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Ilmatar OIE is an open physical and digital development environment targeted for different third parties i.e. students, startups, SMEs, larger corporations or other parties, who want to innovate and develop new devices and applications that are connected to Konecranes overhead cranes. It includes a physical crane environment at premises and multiple software components to support development for industries including cranes.

The environment enables fast cyber-physical prototyping with solutions from latest research activities, being even further than current state-of-the-art industry solutions. The platform is constantly evolving, so please acknowledge that most of the components are not finalized products and may contain bugs.

Ilmatar is the nickname of the crane installed ������ Industrial Internet Campus premises in late 2016. It is a Konecranes CXT family crane with Siemens PLCs and can lift 3.2 ton loads. The serial number of Ilmatar is K16052. Further information in conference publication: accepted manuscript available at , final published version in IEEExplore:

Resources of Ilmatar OIE

Ilmatar OIE currently includes these physicalish resources:

• Physical Ilmatar crane
• The surrounding laboratory space
• The local network of the crane
• Raspberry Pi in the crane cabinet
• Siemens MindConnect Nano

Ilmatar OIE Digital resources

• OPC UA interface to the crane
  • API documentation in
• Crane.py python library
  • to read and control the crane with simple python commands
  • Available at GitHub:
• Time series data in MindSphere
  • Requires user account, contact us to apply for one
  • Graphical user interface behind
  • REST API to the data is also available, link to
• Digital twin description document
  • Includes machine-readable metadata about Ilmatar crane.
  • Uses the solution.
  • Available via
• 3D model of the crane
  • surface model, available in both STEP and Siemens NX formats
  • Available in
• Available upon request: Simulation model of the crane
  • with the same OPC UA interface as the physical crane
  • (requires Visual Components software)

Dependencies of the Ilmatar OIE

• OPC UA - GraphQL wrapper software
  • Installed to a Raspberry Pi in the crane network
  • Source code available at GitHub:

Applications developed and available in the Ilmatar OIE

• GraphQL-based user interface application to monitor and control the crane
  • Source code available at Gihub:

Resources with limited availability and/or possible unfinished projects. Please reach technical contact for more information.

• Application: High Precision Lifting Device
  • Journal article of the development process:
• Application: HoloLens control of the crane
• MindSphere based REST API to crane data
• Digital twin data broker

Supporting materials:

• OSEMA: Open Sensor Manager
  • Can be used to add sensors to the crane environment or anywhere else
  • Available at GitHub:
  • These describe the basic idea of the sensor manager:
    • Open access journal article
    • Master's thesis:

Getting started

You can use the resources according to their respective terms.

Physical access

The crane is located in the recently renovated Viima building (Puumiehenkuja 5), more precisely inside . The facilities are generally open during normal office hours, but it is advisable to ensure access in advance from a staff member.

Moving the crane physically requires a safety training which are organized based on demand. Contact us for more info.

to get access to the resources. (The access is given manually, so please prepare for a delay of day or two.)

Please contact us if you have any questions.

Academic publications

2025

Yang, C. et al. (2025) ‘A digital twin-driven industrial context-aware system: A case study of overhead crane operation’, Journal of Manufacturing Systems, 78, pp. 394–409. Available at: .

2024

Tu, X. (2024) Industrial Metaverse: Revolutionizing Industry 5.0 with Digital Twins and Extended Reality. Doctoral thesis. Aalto University. Available at: .

Tu, X., Ala-Laurinaho, R., Yang, C., Autiosalo, J. and Tammi, K. (2024) ‘Architecture for data-centric and semantic-enhanced industrial metaverse: Bridging physical factories and virtual landscape’, Journal of Manufacturing Systems, 74, pp. 965–979. Available at: .

2023

Joswig, N., Autiosalo, J. and Ruotsalainen, L. (2023) ‘Improved deep depth estimation for environments with sparse visual cues’, Machine Vision and Applications, 34(1), p. 18. Available at: .

Tu, X. et al. (2023) ‘TwinXR: Method for using digital twin descriptions in industrial eXtended reality applications’, Frontiers in Virtual Reality, 4. Available at: .

