Publications
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A global approach based on k-means clustering principle for optimal smartphones and laptops batteries waste collection in Algeria
Rapid urbanization and population growth in developing countries have posed significant challenges for solid waste management. This is clearly evident in African countries including Algeria, where environmental concerns are not effectively managed. The purpose of this article is to design a network to facilitate waste collection in Algeria. A location allocation-based clustering approach is proposed, […]
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Fault Diagnosis using Deep Neural Networks for Industrial Alarm Sequence Clustering
Significant progress has been made in the field of industrial alarm management systems (AMS) in terms of diagnostic and prognostic accuracy. However, persistent challenges, such as poorly configured alarm setups and floods, contribute to an increased number of false alarms, consequently reducing the efficiency of the monitoring system. In addition, more sophisticated models and interactive […]
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Synthetic Population Generation for Autonomous Vehicle Demand Forecasting
The growing interest in Automated Mobility on Demand (AMoD) services in passenger transportation necessitates accurate forecasting for successful deployment. However, the paucity of real-world data is a significant challenge. In this study, we present a unique technique for developing a synthetic user population tailored to AMoD car services. We identify possible passengers using selection criteria […]
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OSR: Advancing Multi-Hop Routing for LoRaWAN Mesh Networks in Maritime Scenarios
Reliable data acquisition and transmission from ocean-deployed buoys are crucial for maritime applications. However, wireless data transmission in such contexts faces significant challenges due to limited buoy battery capacity, harsh weather conditions, and potential disruptions from maritime vessels. LoRaWAN technology presents a promising solution due to its low power consumption and long-range communication capabilities. Multi-hop […]
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LoRaCAPS: Congestion-Aware Path Selection Protocol for Offshore LoRaWAN Networking
LoRaWAN technology plays a pivotal role in enabling data transmission from IoT devices across various industries. In the maritime sector, applications such as operational monitoring and environmental surveillance depend critically on reliable data communication. However, wireless data transmission at sea presents significant challenges, including limited device battery life, harsh weather conditions, and interference from vessels. […]
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A model-driven approach for prospective ergonomics: Application to ikigai robotics
Prospective Ergonomics requires building a vision of the future, which can be achieved empirically (e.g. analysing unmet needs) and/or creatively (e.g. creating future needs). We develop an alternative way of imagining the future, through a model-driven approach. Based on several developmental models, we provide a global picture of possible future(s) emphasising higher-ordered motivations and values […]
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Multi Objective Optimization of Human-Robot Collaboration: A Case Study in Aerospace Assembly Line
Collaborative robotics is becoming increasingly prevalent in industry 5.0, leading to a growing need to improve interactions and collaborations between humans and robots. However, the current approach to defining the sharing of responsibilities between humans and robots is empirical and uses the robot as an active fixture of parts, which is a sub-optimal method for […]
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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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Educational digital twins (EDT) to a sustainable future? Between promises and reality
The Sustainable Development Goals set by the United Nations in 2015 underline the urgency of sustainability in all sectors, starting with the industrial sector. The ambition of Industry 5.0 is to go beyond Industry 4.0, striving for a sustainable technological revolution centered on people (Barcellini, 2019; Julien & Martin, 2021). So-called “disruptive” industrial innovations are […]
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Proteus effect: how avatars influence the way we behave
Poster présenté au RJC en IHM 2024 sur le projet de thèse d’Anna Martin Coesel
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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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