Dr Muhammad Khalid's Outputs (20)

LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing (2025)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Majid, A. (online). LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing. IEEE internet of things journal, https://doi.org/10.1109/JIOT.2025.3549374

Traditional RF-based liquid identification methods generally rely on a single characteristic such as refractive index or permittivity and often assume prior container knowledge, limiting their versatility. These approaches also face challenges in sce... Read More about LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing.

An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications † (2025)
Journal Article
Arshad, M., Liu, |., Khalid, |. M., Liu, Y., Wang, P., & Arshad, M. (online). An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †. International Journal of Satellite Communications and Networking, https://doi.org/10.1002/sat.1560

Satellite communication has gained significant attention in the context of sixth-generation (6G) internet technology. Due to their high altitudes, dynamic link switching, and limited resources, satellite nodes are prone to higher bit error rates and... Read More about An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †.

Combined Oriented Data Augmentation Method for Brain MRI Images (2025)
Journal Article
Farhan, A. S., Khalid, M., & Manzoor, U. (2025). Combined Oriented Data Augmentation Method for Brain MRI Images. IEEE Access, 13, 9981-9994. https://doi.org/10.1109/ACCESS.2025.3526684

In recent years, deep learning’s use in medical imaging has grown exponentially. However, one of the biggest problems with training deep learning models is the unavailability of large amounts of data, which leads to overfitting. Collecting large quan... Read More about Combined Oriented Data Augmentation Method for Brain MRI Images.

mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology (2024)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Niaz, A. (online). mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology. IEEE Transactions on Mobile Computing (TMC), https://doi.org/10.1109/TMC.2024.3520914

Wireless sensing offers a promising approach for non-destructive and contactless identification of the moisture content in fruits. Traditional methods assess fruit quality based on external features such as color, shape, size, and texture. However, f... Read More about mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology.

LLM Based Cross Modality Retrieval to Improve Recommendation Performance (2024)
Presentation / Conference Contribution
Anwaar, F., Khan, A. M., & Khalid, M. (2024, August). LLM Based Cross Modality Retrieval to Improve Recommendation Performance. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, UK

The metadata of items and users play an important role in improving the decision-making process in the Recom-mender System. In recent times, web scraping-based techniques have been widely utilized to extract explicit user and item meta-data from diff... Read More about LLM Based Cross Modality Retrieval to Improve Recommendation Performance.

mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor (2024)
Journal Article
Niaz, F., Zhang, J., Zheng, Y., Khalid, M., & Niaz, A. (online). mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor. ACM Transactions on Sensor Networks, https://doi.org/10.1145/3694970

Target material sensing in non-invasive and ubiquitous contexts plays an important role in various applications. Recently, a few wireless sensing systems have been proposed for material identification. In this paper, we introduce mm-CUR, A Novel Ubiq... Read More about mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor.

AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor (2024)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Qureshi, K. N., Zheng, Y., Younas, M., & Imran, N. (in press). AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor. Computing, https://doi.org/10.1007/s00607-024-01300-2

In recent years, the significance of millimeter wave sensors has achieved a paramount role, especially in the non-invasive and ubiquitous analysis of various materials and objects. This paper introduces a novel IoT-based fake currency detection using... Read More about AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor.

Probabilistic model-checking of collaborative robots: a human injury assessment in agricultural applications (2024)
Journal Article
Guevara, L., Khalid, M., Hanheide, M., & Parsons, S. (2024). Probabilistic model-checking of collaborative robots: a human injury assessment in agricultural applications. Computers and Electronics in Agriculture, 222, Article 108987. https://doi.org/10.1016/j.compag.2024.108987

Current technology has made it possible to automate a number of agricultural processes that were traditionally carried out by humans and now can be entirely performed by robotic platforms. However, there are certain tasks like soft fruit harvesting,... Read More about Probabilistic model-checking of collaborative robots: a human injury assessment in agricultural applications.

Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach (2024)
Thesis
Dulian, . A. Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4625808

Complex environments manifest a high level of complexity and it is of critical importance that the safety systems embedded within autonomous vehicles (AVs) are able to accurately anticipate short-term future motion of agents in close proximity. This... Read More about Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach.

Access Authentication Via Blockchain in Space Information Network (2024)
Journal Article
Arshad, M., Jianwei, L., Khalid, M., Khalid, W., Cao, Y., & Khan, F. A. (2024). Access Authentication Via Blockchain in Space Information Network. PLoS ONE, 19(3), Article e0291236. https://doi.org/10.1371/journal.pone.0291236

These authors contributed equally to this work. Abstract Space Information Network (SIN) has significant benefits of providing communication anywhere at any time. This feature offers an innovative way for conventional wireless customers to access enh... Read More about Access Authentication Via Blockchain in Space Information Network.

