Explanipedia

Collaborative intrusion detection in resource-constrained IoT environments: Challenges, methods, and future directions a review Open

Vasilis Ieropoulos, Eirini Anthi, Theodoros Spyridopoulos, Pete Burnap, Ioannis Mavromatis , et al. · 2025

Optimizing Convolutional Neural Networks for Real-Time Object Detection in Autonomous Vehicles Open

David B. Sher, Aftab Khan, Abdul Sattar, Muhammad Zeshan Tareen · 2025

This study explores the optimization and reliability of convolutional neural network (CNN) models, namely YOLOv5, for real-time object detection in autonomous vehicles under varying environmental conditions. The study intends to evaluate t…

Investigating a survey on assessing artificial intelligence technology: A key to futuristic perception of education Open

Anita Atwal, Aftab Khan · 2025

Perceptions of artificial intelligence: A study on academic fraternity of Sonipat district, Haryana, India Open

Aftab Khan, Anita Atwal · 2025

Large Generative AI Models meet Open Networks for 6G: Integration, Platform, and Monetization Open

Peizheng Li, Adrián Sánchez-Mompó, Tim Farnham, Aftab Khan, Adnan Aijaz · 2024

Generative artificial intelligence (GAI) has emerged as a pivotal technology for content generation, reasoning, and decision-making, making it a promising solution on the 6G stage characterized by openness, connected intelligence, and serv…

Investigating Quantum Machine Learning Frameworks and Simulating Quantum Approaches Open

Muhammad Jawad Khan, Stamatia Bibi, Muzammil Ahmad Khan, Huda Al Ali, Aftab Khan , et al. · 2024

Quantum machine learning (QML) has emerged as a promising field, combining the power of quantum computing with classical machine learning techniques to solve complex computational tasks. As the demand for efficient quantum simulations grow…

FLAME: Adaptive and Reactive Concept Drift Mitigation for Federated Learning Deployments Open

Ioannis Mavromatis, Stefano De Feo, Aftab Khan · 2024

This paper presents Federated Learning with Adaptive Monitoring and Elimination (FLAME), a novel solution capable of detecting and mitigating concept drift in Federated Learning (FL) Internet of Things (IoT) environments. Concept drift pos…

Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inference Open

Ioannis Mavromatis, K. B. Katsaros, Aftab Khan · 2024

Machine learning (ML) has seen tremendous advancements, but its environmental footprint remains a concern. Acknowledging the growing environmental impact of ML this paper investigates Green ML, examining various model architectures and hyp…

Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems Open

Jikun Gao, Ioannis Mavromatis, Peizheng Li, Pietro Carnelli, Aftab Khan · 2024

Federated learning (FL) systems face performance challenges in dealing with heterogeneous devices and non-identically distributed data across clients. We propose a dynamic global model aggregation method within Asynchronous Federated Learn…

Cybersecurity in Motion: A Survey of Challenges and Requirements for Future Test Facilities of CAVs Open

Ioannis Mavromatis, Theodoros Spyridopoulos, Pietro Carnelli, Woon Hau Chin, Ahmed Khalil , et al. · 2024

The way we travel is changing rapidly and Cooperative Intelligent Transportation Systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduces new risks and challenges, making cybersecurity a top prior…

UMBRELLA: A One-Stop Shop Bridging the Gap From Lab to Real-World IoT Experimentation Open

Ioannis Mavromatis, Yichao Jin, Aleksandar Stanoev, Anthony Portelli, Ingram Weeks , et al. · 2024

UMBRELLA (A Living Laboratory: https://www.umbrellaiot.com/) is an open, large-scale IoT ecosystem deployed across South Gloucestershire, UK. It is intended to accelerate innovation across multiple technology domains. UMBRELLA is built to …

Cybersecurity in Motion: A Survey of Challenges and Requirements for Future Test Facilities of CAVs Open

Ioannis Mavromatis, Theodoros Spyridopoulos, Pietro Carnelli, Woon Hau Chin, Ahmed Khalil , et al. · 2023

The way we travel is changing rapidly, and Cooperative Intelligent Transportation Systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduces new risks and challenges, making cybersecurity a top prio…

FROST: Towards Energy-efficient AI-on-5G Platforms -- A GPU Power Capping Evaluation Open

Ioannis Mavromatis, Stefano De Feo, Pietro Carnelli, Robert J. Piechocki, Aftab Khan · 2023

The Open Radio Access Network (O-RAN) is a burgeoning market with projected growth in the upcoming years. RAN has the highest CAPEX impact on the network and, most importantly, consumes 73% of its total energy. That makes it an ideal targe…

Multi-sensor, multi-device smart building indoor environmental dataset Open

Ufuk Erol, Francesco Raimondo, James Pope, Samuel Gunner, Vijay Kumar , et al. · 2023

Federated Deep Learning for Intrusion Detection in IoT Networks Open

Othmane Belarbi, Theodoros Spyridopoulos, Eirini Anthi, Ioannis Mavromatis, Pietro Carnelli , et al. · 2023

The vast increase of Internet of Things (IoT) technologies and the ever-evolving attack vectors have increased cyber-security risks dramatically. A common approach to implementing AI-based Intrusion Detection systems (IDSs) in distributed …

FLARE: Detection and Mitigation of Concept Drift for Federated Learning based IoT Deployments Open

