual life assessment combines:
- Continuous vibration and strain monitoring — High-frequency data capture on critical structural members subject to cyclic loading
- Rainflow cycle counting — Advanced signal processing to extract fatigue cycles from raw strain and vibration waveforms
- Damage accumulation models — Palmgren-Miner linear damage rules and S-N curve analysis based on material properties and design standards
- Remaining useful life prediction — Probabilistic models that estimate the remaining safe operating life based on actual loading history rather than design assumptions
This enables asset owners to make data-driven decisions about life extension, load restrictions, or rehabilitation timing — replacing conservative blanket replacement programmes with condition-based lifecycle management. Learn more →
Sentra's digital engineering and BIM (Building Information Modeling) services complement our monitoring solutions by providing the digital foundation for smart infrastructure management:
- LiDAR scanning & UAV photogrammetry — High-precision reality capture creating accurate as-built point clouds and 3D models
- Scan-to-BIM — Conversion of point cloud data into semantically rich BIM models (IFC-compliant) with asset tagging and metadata
- Digital twin integration — BIM models become the 3D canvas for visualising live sensor data, enabling engineers to see real-time structural behaviour in the context of the actual geometry
- Clash detection & constructability reviews — For construction-phase projects, ensuring monitoring installations do not conflict with structural elements
By integrating monitoring data with BIM, asset owners gain a complete digital record from construction through operation — supporting maintenance planning, refurbishment design, and lifecycle decision-making. Learn more →
Sentra offers a full spectrum of consulting and advisory services complementing our monitoring solutions:
- Asset risk assessments — Comprehensive evaluation of infrastructure vulnerability, failure modes, and monitoring criticality — identifying which assets need monitoring and what parameters to track
- Instrumentation strategy design — Engineering-led selection of sensor types, locations, sampling regimes, and alert thresholds tailored to each asset's specific failure mechanisms and operational context
- Specification & tender support — Technical specification writing for monitoring systems, helping asset owners procure the right solutions from contractors and integrators with clear performance criteria
- Data interpretation & forensic analysis — Expert engineering review of monitoring data, anomaly investigation, and correlation with structural inspection findings for informed decision-making
Our advisory team combines structural engineering, geotechnical, and IoT domain expertise to guide clients through every stage — from initial feasibility through to long-term data-driven asset management. Learn more →
Sentra's real-time monitoring system works through an integrated pipeline of hardware, connectivity, and analytics:
- Sensors acquire data — Each sensor type (tiltmeter, vibration meter, strain gauge, GNSS, etc.) samples readings at configurable intervals — from 30 seconds to 24 hours depending on monitoring requirements
- Edge processing — Data loggers and gateways at the site pre-process sensor readings: filtering noise, applying calibration factors, detecting threshold breaches, and compressing data for transmission
- Wireless transmission — Data is transmitted via LoRaWAN to the gateway, then via 4G LTE cellular backhaul (or Ethernet) to the cloud platform. Local data buffering prevents loss during connectivity outages (30–90 day storage capacity)
- Cloud analytics & visualisation — The Sentra cloud platform processes incoming data streams, updates live dashboards, applies AI anomaly detection models, and generates alerts when thresholds are exceeded
- Alert delivery — Multi-tier alerts (advisory, warning, critical) are delivered via SMS, email, and dashboard notifications — typically within 2 seconds of detection for critical events
All data is accessible from any device via web dashboards, with historical trend analysis, export capabilities, and role-based access controls.
Depending on your sensor configuration and monitoring objectives, you receive:
- Real-time dashboards — Live visualisation of all monitored parameters with configurable views for different stakeholders (engineers, maintenance teams, management)
- Trend analysis — Time-series plots showing structural behaviour over hours, days, months, and years — enabling identification of gradual deterioration patterns
- Anomaly detection — AI-based identification of unusual behaviour that deviates from established baselines, with engineering interpretation
- Alert notifications — Configurable multi-tier alerts delivered via SMS, email, and dashboard when thresholds are exceeded
- Monthly performance reports — Comprehensive reports including executive summaries, sensor health status, trend plots, identified anomalies, and prioritised maintenance recommendations
- Data exports — CSV, JSON, and API access to raw and processed data for integration with your existing asset management or SCADA systems
Our alerting system is designed to deliver actionable intelligence without overwhelming operators with false alarms:
- Three-tier alert levels — Advisory (monitoring readings approach expected values, review recommended), Warning (readings approach design limit state, action required), Critical (readings at or exceeding design limits, immediate response required)
- Multiple delivery channels — SMS, email, dashboard notifications, and API webhooks for integration with your internal alerting systems
- Configurable thresholds — Alert thresholds are set based on structural design limits, geotechnical trigger levels, and operational parameters specific to your asset
- Alert escalation — Unacknowledged critical alerts can be automatically escalated to additional team members after a configurable timeout
- Audit trail — All alerts are logged with timestamps, acknowledgment records, and response actions for compliance and post-event analysis
Alert fatigue is actively managed through baseline tuning during the commissioning period and ongoing model refinement. Our engineers work with your team to calibrate thresholds that minimise false positives while ensuring no genuine events are missed.
