Research & Innovation

Research & Innovation

10 years of research to optimize equipment and the customer experience.

Our research at BLPredict focuses on leveraging equipment data with AI to optimize performance and operational efficiency. Our R&D researchers and engineers create new approaches to transform your data into actionable intelligence, facilitating predictive maintenance, accelerated diagnostics and the transition to “Equipment as a Service” (EaaS) models. Our distributed and frugal AI algorithms and technologies enable significant reductions in operational costs, increased equipment availability and differentiation through innovative new services.. .

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Discover our scientific publications

  • Ducharlet, K., Travé-Massuyès, L., Lasserre, J.-B., Le Lann, M.-V., & Miloudi, Y. (2024). Leveraging the Christoffel function for outlier detection in data streams. International Journal of Data Science and Analytics. https://doi.org/10.1007/s41060-024-00581-2
  • SAFRI, H., KANDI, M. M., & MILOUDI, Y. (2024, September 17). Towards Efficient Belt Conveyor Maintenance: Leveraging Federated Learning. The 2nd IEEE International Conference on Federated Learning Technologies and Applications (FLTA24). Valencia , Spain.
  • Safri, H., Papadimitriou, G., & Deelman, E. (2024). Dynamic Tracking, MLOps, and Workflow Integration: Enabling Transparent Reproducibility in Machine Learning. 2024 IEEE 20th International Conference on E-Science (e-Science), 1-10. https://doi.org/10.1109/e-Science62913.2024.10678658
  • Safri, H., Papadimitriou, G., Desprez, F., & Deelman, E. (2024). A Workflow Management System Approach To Federated Learning: Application to Industry 4.0. 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2024, Abu Dhabi, United Arab Emirates, April 29 – May 1, 2024, 259-263. https://doi.org/10.1109/DCOSS-IoT61029.2024.00047
  • Baudry, G., BA, P. A., & Miloudi, Y. (2023, January 24). Entre défis organisationnels, sociaux et techniques pour la production de la ville: de la plateformisation des services à l’usager vers la transversalitédes échanges. Colloque international – Economie sociale et solidaire et Animation socioculturelle : quelles contributions dans la résilience des territoires, Bordeaux, France. https://hal.science/hal-03969467
  • Toufaili, E., Bortolaso, C., Miloudi, Y., Petit, J.-M., & Scuturici, V.-M. (2023). Information visualization for industrial process monitoring. International Database Engineered Applications Symposium Conference, 107-114. https://doi.org/10.1145/3589462.3595631
  • Ducharlet, K. (2023). Anomaly detection in data flows for application in sensor networks [Phdthesis, INSA de Toulouse]. https://laas.hal.science/tel-04281671
  • Ducharlet, K., Travé-Massuyès, L., Le Lann, M.-V., & Miloudi, Y. (2022, June). Study of unsupervised anomaly detection methods applied to data streams. 20th Rencontres Des Jeunes Chercheurs En Intelligence Artificielle. https://hal.archives-ouvertes.fr/hal-03765550
  • Dufour, S., Mehdi Kandi, M., Boutamine, K., Gosset, C., Billami, M. B., Bortolaso, C., & Miloudi, Y. (2022). BL.Research at SemEval-2022 Task 8: Using various Semantic Information to evaluate document-level Semantic Textual Similarity. Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), 1221-1228. https://aclanthology.org/2022.semeval-1.173
  • Safri, H., Kandi, M. M., Miloudi, Y., Bortolaso, C., Trystram, D., & Desprez, F. (2022). Towards Developing a Global Federated Learning Platform for IoT. 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), 1312-1315. https://doi.org/10.1109/ICDCS54860.2022.00145
  • Toufaili, E., Miloudi, Y., & Bortolaso, C. (2022). Information visualization adapted to industrial process monitoring. PFIA 2022. PFIA 2022 – IoT and AI Day, St Etienne, France.
  • Ducharlet, K., Travé-Massuyès, L., Le Lann, M.-V., & Miloudi, Y. (2020). A Multi-phase Iterative Approach for Anomaly Detection and Its Agnostic Evaluation. Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices , 505-517. https://doi.org/10.1007/978-3-030-55789-8_44