2022

Mattila, J. et al. (2022) ‘Using Digital Twin Documents to Control a Smart Factory: Simulation Approach with ROS, Gazebo, and Twinbase’, Machines, 10(4), p. 225. Available at: .

Mustapää, T. et al. (2022) ‘Secure Exchange of Digital Metrological Data in a Smart Overhead Crane’, Sensors, 22(4), p. 1548. Available at: .

Yang, C. et al. (2022) ‘Extended Reality Application Framework for a Digital-Twin-Based Smart Crane’, Applied Sciences, 12(12), p. 6030. Available at: .

2021

Ala-Laurinaho, R. (2021) API-based Digital Twins - Architecture for Building Modular Digital Twins Following Microservices Architectural Style. Doctoral thesis. Aalto University. Available at: .

Autiosalo, J. (2021) Discovering the Digital Twin Web - From singular applications to a scalable network. Doctoral thesis. Aalto University. Available at: .

Autiosalo, J. et al. (2021) ‘Towards Integrated Digital Twins for Industrial Products: Case Study on an Overhead Crane’, Applied Sciences, 11(2), p. 683. Available at: .

Tu, X. et al. (2021) ‘A Mixed Reality Interface for a Digital Twin Based Crane’, Applied Sciences, 11(20), p. 9480. Available at: .

Yang, C. (2021) Framework for virtual reality digital services leveraging digital twin-based crane. Available at: .

2020

Ala-Laurinaho, R., Autiosalo, J. and Tammi, K. (2020) ‘Open Sensor Manager for IIoT’, Journal of Sensor and Actuator Networks, 9(2), p. 30. Available at: .

Ala-Laurinaho, R. et al. (2020) ‘Data Link for the Creation of Digital Twins’, IEEE Access, 8, pp. 228675–228684. Available at: .

Hietala, J. et al. (2020) ‘GraphQL Interface for OPC UA’, in 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS). 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS), pp. 149–155. Available at: .

Hietala, J. (2020) Real-time two-way data transfer with a digital twin via web interface. MSc thesis. Aalto University. Available at: .

Hublikar, P. (2020) A prototype of a digital twin with mixed reality and voice user interfaces for controlling a smart industrial crane. MSc thesis. Aalto University. Available at: .

Mattila, J. (2020) Nosturidatan analysointi ja visualisointi IoT-alustalla. BSc thesis. Aalto University. Available at: .

Tu, X. (2020) A mixed reality interface for digital twin based crane. MSc thesis. Aalto University. Available at: .

2019

Ala-Laurinaho, R. (2019) Sensor data transmission from a physical twin to a digital twin. MSc thesis. Available at: .

2018

Autiosalo, J. (2018) ‘Platform for industrial internet and digital twin focused education, research, and innovation: Ilmatar the overhead crane’, in 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), pp. 241–244. Available at: .

Lagus, H. (2018) Digitaalisen kaksosen tietoturvavaatimukset. BSc thesis. Available at: .

Sjöman, H. et al. (2018) ‘Using Low-Cost Sensors to Develop a High Precision Lifting Controller Device for an Overhead Crane—Insights and Hypotheses from Prototyping a Heavy Industrial Internet Project’, Sensors, 18(10), p. 3328. Available at: .

Other publications

Aalto University students win innovation competition with autonomous hoist | Aalto University (2019). Available at: /en/news/aalto-university-students-win-innovation-competition-with-autonomous-hoist

Chattopadhyay, A. et al. (2019) Autonomous crane for warehouse management - AEEproject - Aalto University Wiki. Available at:

Lehto, T. (2019) ‘Opiskelijoiden tekoälykisan voittaja aikaansa edellä – ”Lainsäädäntö ei vielä salli...”’, Tivi, 13 May. Available at:

Konecranes CXT NEO-based crane enables industrial internet research at Aalto University. Konecranes. Available at:

Smart crane receives open development environment | Aalto University (2019). Available at: /en/news/smart-crane-receives-open-development-environment

The smart crane and first research topics presented at the Industrial Internet Campus | Aalto University (2017). Available at: /en/news/the-smart-crane-and-first-research-topics-presented-at-the-industrial-internet-campus