Publications
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An improved 3D skeletons UP-Fall dataset : enhancing data quality for efficient impact fall detection
Detecting impact where an individual makes contact with the ground within a fall event is crucial in fall detection systems, particularly for elderly care where prompt intervention can prevent serious injuries. The UP-Fall dataset, a key resource in fall detection research, has proven valuable but suffers from limitations in data accuracy and comprehensiveness. These limitations […]
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Designing Secure and Smart Supply Chains: A Roadmap
The supply chain (SC) comprises all the vital stages a product goes through to its final destination, forming a value chain. In this article, our primary focus is on integrating Internet of Things, artificial intelligence, and blockchain technology to design secure and smart SC systems.
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Contribution to the distribution supply chain’s performance through the use of digital technologies Case study: cold logistics chain
The development of the Internet of Things (IOT) has made it easier to obtain real-time data related to the supply chain for food distribution’s traceability management. In this study, we suggest digitally transforming the supply chain for seafood distribution. In order to provide better visibility of both traceability data and the parameters that need to […]
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Remaining useful life prediction with uncertainty quantification using evidential deep learning
Predictive Maintenance presents an important and challenging task in Industry 4.0. It aims to prevent premature failures and reduce costs by avoiding unnecessary maintenance tasks. This involves estimating the Remaining Useful Life (RUL), which provides critical information for decision makers and planners of future maintenance activities. However, RUL prediction is not simple due to the […]
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Transitioning from AGVs to AIVs in Integrated Job Shop Scheduling with Transportation Tasks: aMulti-agent Simulator for Comparative Analysis
Optimizing job shop scheduling in modern factories demands flexibility and adaptability to handle unexpected events and Unmanned Ground Vehicles (UGVs) limitations. This paper addresses these challenges by introducing a novel multi-agent simulator for the Job Shop Scheduling Problem (JSSP) with UGVs handling transportation tasks. The simulator, designed with Netlogo, incorporates real-world constraints, such as collision […]
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La construction circulaire en action
Engagé dans une démarche de baisse de son impact environnemental, le secteur de la construction s’applique à passer d’un modèle économique linéaire « fabriquer, consommer, jeter » à un modèle circulaire, favorisant le réemploi, la durabilité et la réversibilité. Alors que la pénurie de matériaux est de plus en plus préoccupante, il est essentiel d’anticiper […]
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Multimodal transportation network for bio-waste collection: the case of Normandy
In this paper, we introduce a new topology, connected-hubs, to the multimodal transportation literature. As strategic planning, the multimodal transportation network design decides the locations of consolidation centers and the routes between the origins and the destinations with the minimum of total cost. Most existing papers formulate the problem based on the hub-and-spoke topology, while […]
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Graph Transformer Mixture-of-Experts (GTMoE) for 3D Hand Gesture Recognition
Mixture-of-experts (MoE) architectures have gained popularity in achieving high performance in a wide range of challenging tasks in Large Language Modeling (LLM) and Computer Vision, especially with the rise of Mixture-of-Experts with Mixtral/Mistral-7B Transformers. In this work, we propose the Graph Transformer Mixture-of-Experts (GTMoE) deep learning architecture to enhance the ability of the Transformer model […]
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Dataset of an operating education modular building for simulation and artificial intelligence
Improving energy efficiency in the building sector is a subject of significant interest, considering the environmental impact of buildings. Energy efficiency involves many aspects, such as occupant comfort, system monitoring and maintenance, data treatment, instrumentation… Physical modeling and calibration, or artificial intelligence, are often employed to explore these different subjects and, thus, to limit energy […]
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Multi-Objective Sustainable Flexible Job Shop Scheduling Problem: Balancing Economic, Ecological, and Social Criteria
Industry 5.0 makes it imperative to reevaluate the manner of using resources in manufacturing systems to ensure sustainability. In this context, scheduling problems are encountering new environmental and humanrelated challenges, and the concept of sustainable scheduling has gained importance, aiming to balance economic, environmental, and human factors. In this paper, we propose two multi-objective mathematical […]
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Dynamic and Sustainable Flexible Job Shop Scheduling Problem under Worker Unavailability Risk
In the current context of Industry 5.0, sustainable scheduling has emerged as an evolution of classical scheduling, now integrating environmental and human-centric considerations. The objective is to strike a balance between economic, environmental, and societal concerns. Additionally, there is a growing need to enhance the resilience in the Industry 5.0 era, necessitating dynamic systems capable […]
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Energy-Efficient Flexible Flow Shop Scheduling Under Time-Of-Use Rates with Renewable Energy Sources
In response to climate change, industries strive to curtail energy consumption while maintaining production efficiency. Focused on time-dependent electricity prices, this paper addresses the scheduling challenge in a flexible flow shop machine environment. The goal is to minimize both makespan and total electricity costs in a grid-connected manufacturing setup with battery storage, solar power, and […]
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