INFOS – Digital Textile Passport
A INFOS participated as a partner and co-author in the scientific article “Machine Learning-Based Data Quality Assessment for the Textile and Clothing Digital Product Passport”, recently published in the journal Applied Sciences (MDPI).
The study focuses on the application of techniques for Machine Learning to ensure the Data quality and reliability in the context of Digital Product Passport (DPP) of the textile industry.
The contribution of INFOS
O Marcelo Alves, Head of Innovation at INFOS, is one of the authors of the article and contributed decisively to:
- Define the technical integration requirements between systems;
- Develop Data validation APIs applicable to the DPP ecosystem;
- Model tuning Machine Learning in the context of the textile industry;
- Analyse performance metrics of models applied to anomaly detection.
This contribution reinforces the role of INFOS as Technology innovation agent in the textile sector, not just as a provider of solutions, but also as an active partner in applied research.
The importance of studying
The article responds to a central industry challenge: ensuring that data used for traceability, sustainability, and transparency has Quality and consistency.
The DPP requires the integration of data from multiple stakeholders, and the application of Machine Learning techniques allows for the detection and correction of errors before their incorporation into critical systems.
With this advance, the industry can gain efficiency, credibility and trust in the process of digitalisation and transition to the circular economy.
Conclusion
INFOS's participation in this scientific work reflects its commitment to the Innovation in the textile sector and your capacity to collaborate on high-impact research projects.
