2. ISS Team
Intelligent Security Systems
📌
Code: W1164102
Leader Team
Members
PhD Students
Welcome to the Intelligent Safety Systems (ISS) team, a dynamic and innovative research group within the LISIDD laboratory. Our mission is to enhance safety in industrial processes through the development of cutting-edge technologies and methodologies. We are committed to fostering social progress and improving the quality of life for persons, installations and environment, contributing significantly to sustainable development.
Research Axes
Our research focuses on several key areas:
- Intelligent Dynamic Monitoring Systems: Developing advanced systems for real-time monitoring and management of industrial environments.
- Innovative Dynamic Neural Networks: Introducing new neural network models to enhance predictive capabilities in safety systems.
- Fuzzy Logic Applications: Utilizing fuzzy logic for its flexibility and powerful predictive dimensions in safety analysis.
- Neuro-Fuzzy Network for Diagnosis: Creating a neuro-fuzzy network, derived from fault trees and AMDEC analysis, for both curative and predictive diagnosis.
- Multi-Agent Safety Systems: Designing intelligent monitoring tools using multi-agent systems to enhance safety and prevention measures.
- Bayesian Approaches in Security Analysis: Employing frequency probabilistic methods, like Bayesian approaches, for in-depth security analysis and making-decision.
- Additional Research Elements:
- Improving Functional Safety: Through a deep understanding of manufacturing processes, machine limitations, and human-machine interactions, we aim to elevate the level of functional safety.
- Innovative Security Technologies: Integrating new security technologies and standards (like API, NFPA, and ISO) into our research to position safety as a critical system function.
- Risk Analysis and Minimization: Utilizing operational data and predictive analytics tools to measure and minimize operational risks continuously.
Keywords:
- Intelligent Security
- Intelligent Prevention
- Intelligent Dynamic Surveillance Systems
- Multi-Agent System
- Artificial Neural Networks
- Fuzzy Logic
- Neuro-Fuzzy Networks
- Curative Diagnosis
- Preventive Diagnosis
- Bayesian Networks
- Renewable Energy Safety
- Hydrogen Safety
- Firefighting Systems
- API, NFPA, ISO Standards
- Fault Tree Analysis
- Reliability Block Diagrams
- Safety Integrity Level (SIL)
- Multi-Criteria Methods
- Reliability Engineering (RAMS)
Books
Approche Bayésienne expérimentale pour l’analyse des risques
Nassima Aissani, Islam Hadj Mohamed Guetarni
2023
Thesis
Analyse Quantitative Des Risques : Application Sur Les Bacs De Stockage
Guetarni Islam Hadj Mohamed
Université Mohamed Ben Ahmed - Oran 2, 2019
Chapters
Nassima Aissani, Islam Hadj Mohamed Guetarni
Theodor Borangiu, Andr{\'e} Thomas, Damien Trentesaux, Service Orientation in Holonic and Multi-agent Manufacturing, Springer International Publishing, Cham, 2015, pp. 125--134
A Model for Manufacturing Scheduling Optimization Through Learning Intelligent Products
Wassim Bouazza, Yves Sallez, Nassima Aissani, Bouziane Beldjilali
Theodor Borangiu, Andr{\'e} Thomas, Damien Trentesaux, Service Orientation in Holonic and Multi-agent Manufacturing, Springer International Publishing, Cham, 2015, pp. 233--241
Extraction of Priority Rules for Boolean Induction in Distributed Manufacturing Control
Nassima Aissani, Baghdad Atmani, Damien Trentesaux, Bouziane Beldjilali
Theodor Borangiu, Damien Trentesaux, Andre Thomas, Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics, Springer International Publishing, Cham, 2014, pp. 127--143