Yes. All Sentra monitoring data is accessible from anywhere with an internet connection through:
- Web dashboards — Fully responsive, accessible from desktop, tablet, and mobile browsers
- CMT Cloud platform — Centralised multi-project management with role-based access controls, audit logging, and user permissions management
- API access — RESTful API for programmatic data retrieval and integration with your internal systems
- Data export — CSV and JSON export for offline analysis or integration with GIS, BIM, and CMMS platforms
For sites with connectivity constraints, our edge gateway variant stores data locally, which can be retrieved on-site or scheduled for periodic synchronisation. Data is secured end-to-end with 128 AES encryption and TLS transmission.
Sentra provides structured reporting at multiple frequencies to suit different stakeholder needs:
- Monthly performance reports — Include executive summary, sensor health and system uptime, trend plots for all monitored parameters, identified anomalies with engineering interpretation, recommended maintenance actions with prioritisation, and a downloadable CSV of key metrics
- Quarterly trend analysis reports — Deeper analysis of long-term trends, seasonal effects, and structural behaviour evolution over time — ideal for lifecycle planning and capital budget submissions
- Custom reporting — Weekly, ad-hoc, and event-specific reports available on request. Reports can be tailored for different audiences (engineering, management, regulatory)
- Regulatory compliance reports — Formatted for submission to railway safety authorities, national bridge inspection bodies, and planning departments, with full audit trail documentation
All reports are delivered in PDF format with accompanying raw data files. Real-time dashboards provide continuous visibility between report cycles, and critical alerts are delivered in real time regardless of report frequency.
Data protection is built into every layer of Sentra's monitoring ecosystem:
- End-to-end encryption — All sensor data is encrypted with 128 AES encryption at multiple levels, from the sensor node through the gateway to the application server
- Secure transmission — TLS/HTTPS protocols for all cloud communications
- Role-based access control — Granular user permissions ensure stakeholders see only the data and functions relevant to their role
- Audit logging — All access and configuration changes are logged with timestamps and user identification for compliance and forensic analysis
- Edge deployment option — For high-security environments, the CMT Edge variant keeps all data on-site within a private, isolated network with no internet dependency — data never leaves the facility
We comply with international data protection standards and can provide detailed security documentation for enterprise procurement and regulatory review processes.
All monitoring data is securely stored in the cloud with configurable retention policies:
- Unlimited retention — Raw and processed data is retained for the full duration of your monitoring programme with no auto-deletion, enabling long-term trend analysis and lifecycle studies spanning years or decades
- Tiered storage — High-resolution recent data is kept in hot storage for rapid dashboard access; older data is automatically migrated to cost-optimised archive storage with the same query and export capabilities
- Data export & backup — Full dataset exports in CSV, JSON, or API format are available on demand. Scheduled automated backups can be configured to your own storage (AWS S3, Azure Blob, on-premises NAS)
- Historical replay — The dashboard supports replaying historical data to visualise structural behaviour at any past point in time — useful for forensic analysis, claims investigation, and compliance audits
A Digital Twin is a dynamic, real-time virtual replica of a physical asset — bridge, building, dam, tunnel, or industrial facility — that mirrors its current condition, behaviour, and performance. Sentra creates and maintains Digital Twins by:
- Integrating IoT sensor streams — Live data from tiltmeters, strain gauges, accelerometers, GNSS, and environmental sensors is continuously fed into the digital model
- Combining with BIM and GIS data — 3D BIM models provide the structural geometry and metadata, while GIS provides spatial context and geolocation
- Enabling predictive simulations — Engineers can run "what-if" scenarios on the Digital Twin: simulate a 100-year flood on a dam, a seismic event on a bridge, or a loading change on a building — and see the predicted structural response before it happens in the real world
- Visualising real-time data in 3D — Sensor readings are overlaid on the 3D model with colour-coded health indicators, making complex multi-sensor data instantly understandable
The result is a living digital record that supports condition-based maintenance, rehabilitation planning, emergency response simulation, and lifecycle optimisation. Learn more →
Yes. Sentra's platform is designed for integration with leading enterprise systems:
- CMMS (Computerised Maintenance Management Systems) — Integration with Maximo, SAP PM, Infor EAM, and other CMMS platforms. Monitoring alerts can automatically create work orders, and maintenance records can be correlated with sensor data in the dashboard
- SCADA (Supervisory Control and Data Acquisition) — Data exports via OPC-UA, ModBus TCP, and REST API for integration with existing SCADA and process control systems
- BIM (Building Information Modelling) — IFC-compliant model integration, enabling sensor data visualisation within the 3D BIM context
- GIS (Geographic Information Systems) — Geospatial data integration for mapping sensor networks across large asset portfolios
- ERP (Enterprise Resource Planning) — Data feeds for capital planning, asset valuation, and lifecycle cost analysis
Custom integration with non-standard platforms is available through our engineering team. We provide API documentation and technical support throughout the integration process.
Edge computing is a core component of Sentra's architecture, bringing intelligence and processing power directly to the deployment site:
- Local data processing — Our edge gateways and data loggers filter noise, compress data streams, apply calibration factors, and detect threshold breaches on-site — without requiring cloud connectivity for basic operations
- Real-time local alerts — Critical threshold alerts can trigger local alarms and actions (e.g., activating warning beacons or shutting down equipment) with sub-second latency, independent of internet connectivity
- Data buffering — Edge devices store 30–90 days of sensor data locally, ensuring no data is lost during connectivity outages. When connection is restored, buffered data is automatically synchronised to the cloud
- Reduced bandwidth and cloud costs — By processing and compressing data at the edge, only meaningful insights and alerts are transmitted to the cloud — reducing cellular data costs and cloud storage requirements
Edge computing is particularly valuable for remote, underground, or bandwidth-constrained sites where continuous cloud connectivity cannot be guaranteed.
Sentra offers two complementary management platforms to suit different deployment architectures:
- CMT Edge — Local network management software installed on-site at the gateway level. Best for private, isolated deployments where data must stay within a secure local network (military sites, sensitive infrastructure, facilities with strict data sovereignty requirements). Handles up to 30 messages/min per gateway.
- CMT Cloud — Centralised multi-project, multi-gateway management accessible from anywhere. Provides consolidated dashboards across all monitored sites, role-based user management, automated reporting, and API access. Handles up to 300 messages/min per gateway.
Many organisations use a hybrid approach: edge processing for real-time local operations and alerting, with cloud synchronisation for centralised reporting, long-term data storage, and multi-site visibility. The choice depends on your security requirements, data governance policies, and operational workflow.
Yes. Sentra supports integration with leading GIS platforms to provide geospatial context for your monitoring data:
- Geo-tagged sensors — Every sensor deployed is geo-tagged with precise coordinates, enabling spatial visualisation of your entire monitoring network on a map
- GIS data export — Monitoring data can be exported in GIS-compatible formats (GeoJSON, Shapefile, KML) for direct import into ArcGIS, QGIS, or other mapping platforms
- Web map visualisation — Our cloud dashboard includes interactive map views showing sensor locations with colour-coded status indicators and pop-up data panels
- Integration workflows — GIS teams can overlay sensor data with land parcels, utility networks, zoning maps, and environmental data to support spatial analysis and decision-making
This integration is particularly valuable for large-scale infrastructure portfolios such as railway networks, city-wide bridge programmes, and pipeline corridors where understanding the spatial relationship between monitored assets is essential.
A Digital Twin is not a static model — it evolves continuously as the physical asset ages, undergoes changes, and accumulates monitoring data:
- Continuous data enrichment — Every sensor reading, inspection report, and maintenance action adds new data to the Digital Twin, building an increasingly accurate picture of the asset's behaviour over time
- Baseline evolution — AI models in the Digital Twin learn the asset's normal behaviour patterns and update these baselines as the structure responds to seasons, traffic patterns, and environmental changes
- Model calibration — Finite element models within the Digital Twin are calibrated against real monitoring data, improving the accuracy of predictive simulations over years of operational data
- Asset modifications — When structural modifications, repairs, or upgrades are made, the Digital Twin is updated to reflect the new as-built condition, maintaining a complete lifecycle record
- Historical replay — Engineers can "rewind" the Digital Twin to see structural behaviour at any point in its history — supporting forensic analysis of events, claims investigation, and long-term trend studies
Over time, the Digital Twin becomes the single source of truth for the asset — eliminating the fragmented paper records, disparate spreadsheets, and disconnected databases that traditionally hinder infrastructure lifecycle management.
No specialised software is required. The Digital Twin is accessible through standard web browsers on desktop, tablet, and mobile devices. Key access points include:
- Web dashboard — Full Digital Twin visualisation with 3D model viewer, live sensor data overlays, and interactive navigation — works in Chrome, Firefox, Edge, and Safari without plugins
- Mobile responsive — The dashboard adapts to mobile screens for field access, allowing engineers on-site to view real-time data alongside the physical asset
- BIM authoring tools — For teams that need to modify the underlying BIM model, standard tools such as Autodesk Revit, Navisworks, or open-source IFC-compatible viewers can be used alongside our platform
- API & data feeds — Raw monitoring data and model metadata are accessible via REST API for integration with your existing engineering software ecosystem
Deployment timelines depend on project scope, site complexity, and the number of sensors involved:
- Small-scale pilot (5–15 sensors) — Typically 2–4 weeks from site survey to live dashboard, including installation, data integration, baseline collection, and alert configuration
- Standard deployment (20–50 sensors) — Typically 4–8 weeks covering asset inventory, sensor selection, installation, data integration, threshold tuning, and team training
- Large-scale enterprise (100+ sensors across multiple sites) — Phased deployment over 8–16 weeks, with each phase delivering measurable value before moving to the next site
We provide a detailed project schedule before commencing work, with defined milestones, deliverables, and acceptance criteria. The process follows six structured steps: site survey → instrumentation design → installation → data collection → analytics setup → reporting and handover.
Yes. Every monitoring deployment includes:
- Professional installation — Our certified engineers handle all installation — sensor mounting, borehole instrumentation, gateway deployment, network configuration, and system calibration. We work to minimise disruption to operational structures and traffic, and adhere to all site safety requirements
- Commissioning and testing — Full system testing, baseline data collection, and alert threshold configuration before handover
- Operator training — Hands-on training for your team covering dashboard navigation, alert response protocols, data interpretation, and basic troubleshooting. Training is tailored to your team's technical background
- Documentation — Complete as-built documentation, system manuals, and maintenance schedules provided at handover
For ongoing support, we offer annual maintenance agreements that include system health checks, sensor recalibration, software updates, and priority technical support. Our engineering team is available 24/7 for critical issues.