T.T. Chow, Usman Raza, Ioannis Mavromatis, Aftab Khan · 2023

Intelligent, large-scale IoT ecosystems have become possible due to recent advancements in sensing technologies, distributed learning, and low-power inference in embedded devices. In traditional cloud-centric approaches, raw data is transm…

A Federated Learning-enabled Smart Street Light Monitoring Application: Benefits and Future Challenges Open

Diya Anand, Ioannis Mavromatis, Pietro Carnelli, Aftab Khan · 2022

Data-enabled cities are recently accelerated and enhanced with automated learning for improved Smart Cities applications. In the context of an Internet of Things (IoT) ecosystem, the data communication is frequently costly, inefficient, no…

A dataset of images of public streetlights with operational monitoring using computer vision techniques Open

Ioannis Mavromatis, Aleksandar Stanoev, Pietro Carnelli, Yichao Jin, Mahesh Sooriyabandara , et al. · 2022

A dataset of street light images is presented. Our dataset consists of ∼350 k images, taken from 140 UMBRELLA nodes installed in the South Gloucestershire region in the UK. Each UMBRELLA node is installed on the pole of a lamppost and is e…

Images of Public Streetlights with Operational Monitoring using Computer Vision Techniques Open

Ioannis Mavromatis, Aleksandar Stanoev, Pietro Carnelli, Yichao Jin, Mahesh Sooriyabandara , et al. · 2022

This dataset consists of ~350k JPEG images of streetlight columns installed on a public road infrastructure located in the city of Bristol, UK. Each streetlight is photographed by a Raspberry Pi Camera Module v1, installed on each lamppost…

Images of Public Streetlights with Operational Monitoring using Computer Vision Techniques Open

Ioannis Mavromatis, Aleksandar Stanoev, Pietro Carnelli, Yichao Jin, Mahesh Sooriyabandara , et al. · 2022

This dataset consists of ~350k JPEG images of streetlight columns installed on a public road infrastructure located in the city of Bristol, UK. Each streetlight is photographed by a Raspberry Pi Camera Module v1, installed on each lamppost…

An Intrusion Detection System Based on Deep Belief Networks Open

Othmane Belarbi, Aftab Khan, Pietro Carnelli, Theodoros Spyridopoulos · 2022

Towards Multi-Criteria Heuristic Optimization for Computational Offloading in Multi-Access Edge Computing Open

Raghubir Singh, Simon Armour, Aftab Khan, Mahesh Sooriyabandara, George Oikonomou · 2021

In recent years, there has been considerable interest in computational offloading algorithms. The interest is mainly driven by the potential savings that offloading offers in task completion time and mobile device energy consumption. This …

Deep Transfer Learning for WiFi Localization Open

Peizheng Li, Han Cui, Aftab Khan, Usman Raza, Robert J. Piechocki , et al. · 2021

This paper studies a WiFi indoor localisation technique based on using a deep learning model and its transfer strategies. We take CSI packets collected via the WiFi standard channel sounding as the training dataset and verify the CNN model…

Wireless Localisation in WiFi using Novel Deep Architectures Open

Peizheng Li, Han Cui, Aftab Khan, Usman Raza, Robert J. Piechocki , et al. · 2020

This paper studies the indoor localisation of WiFi devices based on a commodity chipset and standard channel sounding. First, we present a novel shallow neural network (SNN) in which features are extracted from the channel state informatio…

Identification of the Key Parameters for Computational Offloading in Multi-Access Edge Computing Open

Raghubir Singh, Simon Armour, Aftab Khan, Mahesh Sooriyabandara, George Oikonomou · 2020

Computational offloading is a strategy by which mobile device (MD) users can access the superior processing power of a Multi-Access Edge Computing (MEC) server network. This paper investigates the impact of CPU workloads (on both the user …

Table of Contents Open

Antonio Bucchiarone, Mirko Angelo, Danilo Pianini, Giacomo Cabri, Martina De Sanctis , et al. · 2020

Standing on the Shoulders of Giants: AI-Driven Calibration of Localisation Technologies Open

Aftab Khan, Tim Farnham, Roget Kou, Usman Raza, Thajanee Premalal , et al. · 2019

High accuracy localisation technologies exist but are prohibitively expensive to deploy for large indoor spaces such as warehouses, factories, and supermarkets to track assets and people. However, these technologies can be used to lend the…

Dataset: Indoor Localization with Narrow-band, Ultra-Wideband, and Motion Capture Systems Open

Usman Raza, Aftab Khan, Roget Kou, Tim Farnham, Thajanee Premalal , et al. · 2019

Localization Dataset README In this, data for BLE and UWB calibration is included through the use of UWB and OptiTrack Motion capture system respectively. There are two sets of data each covering two scenarios; these being…

Dataset: Indoor Localization with Narrow-band, Ultra-Wideband, and Motion Capture Systems Open

Usman Raza, Aftab Khan, Roget Kou, Tim Farnham, Thajanee Premalal , et al. · 2019

Localization Dataset README In this, data for BLE and UWB calibration is included through the use of UWB and OptiTrack Motion capture system respectively. There are two sets of data each covering two scenarios; these being…

The Advantage of Computation Offloading in Multi-Access Edge Computing Open

Raghubir Singh, Simon Armour, Aftab Khan, Mahesh Sooriyabandara, George Oikonomou · 2019

Computation offloading plays a critical role in reducing task completion time for mobile devices. The advantages of computation offloading to cloud resources in Mobile Cloud Computing have been widely considered. In this paper, we have inv…

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