Railway transportation of passengers and goods is an essential gear to keep the engine

of our urbanized society running. Safety and reliability are core aspects and can only

be enabled by meticulous infrastructure maintenance. Currently, this is not given in

all aspects as track infrastructure monitoring is mainly conducted by combining two

methods: 1) partially a frequent superficial monitoring by employees, and 2) an

occasional, precise monitoring using cost-intensive measuring vehicles. Increasing the

precision and frequency of infrastructure monitoring is not reasonable (time and

money) with the current methods. This issue has also been raised by FFG in the call

VIF 2017. Our company has been awarded funding and has successfully completed a

detailed analysis and solution proposal in cooperation with the Austrian Federal

Railways (ÖBB) in the study KOMBI (Kontinuierliches Onboard Monitoring der Bahn-

Infrastruktur).

The HARMONY project aims to develop an intelligent on-board monitoring system

mountable on regular trains to support the operator’s staff in decision making in

relation to immediately necessary maintenance work and eventually consequential

operational constraints. The design of this system draws upon the results of KOMBI

allowing a high-frequency and low-cost monitoring. The project outlined in this

proposal comprises of two key aspects: 1) The intelligent processing of the data

collected by the on-board system equipped with the sensors as determined in KOMBI,

and 2) gaining an in-depth understanding of human factors to increase the overall

railway system safety and analyse user acceptance for a diverse audience and the

definition of a new role in the (railway) work force: The Remote Analyst.

The first aspect aims to find answers on how to efficiently reduce and transform huge

amounts of sensor data into relevant information on potentially safety-critical

infrastructure issues in real-time and on-board a regular train prior to transmission to

a remote human operator. Solutions are needed for the selection of suitable data

analysis tools, sensor correlation methods, data interpretation and synchronisation

methods by considering economic constraints and high demands on robustness,

performance and dependability. Furthermore, the system requires a suitable design

in relation to necessary processing methods and units on-board.

The second aspect of this project aims to focus on human-machine interaction and

Human Factors Safety, investigating implications of our system on the human

workforce and its benefits to the overall railway system safety, including human

interactions. By conducting information stream design, a human performance process

and a business process analysis within an interdisciplinary team, we will define and

design a holistic solution that creates an inclusive work space for people of different

backgrounds, genders and age groups in the railway industry.

The research results from this project will provide solid groundwork upon which a

more frequent and cost-efficient condition-based railway maintenance as well as a

safer and more reliable railway operation system can be built. This system will

alleviate decision making for human operators, provides a tangible solution for

increased user acceptance and opens up novel possibilities for remote

operations/control of autonomous machines/vehicles.