Objectives of the service
The objective is to create a complex platform for digital, continuous, and automatic monitoring of transport infrastructure (TI), conditions of road, rail, and inland waterways and their respective nearby corridors. The product uses a 3D Ultra HD infrastructure model to create a TI Digital Shadow, and advanced algorithms to keep it up to date by fusing all available data, including vehicle sensor data, vehicle dashcam imagery, satellite EO imagery, or InSAR data. The product supports the identification of problems, potentially risky locations, or hazardous elements and reports these findings to the operational maintenance centre of a relevant TI operator in order to timely and precisely target TI inspection and scheduling. Customers gain a powerful tool for identifying, analysing and specifying currently problematic as well as potentially risky areas of TI elements.
The first phase was the Feasibility study activity. The goal of the Feasibility study was to verify whether the intended innovative product is an effective solution to meet the needs of TI operators for assessing the condition of their infrastructure more effectively and at a lower cost than currently possible. The feasibility study confirms genuine market interest in a unified transport infrastructure monitoring solution. While a wide, EO-only-based monitoring service is impractical under current market conditions, a pragmatic hybrid model – prioritizing low-cost ground sensors with satellite PNT, treating satellite and InSAR data as optional enrichments, and adapting object categories and location-context rules to each customer's specific mix of pain points and available data – provides a grounded, flexible foundation for future transport infrastructure monitoring, provided value for customers is validated segment by segment, use case by use case rather than assumed at the market level.
Users and their needs
Key customers are transport infrastructure (TI) owners and operators, highway & motorway operators, rail track operators, and inland waterways operators. They are all facing similar problems, drawbacks, and limitations in the efficiency of their day-to-day monitoring operations. Most often, it is reactive and inefficient maintenance; delayed and costly detection of defects on TI; ineffective or non-existent automated TI cataloguing (including technical inventory); expensive in-situ & in-person inspections dealing with the human factor and lack of personnel.
Another group of needs is dealing with data management, processing automation, and generation of useful information with context and in time series.
It’s all about the responsibility for a large network of infrastructure that needs to be maintained and kept in 100% condition but with limited resources.
The primary user needs analysis was conducted in cooperation with Czech TI, however, the product is applicable on (at least) a European scale, while all TI operators are facing similar problems.
Service/ system concept
The PathWatch system architecture is structured as a cloud-based or on-prem TI Digital Shadow framework that utilizes inputs from various external sensing systems to keep the TI Digital Shadow up to date and bring fast, reliable user insights presented through the PathWatch web user interface, by alerts, reports, and exported into the operators' own Infrastructure Asset Management Systems.
Primary detection and the related sensor data pre-processing can be performed by subsystems/services that can stand outside PathWatch or in separate PathWatch modules: satellite Earth Observation (regardless of sensors used), vehicle dashcam video processing (edge processing/batch post-processing), HD mobile-mapping with LiDAR and High-resolution cameras, and other sensor platforms operate their own acquisition and processing chains and deliver primary “Observations”, which form the input into the system.
PathWatch ingests these Observations, taking into account their accuracy, quality, and reliability, and maintains a Transport Infrastructure Digital Shadow with all recognized Objects linked to the transport infrastructure segments. The TI Digital Shadow has two parts: (1) a Reference Frame — the static reference TI Network Model and Areas of Interest (AOI) Layer, which changes only infrequently — and (2) the Monitored Object Layers, one per object category, holding the dynamic digital representations of physical objects or phenomena whose state is tracked and therefore changes over time. Systems maintain the overall state, position, quality, reliability, and precision of information about every monitored object combined from all related Observations. When a monitored phenomenon crosses the customer-defined rules, the system generates a new record in the “Findings” database and reports it through alerts, notifications, event logs, dashboards, and above all through API exports into the operator's Infrastructure Asset Management System (IAMS). Rules can be set to report situations like changes of state to damaged, missing, new (pothole, traffic sign), increased risk level for landslides, treefalls, greenery encroachment. For each location and type of issue, a different level of confidence can be set. This approach reduces the risk of false positive detections by utilizing synergy between various data sources.
The proposed technical scheme and possible interface specifications can be found in the following diagram.
Space Added Value
By leveraging sensor data from vehicle fleets, EO (Copernicus and other commercial providers) and other sensor and context data sources, combined with GNSS (including Galileo) positioning information, the product provides near high frequency TI condition awareness, enabling prompt reactions to sudden changes and improved information (and evidence-based) decision-making. This allows agile and timely response to emergencies, traffic disruptions, or any other critical event affecting TI. GNSS positioning is utilised for cataloguing and/or pre-selection of areas of interest, is crucial part of detection and localization technologies and for ad-hoc maintenance. EO represents a significant innovation with respect to what is the industry standard today, and the rapidly increasing availability and accessibility of the data has the potential to replace many in-situ measurements and thus contribute to maintenance cost savings.
Current Status
Intensive and broad discussions with users were held. Together, 4 face-to-face analytical sessions were conducted, collecting 111 user requirements (UR) in total. These URs were identified amongst the rail, highway, and waterway TI operators. URs are structurally collected in the database user register and distinguished into 5 categories: Monitoring activities; Process/workflow; Data; Integration into operational systems; Budget and costs.
This UR register is a very unique collection of insights from a broad variety of employees and experts that are working on a day-to-day basis on the maintenance of the TI.
Following the UR collection, a selected set of 6 representative use cases that reflect the most relevant and recurring operational needs was prepared. These illustrate the potential applications of the proposed concept. All these use cases are evaluated from the perspective of data and processing algorithm needs, technical limitations of resources, and system architecture is proposed, including analysis of existing promising solutions. Finally, the PoC (Proof of Concept) consisted of the development of an interactive PathWatch web mapping portal integrating representative data sources and user requirements in order to validate the technical feasibility, user relevance and operational applicability of the proposed service concept. The PoC evaluated user experience, multi-sensor data ingestion workflows, and operational assumptions across three representative pilot areas: the Volary Rail and Road Corridor, the Ústí nad Labem Waterway Corridor, and the Ostrava Flood Event. PoC testing visually proved that EO assets cannot replace high-resolution ground vehicle sensors for micro-asset detailing due to physical resolution constraints. Low-cost vehicle dashcams, high-precision vehicle/train mounted optical cameras and LiDAR drive primary commercial value by delivering the required spatial detail at lower operational costs per kilometer. EO is at this point positioned as a complementary tool for broad-area screening and for high-level overview.
Beyond these specific findings, the PoC also validated the broader technical premise underlying the envisioned PathWatch platform: a modular, multi-source architecture leveraging PNT, capable of ingesting and fusing diverse sensor types using satellite positioning information — vehicle cameras, LiDAR, and satellite imagery alike — within a single platform with TI Digital Shadow in the heart. This flexibility positions the concept for progressive expansion, allowing additional data sources (e.g., InSAR, third-party fleet sensors) to be incorporated as they become commercially and technically viable, without requiring a redesign of the underlying architecture.
Prime Contractor(s)