AI-Based Hand Gesture Recognition Through Camera on Robot (2024)
Presentation / Conference Contribution
Csonka, G., Khalid, M., Rafiq, H., & Ali, Y. (2023, December). AI-Based Hand Gesture Recognition Through Camera on Robot. Presented at 2023 International Conference on Frontiers of Information Technology (FIT), Islamabad

This paper presents an innovative approach to real-time hand gesture recognition for robot control using Artificial Intelligence (AI). The core of this project is a machine learning model trained on a custom data set of hand gestures, which was metic... Read More about AI-Based Hand Gesture Recognition Through Camera on Robot.

Deep reinforcement learning based Evasion Generative Adversarial Network for botnet detection (2023)
Journal Article
Randhawa, R. H., Aslam, N., Alauthman, M., Khalid, M., & Rafiq, H. (2024). Deep reinforcement learning based Evasion Generative Adversarial Network for botnet detection. Future generations computer systems : FGCS, 150, 294-302. https://doi.org/10.1016/j.future.2023.09.011

Botnet detectors based on machine learning are potential targets for adversarial evasion attacks. Several research works employ adversarial training with samples generated from generative adversarial nets (GANs) to make the botnet detectors adept at... Read More about Deep reinforcement learning based Evasion Generative Adversarial Network for botnet detection.

Autonomous valet parking optimization with two-step reservation and pricing strategy (2023)
Journal Article
Hu, Z., Cao, Y., Li, X., Zhu, Y., Khalid, M., & Ahmad, N. (2023). Autonomous valet parking optimization with two-step reservation and pricing strategy. Journal of Network and Computer Applications, 219, Article 103727. https://doi.org/10.1016/j.jnca.2023.103727

With the development of autonomous vehicle, the autonomous valet parking has been attracting extensive attention, by relieving users’ inconvenience from parking. Compared with shortrange autonomous valet parking, long-range autonomous valet parking e... Read More about Autonomous valet parking optimization with two-step reservation and pricing strategy.

Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review (2023)
Journal Article
Ali, Y., Ullah Khan, H., & Khalid, M. (2023). Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review. Journal Of Big Data, 10(1), Article 128. https://doi.org/10.1186/s40537-023-00805-5

Internet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of service (DDoS) attacks, intrusions, malwares,... Read More about Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review.

Symmetry-based decomposition for optimised parallelisation in 3D printing processes (2023)
Journal Article
Hatton, H., Khalid, M., Manzoor, U., & Murray, J. (2023). Symmetry-based decomposition for optimised parallelisation in 3D printing processes. International Journal of Advanced Manufacturing Technology, 127, 2935–2954. https://doi.org/10.1007/s00170-023-11205-7

Current research in 3D printing focuses on improving printing performance through various techniques, including decomposition, but targets only single printers. With improved hardware costs increasing printer availability, more situations can arise i... Read More about Symmetry-based decomposition for optimised parallelisation in 3D printing processes.

Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging (2022)
Journal Article
Ahmad, A., Khalid, M., Ullah, Z., Ahmad, N., Aljaidi, M., Malik, F. A., & Manzoor, U. (2022). Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging. Energies, 15(24), Article 9471. https://doi.org/10.3390/en15249471

The rise of the intelligent, local charging facilitation and environmentally friendly aspects of electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still numerous challenges faced by researchers trying to put EVs... Read More about Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging.

Deep reinforcement learning-based long-range autonomous valet parking for smart cities (2022)
Journal Article
Khalid, M., Wang, L., Wang, K., Aslam, N., Pan, C., & Cao, Y. (2023). Deep reinforcement learning-based long-range autonomous valet parking for smart cities. Sustainable Cities and Society SCC, 89, Article 104311. https://doi.org/10.1016/j.scs.2022.104311

In this paper, to reduce the congestion rate at the city center and increase the traveling quality of experience (QoE) of each user, the framework of long-range autonomous valet parking is presented. Here, an Autonomous Vehicle (AV) is deployed to pi... Read More about Deep reinforcement learning-based long-range autonomous valet parking for smart cities.

A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations (2022)
Presentation / Conference Contribution
Aljaidi, M., Aslam, N., Chen, X., Kaiwartya, O., Al-Gumaei, A., & Khalid, M. (2022, June). A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations. Presented at 2022 IEEE 95th Vehicular Technology Conference: VTC2022-Spring, Helsinki, Finland

Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the number of electric vehicles (EVs) increases, the public charging infrastructure needs to adopt efficient charg... Read More about A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations.

Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach (2022)
Journal Article
Khan, S., Khan, S., Ali, Y., Khalid, M., Ullah, Z., & Mumtaz, S. (2022). Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach. Journal of Network and Systems Management, 30, Article 29. https://doi.org/10.1007/s10922-021-09636-2

In current era, the next generation networks like 5 th generation (5G) and 6 th generation (6G) networks requires high security, low latency with a high reliable standards and capacity. In these networks, reconfigurable wireless network slicing is co... Read More about Highly Accurate and Reliable Wireless Network Slicing in 5 th Generation Networks: A Hybrid Deep Learning Approach.

Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology (2022)
Journal Article
Ahmad, A., Ullah, Z., Khalid, M., & Ahmad, N. (2022). Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology. Applied Sciences, 12(2), Article 904. https://doi.org/10.3390/app12020904

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As com... Read More about Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology.