Outputs (22)

AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture (2023)
Journal Article
Masood, F., Khan, W. U., Jan, S. U., & Ahmad, J. (2023). AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture. Sensors, 23(19), Article 8218. https://doi.org/10.3390/s23198218

Smart agricultural systems have received a great deal of interest in recent years because of their potential for improving the efficiency and productivity of farming practices. These systems gather and analyze environmental data such as temperature,... Read More about AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture.

Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0 (2023)
Journal Article
Siddique, A. A., Boulila, W., Alshehri, M. S., Ahmed, F., Gadekallu, T. R., Victor, N., …Ahmad, J. (2023). Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0. IEEE Transactions on Consumer Electronics, ht

Pneumonia is a significant global health concern that can lead to severe and sometimes fatal consequences. Timely identification and classification of pneumonia can substantially improve patient outcomes. However, the disclosure of sensitive medical... Read More about Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0.

Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning (2023)
Journal Article
Shah, S. A., Abbasi, Q. H., Ahmad, J., & Imran, M. A. (2023). Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning. Electronics, 12(19), Article 3990. https://doi.org/10.3390/electronics12193990

FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices (2023)
Journal Article
Ahmad, K., Khan, M. S., Ahmed, F., Driss, M., Boulila, W., Alazeb, A., …Ahmad, J. (2023). FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices. Fire Ecology, 19, Article 54. https://doi.or

Background: Forests cover nearly one-third of the Earth’s land and are some of our most biodiverse ecosystems. Due to climate change, these essential habitats are endangered by increasing wildfires. Wildfires are not just a risk to the environment, b... Read More about FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices.

Enhancing IoT network security through deep learning-powered Intrusion Detection System (2023)
Journal Article
Bakhsh, S. A., Khan, M. A., Ahmed, F., Alshehri, M. S., Ali, H., & Ahmad, J. (2023). Enhancing IoT network security through deep learning-powered Intrusion Detection System. Internet of Things, 24, Article 100936. https://doi.org/10.1016/j.iot.2023.100936

The rapid growth of the Internet of Things (IoT) has brought about a global concern for the security of interconnected devices and networks. This necessitates the use of efficient Intrusion Detection System (IDS) to mitigate cyber threats. Deep learn... Read More about Enhancing IoT network security through deep learning-powered Intrusion Detection System.

Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications (2023)
Journal Article
Saeed, U., Shah, S. A., Ghadi, Y. Y., Khan, M. Z., Ahmad, J., Shah, S. I., …Abbasi, Q. H. (2023). Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications. IEEE Sensors Journal, 23(19),

This study proposes a secure and effective lips-reading system that can accurately detect lips movements, even when face masks are worn. The system utilizes radio frequency (RF) sensing and ultra-wideband (UWB) radar technology, which overcomes the c... Read More about Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications.

A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data (2023)
Presentation / Conference Contribution
Naz, N., Khan, M. A., Khan, M. A., Khan, M. A., Jan, S. U., Shah, S. A., …Ahmad, J. (2023). A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data. In Advances on Intelligent Computing and Data Science. ICACIn 2022 (451-462). https

The Internet of Things (IoT) is a grid of interconnected pre-programmed electronic devices to provide intelligent services for daily life tasks. However, the security of such networks is a considerable obstacle to successful implementation. Therefore... Read More about A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data.

An efficient deep learning model for brain tumour detection with privacy preservation (2023)
Journal Article
Rehman, M. U., Shafique, A., Khan, I. U., Ghadi, Y. Y., Ahmad, J., Alshehri, M. S., …Zayyan, M. H. (in press). An efficient deep learning model for brain tumour detection with privacy preservation. CAAI Transactions on Intelligence Technology, https://d

Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific c... Read More about An efficient deep learning model for brain tumour detection with privacy preservation.

A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks (2023)
Journal Article
Khan, N. W., Alshehri, M. S., Khan, M. A., Almakdi, S., Moradpoor, N., Alazeb, A., …Ahmad, J. (2023). A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks. Mathematical Biosciences and Engineering, 20(8), 13491-13520. https://doi.org

The Internet of Things (IoT) is a rapidly evolving technology with a wide range of potential applications, but the security of IoT networks remains a major concern. The existing system needs improvement in detecting intrusions in IoT networks. Severa... Read More about A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks.

Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants (2023)
Journal Article
Tahir, H., Shahbaz Khan, M., Ahmed, F., M. Albarrak, A., Noman Qasem, S., & Ahmad, J. (2023). Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants. Computers, Materials & Continua, 75(2), 3517-3535. https://doi.org/10.32

The COVID-19 outbreak began in December 2019 and was declared a global health emergency by the World Health Organization. The four most dominating variants are Beta, Gamma, Delta, and Omicron. After the administration of vaccine doses, an eminent dec... Read More about Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants.