Cost-Efficient and Reliable High-Capacity Infrastructure

IP Coordinator: Eleanor Simmons - Network Rail


Project title:
Intelligent Innovative Smart Maintenance of Assets by integRated Technologies

Total Project Value:
€ 16 405 562,56
from 01/09/2016 to 31/08/2019
S2R (Of H2020) co-funding:
€ 7 290 632,50
Carlo Crovetto
Complementary projects:


IN2SMART aims to contribute to the overall concept for Intelligent Asset Management based on the following three main interlinked layers:

  • Measuring and Monitoring systems to collect, process and aggregate a set of heterogeneous railway asset status data, by developing (when necessary) or applying specific monitoring systems or data diagnostic collection techniques.
  • Data management, data mining and data analytics procedures to process data from the field and from other sources by applying standard open interfaces to access heterogeneous maintenance-related data and developing analytic tools to automatic detect anomalies and predict railway assets decay towards prescriptive maintenance.
  • Decision making, maintenance strategies and execution procedures to develop a generic framework, based on the combination of traditional and data driven degradation models to pave the road for future decision support tools and systems.

IN2SMART will complement the work of the IN2RAIL lighthouse project to reach a homogeneous TRL4/5 demonstrator.

Project Structure

WP1 Project  Management

WP2 Specification, Design and Integration

The overall objective of WP2 is to coordinate the technical WPs specific objectives; to provide the specification to develop and validate the Intelligent Asset Maintenance system; to provide guidelines for the design of the whole system guiding the proper integration of its main modules represented by the RIMMS (Railway Integrated Measuring and Monitoring System), DRIMS (Dynamic Railway Information Management System )and IAMS(Intelligent Asset Management System); to start to take into considerations human factors and Human Machine Interface (HMI) aspects 

WP3 RIMMS Satellites and autonomous intelligent monitoring systems

The WP3 objective is to carry out a feasibility study that will be done in strong cooperation with In2Track project,for autonomous measuring systems based on UAV’s, satellites or unmanned/robot vehicles to monitor railway infrastructure assets and the environmental condition near them. This will be carried out with the following activities:
  • Describe the monitoring performances, determined for example in other industrial fields, of various measuring systems based on satellites, UAVs and robots implementation;
  • Identify the most key assets, according to S2R KPI, to be monitored and their related parameters and items to be measured, for which these kind of measuring system are particularly relevant;
  • Propose application cases for each of the measuring vehicles considered;
  • Select the most relevant monitoring system for each of the key assets to be monitored with autonomous system;
  • Identify post-processing methods required to monitor the relevant parameters;
  • Identify gaps that need to be overcome: normative context and security issues, technology improvement;
  • Finally, implement proof of concepts for drone and robotics monitoring systems.
  • The work carried out in this work package is a first coordinate approach among European railway networks about these autonomous monitoring systems, leading to agreed use cases. 

WP4 RIMMS Track and Switch & Crossings Monitoring

The objectives of this WP are:
  • To develop calibrated prototypes of integrated monitoring systems for track and Switches & Crossings which can be installed on inservice trains;
  • To identify and to validate the technology to monitor lateral and other important parameters of track geometry;
  • To develop vehicle movements modelling on S&C, complementary non-destructive testing methods and to extend recording capabilities and processes for switch maintenance parameters.
  • To develop the technology to identify surface errors in the rail tread, which are important for degradation of track geometry and S&C’s;
  • To check that the implemented technologies are able to provide input for root cause identification and prediction of degradation and
  • To point out the benefit of monitoring for smart and intelligent maintenance and asset management.

WP5 RIMMS Signalling and Telecommunications

The objective of this WP is to develop a framework toolset to be used by any party to develop a converter proxy for diagnostic data into a format defined by this project as an open standard IF. Collection of data could be performed using either “embedded” or “remote” monitoring solutions. Using a proxy for gathering data will reduce the risk of violating the safety case of the connected existing legacy signalling system and thus enable fast deployment. Create an in-lab demonstration of the proxy converter to conduct a proof-of-concept of the framework.

WP6 RIMMS Operations

The WP objective is to achieve an integrated solution for monitoring the trains and their impact on the infrastructure which must be standardized, easy to be installed, low cost and compliant with the maintenance process proposed by the S2R project. 

WP7 DRIMS Open Standard Interfaces

The objective of this WP is to develop a guideline for Open Standard Interfaces for Maintenance Data including models and data exchange by exploring the current state of the art concerning the acquisition, integration, fusion, transformation, distribution, and processing of data, available in various heterogeneous data sources. The goal is to implement software to demonstrate the feasibility of the developed interfaces, complementing the work done in IN2RAIL WP8 and WP9 for TMS and related Open Calls.

WP8 DRIMS Data Mining and Predictive Analytics

This WP will be  centred on the study, design and development of innovative approaches for data processing, data analysis, data correlation, data mining and logistics centred on:
  • Big Data analytics;
  • Machine learning, including anomalies detection and data clustering;
  • Process Mining;
  • Prognostics and diagnostics for degrading railway infrastructures.
This work will be structured and organised in a case-study driven way. These case-studies will concern relevant assets, whose malfunction and maintenance policies have an impact on the KPI’s targeted by the Shift2Rail program, and not included into IN2RAIL dynamic modelling activities. 

WP9 IAMS Asset Management and Decision Support

The objective of WP9 is to design and study a generic framework for the decision-making process when planning maintenance and interventions, which is an important functional block of asset management in railway infrastructures.
This framework will put solutions from DRIMS and RIMMS into a common context to establish Intelligent Asset Management Strategies (IAMS). The framework completes the processing chain from gathering data (RIMMS), extracting meaningful information and knowledge (DRIMS) by turning them into decisions.
Specific objectives of this WP include the detailed description of the framework for the IAMS process:
  • the guiding principles of predictive, risk- and condition-based, opportunistic, reliability-centred, integrative maintenance decision support
  • the "building blocks" of the IAMS process, their respective functionalities and interaction, the workflow and the flow of information within the framework.

WP10 IAMS Maintenance Execution, Work Methods and Tools

WP10 develops technologies for enhanced maintenance execution through two core tasks: Integrate




Results and Publications


DDP WP07-DEL-001 D7.1 Open Data: a review of the state-of-the-art



Dissemination and Data Management Plans, including project web site


Mid term event presentation

Presentation of IN2SMART at the mid-term event in Paris on 24 January 2018


* Please note that this/these deliverable(s) is/are undergoing S2R JU review and acceptance processes. At this stage this deliverable reflects only the author’s view and the S2R JU is not responsible for any use that may be made of the information it contains.

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Carlo Crovetto

IN2SMART Project Coordinator

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No: 730569