معرفی
Baseer Ahmad is a Lecturer in Robotics and Artificial Intelligence at the School of Computer Science, Faculty of Science and Engineering, University of Hull. His work bridges embedded systems, IoT, and machine learning with applications in predictive maintenance, smart cities, and environmental monitoring. He is affiliated with the Computer Science research group and contributes to the Data Science, AI and Modelling Centre.
His research interests include:
- Intelligent Predictive Maintenance
- Artificial Intelligence and Deep Learning
- Internet of Things (IoT) and Wireless Sensor Networks
- Embedded Electronics Systems
- Industrial Control Systems
- Renewable Energy Monitoring
His recent work focuses on applying AI and IoT to real-world industrial and environmental challenges. This includes developing predictive maintenance frameworks for lifts, designing fire-safe and EMI-resistant hardware for real-time monitoring, and creating scalable IoT solutions for smart cities using LoRaWAN. His publications highlight trends in using sensor data for health and industrial applications, particularly in indoor air quality and machine fault prediction.
He has secured research funding as a co-investigator on an Innovate UK project titled 'Adopting a Circular Economy Business Model for Resource Efficiency in ICT industry (ACE4ICT)', with a grant of £89,238. He previously worked on the European Commission-funded SCORE project, integrating environmental sensors into mesh and LoRaWAN networks.
Baseer Ahmad is available for PhD supervision in areas such as predictive maintenance, WSN, indoor positioning systems, embedded systems, and IoT. He has supervised research topics but no named students are listed. He is involved in research labs and groups including the Dependable Intelligent Systems and the Data Science, AI and Modelling Centre, where he contributes to interdisciplinary projects combining hardware and software for intelligent monitoring systems.
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