We recommend starting with a free technical consultation and site assessment. Our engineers will:
- Review your infrastructure goals, risk factors, and monitoring objectives
- Assess site conditions, accessibility, power availability, and connectivity options
- Identify the critical failure modes for your specific asset type
- Recommend the right combination of sensors, data loggers, gateways, and analytics — tailored to your asset type, scale, and budget
- Provide a modular proposal with optional pilot phase for validation before full deployment
Every Sentra solution is customised — we don't sell off-the-shelf packages. Whether you need real-time structural alerts, long-term trend monitoring, asset health dashboards, or a full digital twin, our team designs the monitoring programme around your specific requirements. Request a consultation →
Absolutely. Custom solution design is at the core of Sentra's approach. Every monitoring programme is customised to your specific requirements:
- Sensor selection — We select from our full portfolio of sensors based on the specific failure modes, environmental conditions, and accuracy requirements of your asset
- Sampling and configuration — Sampling rates (from 30 seconds to 24 hours), reporting intervals, alert thresholds, and operational modes are configured to match your project needs
- Analytics and reporting — Dashboard layouts, report formats, alert delivery channels, and data export schemas can be customised for your team's workflow
- Integration — Custom API development and system integration with your existing enterprise platforms (CMMS, SCADA, GIS, BIM) are available through our engineering team
- Hybrid architectures — Edge-only, cloud-only, or hybrid deployments to match your security and data governance requirements
Our process is: site survey → risk and scope definition → modular proposal → optional pilot → full deployment. Custom packages include all documentation, test plans, and handover training.
Our edge-first architecture ensures monitoring continues without interruption during connectivity outages:
- Local data buffering — Edge data loggers and gateways have local storage capacity for 30–90 days of sensor data (depending on sampling rates and sensor count). All data continues to be collected and stored locally during the outage
- Automatic synchronisation — When connectivity is restored, buffered data is automatically synchronised to the cloud in chronological order — no manual intervention required
- Local alert processing — Critical threshold alerts on the edge unit continue to operate independently of cloud connectivity. Local alarms, indicator lights, and relay outputs can be configured for immediate on-site warning
- Battery-backed operation — Gateway power backup ensures continued operation during mains power failures as well as network outages
This architecture is specifically designed for remote, underground, and high-security sites where continuous cloud connectivity cannot be guaranteed. Your data is never lost, and critical alerts are never missed — regardless of network conditions.
Sentra's monitoring systems are engineered for decades of reliable unattended operation. Key reliability measures include:
- Industrial-grade hardware — IP68-rated enclosures, wide temperature range (−40°C to +85°C), surge protection, and corrosion-resistant materials selected for the specific deployment environment
- Redundant communication paths — 4G cellular with 3G/2G fallback, local data buffering, and optional Ethernet backup ensure data continuity
- System health monitoring — The platform continuously monitors sensor health, battery levels, signal strength, and gateway status. Health alerts are generated before any device fails, enabling proactive maintenance
- Remote diagnostics — Our support team can remotely diagnose issues, push configuration updates, and resolve most problems without a site visit
- Annual system audits — Under our maintenance agreements, we perform annual system health checks, sensor calibration verification, and firmware updates to ensure ongoing optimal performance
Our systems typically achieve >99.5% availability, and we provide SLAs for response times and system uptime as part of enterprise contracts. With user-replaceable batteries and modular component design, key maintenance actions can be performed without specialised tools or extended downtime.
All Sentra hardware comes with a comprehensive warranty and support package:
- Standard warranty — All sensors, data loggers, and gateways include a 3-year hardware warranty against manufacturing defects and premature failure under normal operating conditions
- Extended warranty — Optional 5-year and 7-year extended warranty plans available at the time of purchase, covering parts and labour for the full duration
- Technical support — Phone and email support during business hours included with all deployments. Enterprise SLAs offer 24/7 priority support with 2-hour response for critical issues
- Firmware updates — Free firmware and software updates for the life of the product, including security patches, performance enhancements, and new feature releases
- Replacement policy — Advance replacement available for critical sensors under warranty, minimising downtime by shipping a replacement unit before the failed unit is returned
Smart infrastructure refers to physical assets — bridges, roads, dams, buildings, railways, and utilities — that are augmented with IoT sensors, connectivity, and data analytics to monitor their own condition, performance, and environment in real time. IoT enables smart infrastructure by providing:
- Continuous sensing — Wireless tiltmeters, vibration sensors, strain gauges, and environmental sensors capture structural behaviour data 24/7 without human intervention
- Real-time data transmission — LoRaWAN and 4G gateways transmit sensor data to cloud platforms, enabling instant visibility into asset health across entire portfolios
- Intelligent analytics — AI and machine learning models process incoming data streams to detect anomalies, predict deterioration, and generate actionable alerts before failures occur
- Digital integration — Sensor data integrates with BIM, GIS, and asset management systems to create a unified digital view of infrastructure performance
Sentra's IoT platform transforms traditional civil assets into smart, self-aware infrastructure that informs data-driven maintenance, reduces lifecycle costs, and improves public safety. Learn more about smart infrastructure monitoring →
Climate change is increasing the frequency and intensity of extreme weather events — floods, storms, heatwaves, and landslides — placing unprecedented stress on aging infrastructure. Continuous monitoring builds climate resilience in several ways:
- Early warning for weather-induced failures — Real-time monitoring of slope movement, water levels, pore pressure, and structural vibration provides early detection of slope instability, scour around bridge foundations, and flood-induced structural stress — enabling preventive action before catastrophic failure
- Post-event damage assessment — After extreme weather events, sensor data provides an immediate picture of structural condition, helping authorities prioritise inspections and reopen critical transport routes faster
- Long-term trend analysis — Continuous data over years reveals how assets respond to cumulative climate effects — accelerating deterioration rates, changing groundwater patterns, and thermal cycling impacts — informing adaptive maintenance and retrofit planning
- Design code validation — Real-world monitoring data helps engineers validate and refine climate resilience designs, ensuring new infrastructure is built to withstand future climate scenarios rather than historical baselines
Sentra's remote monitoring systems are deployed in some of the world's most climate-vulnerable regions — from cyclone-prone coastal bridges to landslide-susceptible mountain railways — providing continuous intelligence for climate-resilient infrastructure management.
