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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Improving Pain Classification using Spatio-Temporal Deep Learning Approaches with Facial Expressions
Pain management and severity detection are crucial for effective treatment, yet traditional self-reporting methods are subjective and may be unsuitable for non-verbal individuals (people with limited speaking skills). To address this limitation, we explore automated pain detection using facial expressions. Our study leverages deep learning techniques to improve pain assessment by analyzing facial images from […]
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GSK-C2F Graph Skeleton Modelization for Action Segmentation and Recognition using a Coarse-to-Fine strategy
Locating the temporal boundaries of performing actions, especially in industry 5.0 context, poses significant challenges due to several factors. These include the complex industrial environment, the presence of similarities between inter-class actions, the significant variation in the execution of intra-class actions arising from the expertise levels of operators, and the under or over-representation of particular […]
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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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Artificial neural network-based models for short term forecasting of solar PV power output and battery state of charge of solar electric vehicle charging station
The main objective of this study is to develop ANN-based predictive models for short-term forecasting of solar PV power output and battery state of charge. The 3Ds energy model that integrates Decarbonization, Digitalization, and Decentralization of the energy system to facilitate the shift towards sustainable energy sources is used for this electric vehicle project. The […]
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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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Performance analysis and planning of Self-Sufficient solar PV-Powered electric vehicle charging station in dusty conditions for sustainable transport
Electric car charging stations are in high demand as a result of the development of the e-mobility sector and the adoption of electric vehicles in transportation. This study aims to construct and analyze a stand-alone solar PV-powered electric car charging station to fulfil electric vehicle load demand and make recommendations for optimizing its operation. The […]
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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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