Publications
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Reinforcement Learning for Optimal HVAC Control: from Theory to Real-world Applications
The HVAC system accounted for a significant portion of the building’s energy consumption, resulting in enormous CO2 emissions. Among the numerous HVAC control methods, reinforcement learning (RL) gives the ability to control complex systems without requiring an explicit model of the building’s thermal dynamics. This study conducted a concise review of previous research on the […]
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Occupancy Prediction in Buildings Using Cascaded LSTM Model
Buildings are one of the prominent sectors among global primary energy consumption. A large portion of this energy consumption is influenced by occupancy interaction with the buildings. Occupancy prediction in buildings without intruding their privacy helps to enhance the building energy management. Due to the complex relations of the inputs and the temporal dependency, modeling […]
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Indoor Air Temperature and Occupant Behavior in Classroom of higher education building in Mediterranean climate
Data collection Include the measurement of indoor and outdoor environmental parameters (air temperature and relative humidity) and occupant interactions with building systems (window and door status: open/closed, blind state, and thermostat/air-conditioning adjustment). The outdoor air temperature, relative humidity, and wind speed were collected as potential control variables to indicate different outdoor conditions. The indoor air […]
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Digital Twin of an education modular smart building
As described by Nguyen and Adhikari [1], the digital twin (DT) is a tool that is expected to address issues link to the interactions between building monitored data and decisions to manage effectively the building during its entire life cycle. Nevertheless, the development and the use of the DT is not always natural since it […]
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Insights Into the Importance of Linguistic Textual Features on the Persuasiveness of Public Speaking
In both professional and private life, there is a growing need for public speaking skills. With this background, our research project’s long-term aims are to develop tools that can analyse public speeches and provide useful feedback. The impact of audio and visual characteristics on the automatic analysis of speech quality has been widely explored in […]
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ACE: how Artificial Character Embodiment shapes user behaviour in multi-modal interactions
The ACE -how Artifcial Character Embodiment shapes user behavior in multi-modal interactions -workshop aims to bring together researchers, practitioners and experts on the topic of embodiment, to analyze and foster discussion on its efects on user behavior in multi-modal interaction. ACE is aimed at stimulating multidisciplinary discussions on the topic, sharing recent progress, and providing […]
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A Secured Blockchain Framework for Healthcare Data Management System
In the healthcare system, electronic medical records are very critical, and they must be authenticated and verified. During the medical check-up, a large amount of patient medical data is generated which includes reports related to blood, lifethreatening diseases, and personal information such as credit card numbers and addresses. Any privacy breach in patient medical records […]
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CAPSULE TRANSFORMER NETWORK FOR DYNAMIC HAND GESTURE RECOGNITION USING MULTIMODAL DATA
In recent years, deep learning techniques have achieved remarkable success in video analysis and more especially in action and gesture recognition. Even though convolutional neural networks (CNNs) remain the most widely used models, they have difficulty in capturing the global contextual information involving spatial and temporal domains or intermodality due to the local feature learning […]
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Fully Residual Unet-based Semantic Segmentation of Automotive Fisheye Images: a Comparison of Rectangular and Deformable Convolutions
Semantic image segmentation is an essential task for autonomous vehicles and self-driving cars where a complete and real-time perception of the surroundings is mandatory. Convolutional Neural Network approaches for semantic segmentation standout over other state-of-the-art solutions due to their powerful generalization ability over unknown data and end-to-end training. Fisheye images are important due to their […]
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Forecasting photovoltaic energy for a winter house using a Hybrid Deep Learning Model
As part of the energy transition, controlling energy consumption is a challenge for everyone. To this end, a number of sustainable solutions are being proposed, notably for BIPV (Building Integrated Photovoltaics) buildings. In addition, artificial intelligence (AI) is an effective tool for analyzing photovoltaic (PV) energy production and consumption data. It will then be possible […]
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Machine Learning and Feature Ranking for Impact Fall Detection Event Using Multisensor Data
Falls among individuals, especially the elderly population, can lead to serious injuries and complications. Detecting impact moments within a fall event is crucial for providing timely assistance and minimizing the negative consequences. In this work, we aim to address this challenge by applying thorough preprocessing techniques to the multisensor dataset, the goal is to eliminate […]
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MR-STGN: Multi-Residual Spatio Temporal Graph Network using Attention Fusion for Patient Action Assessment
Accurate assessment of patient actions plays a crucial role in healthcare as it contributes significantly to disease progression monitoring and treatment effectiveness. However, traditional approaches to assess patient actions often rely on manual observation and scoring, which are subjective and time-consuming. In this paper, we propose an automated approach for patient action assessment using a […]
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