Smart cities rely on interconnected data systems to optimise urban operations, improve public safety, and enhance quality of life. Infrastructure monitoring feeds critical intelligence into this ecosystem by:
- Bridge and tunnel health dashboards — City-wide sensor networks provide real-time structural health status for all major bridges, flyovers, and tunnels — allowing traffic management centres to make informed decisions about load restrictions, lane closures, and emergency rerouting
- Construction impact monitoring — In dense urban environments, monitoring surrounding buildings and ground conditions during excavation, piling, and tunnelling protects adjacent structures and provides documented compliance with regulatory vibration and settlement limits
- Integrated urban asset management — Sensor data from transport, water, and building systems can be aggregated into a single city intelligence platform — enabling holistic infrastructure lifecycle management, capital planning, and risk-based maintenance prioritisation
- Public safety alerting — Automated alert systems notify city authorities and emergency services when monitored assets approach critical thresholds, enabling proactive public safety measures such as road closures, building evacuations, or traffic diversions
Sentra's platform is designed for city-scale deployments, with a single 4G gateway supporting up to 1,000 sensors across urban infrastructure networks — providing the scalable connectivity that smart city monitoring demands.
Flooding and coastal erosion are among the most damaging climate-related threats to infrastructure. Monitoring plays a critical role in detection, early warning, and long-term protection:
- Water level and flow monitoring — IoT-enabled water level sensors, flow meters, and rain gauges provide real-time flood intelligence for rivers, drainage systems, and coastal defences — enabling early warning and controlled flood management responses
- Scour monitoring for bridge foundations — Scour (erosion of bed material around bridge piers) is the leading cause of bridge failure in flooding events. Continuous scour monitoring using sonar and vibration sensors detects dangerous foundation exposure before structural integrity is compromised
- Coastal structure monitoring — Seawalls, revetments, and breakwaters can be monitored for displacement, wave impact, and structural deterioration — providing data for maintenance planning and climate adaptation investments
- Embankment and levee monitoring — IoT sensor networks along flood defences detect internal seepage, settlement, and slope instability — providing early warning of potential breach conditions during high-water events
Sentra's wireless, battery-powered sensors are ideal for flood-prone and coastal environments where wired power and communications are impractical — with IP68 rating and long-range LoRaWAN connectivity ensuring reliable operation in harsh conditions.
Climate adaptation requires moving from reactive repair to proactive, data-driven risk management. Continuous monitoring enables asset owners to:
- Establish climate baselines — Monitor how assets respond to seasonal temperature cycles, rainfall patterns, and groundwater changes before climate effects become critical — creating baseline data against which future climate impacts can be measured
- Identify accelerating deterioration — Trend analysis over months and years reveals whether climate-driven deterioration rates are accelerating, enabling timely intervention before safety margins are eroded
- Prioritise adaptation investments — With limited budgets for climate adaptation, monitoring data helps asset owners target investments where risk is highest — rather than applying blanket upgrades across entire networks
- Validate adaptation measures — After climate resilience upgrades are implemented (e.g., scour protection, slope stabilisation, flood defences), monitoring confirms their effectiveness and provides evidence for future investment decisions
- Meet regulatory requirements — Increasingly, climate risk disclosure regulations require asset owners to demonstrate active management of climate-related physical risks. Continuous monitoring provides the auditable evidence needed for regulatory compliance and stakeholder reporting
Sentra works with infrastructure owners to design climate monitoring programmes tailored to specific asset types, climate hazards, and regulatory frameworks — from coastal bridges to mountain railways and urban drainage networks.
