Publications
-
Optimal Deployment of Fog-Based Solution for Connected Devices in Smart Factory
Internet of Things (IoT) is commonly used in Industry-4.0/5.0, but it generates an excessive amount of data that affects quality of service (QoS). To address this challenge, Fog-based architectures have emerged as an alternative solution. However, its deployment can be challenging, particularly when dealing with mobile connected devices like robots. To optimize the deployment of […]
-
Toward a digital twin IoT for the validation of AI algorithms in smart-city applications
Thedevelopmentofdigitaltwinsforroadtraffichasgarnered significant attention within the scientific community, particularly in the realms of virtualization and the Internet of Things (IoT). The implemen- tation of a digital twin for automobiles offers a virtual replica, capable of discerning the precise location, status, and real-time behavior of each vehicle present in the road traffic network. The primary objective of […]
-
Towards deep learning methods to improve photovoltaic prediction and building decarbonization in benchmarking study
High energy demand, energy transition, energy consumption control are challenges for the future, especially for Building Integrated Photovoltaic (BIPV). There is a great potential to harvest large amounts of photovoltaic (PV) energy on horizontal and vertical surfaces. However, this high potential is often hindered by the slow deployment of these panels, the complex integration into […]
-
T2S-MAKEP and T2T-MAKEP: A PUF-based Mutual Authentication and Key Exchange Protocol for IoT devices
Nowadays, more constrained devices are becoming connected, building an extensive Internet of Things (IoT) network, but suffering from many security issues. In particular, authentication has become a severe research challenge for IoT systems. Furthermore, confidentiality, integrity, and availability are considered the core underpinnings of information security in general. Unfortunately, deploying conventional authentication protocols for IoT […]
-
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 […]
-
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 […]
-
Deep Reinforcement Learning for multiobjective Scheduling in Industry 5.0 Reconfigurable Manufacturing Systems
In today’s manufacturing environment, the need to respond quickly to changing market demands is critical. Reconfigurable Manu- facturing Systems (RMS) represent a monumental step towards realis- ing this requirement, providing an agile and cost-effective framework to accommodate changing production needs. The dynamic nature of RMS requires the integration of robust learning algorithms to continuously op- […]
-
Artificial Intelligence Assistive Fire Detection and Seeing the Invisible Through Smoke using Hyperspectral and Multi-spectral Images
Abstract— The global warming has serious impact on our climate. Due to this, the frequency and the intensity of forest fires is increasing. It has shown serious challenges such as the protection of resources, human and wild life, health, and property. This study focuses on developing an artificial intelligence assistive innovative solution for active fire […]
-
Machine Learning Assistive State of Charge Estimation of Li-Ion Battery
For an effective and economical deployment of battery-powered electric vehicles, mobile phones, laptops, and medical gadgets, the State of Charge (SoC) of the batteries must be properly assessed. It permits a safe operation, have a longer usable battery life, and prevent malfunctions. In this context, the battery management systems provide diverse SoC estimation solutions. However, […]
-
Hybradization of Emperical Mode Decomposition and Machine Learning for Categorization of Cardiac Diseases
The arrhythmia is one of the cardiovascular diseases which has several types. In literature, researchers have presented a broad study on the strategies utilized for Electrocardiogram (ECG) signal investigation. Automated arrhythmia detection by analyzing the ECG data is reported using a number of intriguing techniques and discoveries. In order to effectively categorize arrhythmia, a novel […]
-
Developing innovation culture through the transformation of a master learning path
Every year, around one thousands of postgraduate students attends CESI preparing expertise master courses on diverse aspects of management. During this year, MS® postgraduate students work in companies and spend one week per month at CESI. For each student, one of the issue of the year is to write a professional thesis. On student size, […]
-
Toward Universal Creativity Assessment by Untrained Judges
The purpose of a creativity session being first to generate many ideas, how to fast and reliably assess each one’s creativity, even with non-creativity experts? Creative people appearing not only to be good at generating ideas but also at implicitly evaluating them, improving people’s assessment would further improve their own creativity. This paper investigates canonical […]
Loading…
Erreur : tout le contenu a été chargé.