Meriem Smati, Christophe Danjou
, Jannik Laval and Vincent Cheutet
Abstract (2024)
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| Additional Information: | Laboratoire Poly-Industrie 4.0 |
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| Department: | Department of Mathematics and Industrial Engineering |
| PolyPublie URL: | https://publications.polymtl.ca/66441/ |
| Conference Title: | 2nd annuel congress of Société d'Automatique, de Génie Industriel et de Productique (SAGIP 2024) |
| Conference Location: | Villeurbanne, France |
| Conference Date(s): | 2024-05-29 - 2024-05-31 |
| Publisher: | SAGIP |
| Official URL: | https://sagip2024.sciencesconf.org/538707 |
| Date Deposited: | 02 Jul 2025 16:33 |
| Last Modified: | 02 Jul 2025 16:33 |
| Cite in APA 7: | Smati, M., Danjou, C., Laval, J., & Cheutet, V. (2024, May). Enhancing Data Integrity: A Solution to Predict Data Disturbance in IoT Systems [Abstract]. 2nd annuel congress of Société d'Automatique, de Génie Industriel et de Productique (SAGIP 2024), Villeurbanne, France (1 page). https://sagip2024.sciencesconf.org/538707 |
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