AI-powered predictive maintenance uses machine learning algorithms to analyse continuous sensor data and predict when infrastructure assets are likely to fail or require maintenance — shifting intervention from reactive or calendar-based schedules to condition-based, data-driven decisions. Sentra's system works through the following process:
- Data acquisition — IoT sensors (vibration, strain, tilt, temperature, environmental) collect high-frequency data from critical infrastructure assets — bridges, tunnels, dams, buildings, and industrial equipment — 24/7
- Baseline modelling — Machine learning models learn the 'normal' behaviour of each asset during an initial commissioning period — capturing how the structure responds to daily traffic patterns, temperature cycles, wind loads, and operational conditions
- Anomaly detection — The AI continuously compares incoming sensor data against learned baselines, flagging deviations that may indicate developing damage — fatigue cracking, bearing degradation, foundation settlement, or corrosion progression
- Remaining useful life prediction — Advanced models estimate the remaining safe operating life of critical components based on actual loading history, deterioration rates, and material fatigue models — enabling planned replacement before failure
- Actionable recommendations — The system generates prioritised maintenance recommendations with estimated risk levels, suggested intervention windows, and expected cost-benefit of different maintenance strategies
The result is a shift from reactive emergency repairs — which typically cost 3–5 times more than planned maintenance — to optimised, condition-based asset management that extends service life, reduces downtime, and lowers total cost of ownership.
These three maintenance strategies represent an evolution from schedule-driven to data-driven asset management:
- Preventive maintenance — Maintenance performed on a fixed calendar schedule (e.g., inspect every 6 months, replace bearings every 5 years) regardless of actual asset condition. While better than reactive maintenance, it often results in unnecessary interventions, wasted resources, and unexpected failures between scheduled intervals. Most transportation agencies still rely primarily on periodic preventive maintenance.
- Condition-based maintenance — Maintenance triggered when measured parameters (vibration levels, crack widths, tilt angles) reach predefined thresholds. This approach uses sensor data to determine when maintenance is actually needed — reducing unnecessary interventions while catching issues earlier than scheduled inspections. Condition-based maintenance requires reliable sensor data and well-calibrated threshold levels.
- Predictive maintenance — The most advanced approach, using AI and machine learning to predict when failure is likely to occur based on historical data, deterioration trends, and operational patterns. Predictive maintenance provides weeks or months of advance warning, enabling optimal planning of maintenance activities, parts procurement, and resource allocation — minimising disruption to operations.
Sentra's platform supports all three approaches, but our predictive analytics capability — combining continuous IoT data with machine learning deterioration models — delivers the highest ROI by preventing unplanned failures while optimising maintenance spend. Typical outcomes include a 35% reduction in unplanned downtime and 20–40% reduction in maintenance costs.
Machine learning (ML) significantly enhances structural health monitoring by extracting insights from complex, multi-sensor data streams that would be impossible to analyse manually. Key improvements include:
- Pattern recognition at scale — ML models process data from hundreds of sensors simultaneously, identifying subtle patterns and correlations that indicate early-stage damage — before visible signs appear. This is particularly valuable for detecting fatigue crack initiation, which traditional inspection methods often miss until cracks are well advanced
- Noise filtering and signal enhancement — In real-world environments, sensor data is contaminated by environmental noise — wind, traffic, temperature fluctuations, and operational activities. ML algorithms learn to distinguish genuine structural responses from background noise, dramatically reducing false alarms while maintaining sensitivity to real anomalies
- Adaptive baseline learning — Unlike fixed threshold systems that require manual recalibration, ML models continuously adapt their baseline understanding as the structure ages, seasons change, and usage patterns evolve — maintaining detection accuracy over years of operation without frequent manual adjustment
- Multi-modal data fusion — ML can combine data from different sensor types — tilt, strain, vibration, temperature, crack gauges — to build a holistic picture of structural health, identifying correlations across parameters that single-sensor analysis would miss
- Damage localisation and severity estimation — Advanced ML models can not only detect that something is wrong, but identify approximately where the issue is located and estimate its severity — guiding inspection teams directly to the affected area
Sentra's monitoring platform incorporates these ML capabilities as standard, with models trained on thousands of infrastructure monitoring deployments across bridges, dams, railways, and buildings worldwide.
