Project description
Scalable solution for multiple indoor positioning technologies in industrial environments
Indoor positioning (IP) will play a central role in industry 4.0 by assisting unmanned vehicle navigation or tracking goods within the value chain. However, some disadvantages prevent the usage of technologies with the technical requirements for IP in industrial environments. Also, the variations in scenarios used in empirical assessment exclude the direct comparison of existing IP technologies. The EU-funded ORIENTATE project will address this issue with a new scalable high-accuracy solution. It will integrate multiple IP technologies to create an open assessment structure. The project’s solution is based on visible-light communications principles, processing data provided by other positioning modules with neural networks and local outlier factors, and coding trusted positioning information as hyperspectral images.
Objective
We are clearly on the verge of Industry 4.0. The European Commission is investing on European Industry digitalisation not only to improve competitiveness but also to reach climate-neutrality. Indoor Positioning (IP) will play a key role in Industry 4.0 by, for instance, supporting unmanned vehicles navigation or tracking goods within the value chain. Despite there are already technologies coping with the technical requirements for IP in industrial environments, they present drawbacks that might prevent its usage. Moreover, a direct comparison of the current IP technologies is not possible due to the diversity of scenarios used in empirical evaluation. This project aims to provide a significant contribution to Industrial IP by: i) proposing a new scalable high-accurate solution; ii) dynamically integrating multiple IP technologies; iii) creating an open evaluation framework. From the methodological point of view, a novel solution -based on Visible-Light Communications principles- will be proposed. Moreover, data provided by positioning modules will be processed with neural networks and local outlier factor to detect anomalous behaviour. Trusted positioning information will be coded as hyperspectral images to allow dynamic sensor fusion through Deep Neural Networks. Finally, the Experienced Researcher, with the support of 3 industrial partners and 12 international researchers, will agree an evaluation framework for Industrial IP. The project outcomes will contribute to the IP community with significant advances to the state-of-the-art solutions and, specially, with a new open evaluation framework and generated datasets. The Experienced Researcher will emerge from the project with acquired multidisciplinary competences necessary to conduct high-impact research projects and deliver high-level consultancy services. Thus, it will grant the ER the capacity of achieving maturity and independence on Industrial IP, a research area with great growth potential.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
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Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
4704 553 Braga
Portugal