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DIY Wind Turbines: A Low-Cost Smart ICPS for Educational Research

aut.relation.conference2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)
dc.contributor.authorKuo, Matthew MY
dc.contributor.authorSinha, Roopak
dc.contributor.authorLewis, Ramon
dc.contributor.authorCumming, Charlie
dc.contributor.authorAlarcon, Robin
dc.contributor.authorSharma, Chandan
dc.date.accessioned2025-02-23T22:51:09Z
dc.date.available2025-02-23T22:51:09Z
dc.date.issued2023-11-28
dc.description.abstractIndustrial cyber-physical systems (ICPS) research combines many fields, including mechatronics, electrical, electronic, network, systems and software engineering. ICPS testbeds are often prohibitively expensive to purchase, store and maintain, and tied to vendor-specific tool chains, making them infeasible for small-scale experimental and student-led research. With the rising popularity of 3D printing and ubiquitous computing, it is now possible to rapidly and inexpensively build model ICPS for lab research. This paper presents the “from scratch” construction of an open-source 3D-printed smart wind turbine as a case study. We cover 3D modelling and printing of the wind turbine parts, the hardware-software interfacing and controller design using Arduino and the ESP8266 embedded WiFi controller. Interested readers can build a similar smart wind turbine by downloading the guidance and resource files linked to this document within days. The smart wind turbine also serves as a rich ICPS research and education testbed to enable next-generation learning. In addition to discipline-specific tasks like incrementally optimising the 3D model, the interfacing and/or controller design, students and researchers can also use it for interdisciplinary research exploration. As an example, we show how the design and development of the smart wind turbine can be used to study, learn, and research requirements traceability. We employ graph databases to effectively model, represent, manage and trace requirements throughout the development of the smart wind turbine. The key outcome is a light-weight and efficient method for managing requirements using the Neo4j graph database implementation.
dc.identifier.citation2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), Auckland, New Zealand, 2023, pp. 1-4, doi: 10.1109/TALE56641.2023.10398414
dc.identifier.doi10.1109/tale56641.2023.10398414
dc.identifier.urihttp://hdl.handle.net/10292/18752
dc.publisherIEEE
dc.relation.urihttps://ieeexplore.ieee.org/document/10398414
dc.rightsCopyright © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accessrightsOpenAccess
dc.subjectICPS, CPS, IoT, control software, machines, 3D printing, requirements traceability, wind turbine.
dc.titleDIY Wind Turbines: A Low-Cost Smart ICPS for Educational Research
dc.typeConference Contribution
pubs.elements-id536578

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