Yes — and this is one of the most transformative applications of AI in infrastructure management. AI-powered prediction of infrastructure failures is already operational across thousands of monitored assets worldwide. Here is how it works and what it can achieve:
- Progressive deterioration prediction — For gradual failure modes such as corrosion, fatigue cracking, and settlement, AI models can predict the timeline to critical condition with remarkable accuracy — often providing 6–24 months of advance warning based on observed deterioration rates and historical data from similar assets. This allows asset owners to plan repairs during scheduled maintenance windows rather than emergency closures
- Sudden failure precursor detection — Even apparently sudden failures — such as slope collapses, bridge bearing failures, or dam instability — are often preceded by subtle precursor signals that are invisible to human inspectors but detectable by ML algorithms. Changes in micro-vibration patterns, rate of tilt, or strain correlation shifts can indicate developing instability hours or days before catastrophic failure
- Probabilistic risk assessment — Rather than binary 'safe or unsafe' outputs, AI systems provide probabilistic risk assessments — "there is a 78% probability that this slope will exceed its design threshold within the next 30 days" — enabling risk-based decision-making and proportional response
- Real-world results — In bridge monitoring applications, AI systems have demonstrated the ability to detect critical structural changes 4–8 weeks before they would become visible during routine inspections. In slope stability monitoring, early detection rates exceed 90% for failures that would otherwise cause significant disruption
Sentra's AI analytics platform is continuously refined using data from our global monitoring network, with models specifically calibrated for different asset types, geographical regions, and failure modes. While no system can predict every failure with certainty, AI dramatically reduces the element of surprise in infrastructure management. Explore Sentra's AI monitoring capabilities →
The financial case for predictive maintenance is well-established across multiple infrastructure sectors. While savings vary by asset type and current maintenance practices, typical outcomes from implementing IoT-enabled predictive maintenance include:
- 20–40% reduction in maintenance costs — By eliminating unnecessary scheduled interventions and focusing resources on assets that actually need attention, agencies significantly reduce labour, materials, and equipment costs. A railway authority monitoring 500+ bridges reported annual maintenance savings of over $2 million after implementing predictive monitoring
- 35–50% reduction in unplanned downtime — Early detection of developing issues allows maintenance to be scheduled during planned closures rather than emergency shutdowns — which typically cost 3–5 times more due to expedited mobilisation, overtime labour, and traffic disruption penalties
- Extended asset life by 15–25% — Continuous monitoring and timely intervention slow the rate of deterioration, adding years to the operational life of bridges, tunnels, and buildings. For a major bridge structure, even a 5-year life extension can represent tens of millions of dollars in deferred replacement costs
- ROI of 5:1 to 10:1 — Industry studies consistently show that predictive maintenance programmes deliver $5–10 in savings for every $1 invested in monitoring technology and analytics — making it one of the highest-return infrastructure investments available
- Insurance and liability benefits — Demonstrated active monitoring programmes can reduce infrastructure insurance premiums and provide documented due diligence in the event of third-party claims — further improving the financial case
Sentra provides detailed ROI analysis as part of our initial consultation, modelling expected savings based on your specific asset portfolio, current maintenance spend, and risk profile. Request an ROI assessment →
Bridge monitoring is one of the most impactful applications of structural health monitoring technology. Many of the world's bridges were designed for 50–100 year service lives but are now operating well beyond their original design parameters — carrying heavier traffic loads, experiencing more extreme weather, and facing accelerated deterioration. Continuous monitoring extends bridge life by:
- Early crack and fatigue detection — High-frequency vibration and strain monitoring detects fatigue crack initiation in steel bridges at the earliest possible stage — often years before cracks would become visible during routine inspections. Early detection enables small, low-cost repairs rather than major rehabilitation or emergency replacement
- Safe load capacity utilisation — Rather than imposing blanket weight restrictions based on conservative design assumptions, monitoring data provides the actual structural response to traffic loading — often demonstrating higher capacity than theoretical models predict, keeping bridges open to essential traffic longer
- Bearing and expansion joint monitoring — Bridge bearings and expansion joints are among the most maintenance-intensive components. Monitoring their movement, condition, and alignment enables targeted replacement before secondary damage occurs to the deck and substructure
- Scour and foundation monitoring — Scour around bridge piers and abutments is the leading cause of bridge failure worldwide. Continuous scour monitoring (using sonar, tilt, and vibration sensors) provides early warning of foundation exposure before structural stability is compromised — particularly during flood events
- Corrosion and environmental monitoring — In coastal and de-icing salt environments, corrosion of prestressing strands and reinforcement is a major cause of bridge deterioration. Monitoring humidity, chloride ingress, and electrochemical potential enables targeted protection before corrosion becomes structurally significant
Studies have shown that bridges with continuous monitoring programmes can have their service life extended by 15–25 years compared to bridges managed through periodic inspection alone — representing enormous savings in replacement costs and avoided traffic disruption. Explore Sentra's bridge monitoring solutions →
Dam and tailings dam safety is one of the most critical applications of infrastructure monitoring — where failure can have catastrophic human, environmental, and financial consequences. Sentra provides comprehensive monitoring solutions for both water dams and mining tailings storage facilities (TSFs):
- Deformation and settlement monitoring — GNSS receivers, tiltmeters, and inclinometers track crest settlement, downstream slope deformation, and lateral displacement with millimetre precision — detecting developing instability months before visual signs appear. For tailings dams, where catastrophic failure often results from undetected internal deformation, continuous monitoring is essential
- Seepage and pore pressure monitoring — Vibrating wire piezometers, flow meters, and water quality sensors monitor internal seepage patterns, phreatic surface levels, and pore pressure build-up — providing early warning of internal erosion (piping) and potential breach conditions
- Seismic and dynamic response monitoring — Accelerometers and seismographs capture the dam's response to seismic events, blasting, and operational vibrations — enabling post-event stability assessment and comparison against design assumptions
- Tailings beach and decant monitoring — For TSFs specifically, radar and laser level sensors monitor tailings beach levels, decant pond position, and freeboard — ensuring compliance with regulatory requirements and providing early warning of overtopping risks
- Integrated early warning systems — Multi-tier alerting (Amber, Amber+, Red) configurable against design trigger levels, with automated SMS, email, and voice call notifications to site operators, engineers, and emergency response teams
Sentra's wireless monitoring systems are ideal for dam and TSF applications, where running cables across large earth structures is impractical. Battery-powered sensors with 5–10 year deployment life and long-range LoRaWAN connectivity ensure reliable monitoring even in remote, inaccessible locations. Learn more about dam monitoring →
Railway infrastructure — tracks, embankments, bridges, tunnels, and cuttings — requires constant surveillance to ensure safe and reliable operations. IoT monitoring is transforming railway asset management by providing continuous, real-time intelligence across the entire network:
- Track geometry and alignment monitoring — IoT tiltmeters and displacement sensors installed on rails and sleepers continuously track track gauge, alignment, and cross-level — detecting deformation caused by ground movement, thermal buckling, or ballast degradation before it reaches critical limits for train safety
- Earthwork and embankment stability — Many railway embankments date from the Victorian era and were built with minimal engineering. IoT inclinometers, piezometers, and rain gauges monitor slope stability, pore water pressure, and weather conditions — providing early warning of earthwork failure that could block the line or cause derailment
- Rail bridge monitoring — Under-bridge clearance monitoring, bearing movement tracking, and structural vibration analysis ensure that bridges spanning rail corridors remain safe for both rail and road traffic above or below. High-frequency monitoring captures dynamic response to passing trains, providing fatigue loading data for remaining life assessment
- Overhead line and catenary monitoring — Tilt and vibration sensors on overhead line structures detect developing foundation movement or structural degradation that could bring down power supply cables — a leading cause of railway service disruption
- Monitoring during adjacent construction — When tunnelling, excavation, or piling occurs near active railway lines, real-time monitoring of track displacement, vibration, and settlement provides immediate alerts if construction activities affect track geometry — enabling rapid intervention to prevent service disruption
Sentra's railway monitoring solutions are deployed on networks across India and internationally, with sensors certified for trackside deployment and battery life exceeding 5 years — minimising maintenance access requirements on busy rail corridors. Explore rail monitoring →
Tunnel construction and deep excavation projects pose significant risks to adjacent structures, infrastructure services, and construction workers themselves. Comprehensive monitoring during these works is typically mandated by planning conditions and is essential for safety and risk management:
- Ground surface settlement monitoring — Automated total stations (ATS), tiltmeters, and settlement markers monitor ground surface movement above and around the tunnel alignment — detecting the characteristic settlement trough that develops ahead of and behind the tunnel face. Real-time alerts enable immediate adjustment of tunnelling parameters (face pressure, grout volume, advance rate) to control settlement within acceptable limits
- Building and structure monitoring — Tiltmeters, crack gauges, and vibration monitors on buildings above or adjacent to tunnel alignments track the impact of construction on existing structures. Prisms mounted on building facades enable 3D displacement tracking with sub-millimetre accuracy
- Vibration monitoring — Seismographs and vibration monitors at sensitive locations (heritage buildings, hospitals, laboratories, power plants) ensure vibration levels from blasting, TBM operation, or piling remain within regulatory and contractual limits — providing documented compliance data
- Groundwater and pore pressure monitoring — Piezometers and standpipes track groundwater level changes during excavation and dewatering operations — preventing excessive drawdown that could cause settlement of adjacent structures or damage to buried services
- Support system performance — Load cells, strain gauges, and convergence monitors on tunnel lining, rock bolts, shotcrete, and steel ribs verify that the temporary and permanent support systems are performing as designed — providing confidence in construction safety
Sentra provides fully integrated monitoring solutions for tunnel and excavation projects, combining traditional geotechnical instruments with IoT-enabled data acquisition for real-time visibility across the entire worksite. Learn more about construction monitoring →
Slope stability monitoring is critical for open pit mining operations, where slope failures can cause loss of life, destroy equipment, disrupt production for months, and significantly impact mine economics. Modern IoT-based slope monitoring works through a multi-layered approach:
- Real-time deformation tracking — A network of GNSS receivers deployed across the pit wall continuously tracks 3D displacement with millimetre precision — detecting accelerating deformation trends that signal impending slope failure. Unlike manual survey methods that provide daily or weekly readings, IoT GNSS delivers data every 1–15 minutes, enabling detection of rapidly accelerating failure precursors
- Tilt and crack monitoring — Wireless tiltmeters installed along tension cracks and bench crests detect localised rotational movement and crack widening — complementing GNSS data with high-sensitivity local deformation measurements that capture early-stage instability before larger-scale movement develops
- Radar and LiDAR integration — Slope stability radar (SSR) and LiDAR systems provide area-wide deformation mapping across the entire pit wall. Sentra's platform integrates data from these systems alongside point sensor data into a unified dashboard — giving geotechnical engineers a complete picture of slope behaviour
- Groundwater and pore pressure monitoring — Piezometers installed in boreholes across the pit wall track groundwater levels and pore pressure — a critical control on slope stability, particularly during heavy rainfall events. Rising pore pressure is often the trigger for slope failures in mining operations
- Alerting and action protocols — Three-tier alerting configured against geotechnical trigger levels, with automated alerts to mine controllers, geotechnical engineers, and site management. Alerts can trigger predefined action protocols — including equipment withdrawal, blast timing adjustments, or slope evacuation — based on the severity and rate of movement
Sentra's mining monitoring solutions are designed for the harsh conditions of open pit operations — dust, vibration, extreme temperatures, and limited communications infrastructure — with rugged IP68-rated sensors and long-range wireless connectivity ensuring reliable operation in the most demanding environments.
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