Non-Invasive and Semantic-based IoT stream processing framework with Agentic AI for Next-Generation Trustworthy Wearable and Ambient Systems

About the Project

Wearable Internet of Things (IoT) devices such as smartwatches, health trackers, and fall detectors are revolutionising healthcare, assisted living, and safety-critical systems. However, challenges remain around trust resulting from data quality (Bamgboye, Liu, Cruickshank, & Liu., 2025), and data reliability due to sensor accuracy or failure. Many current solutions depend on intrusive sensing, which can undermine comfort and compliance, while traditional trust models struggle to cope with the demands of highly dynamic IoT environments (Wei, Yang, Wu, Long, & Li, 2022). This PhD project seeks to address these barriers by combining non-invasive computing approaches (e.g., software-side data/signal cleansing in ambient and contactless monitoring) with agentic AI techniques, offering a step-change in how we design trustworthy stream quality focussed IoT systems.

The research will develop a unified trust management framework that integrates semantic knowledge graphs, scalable and interoperable edge/cloud architectures, and autonomous AI agents capable of adaptive trust negotiation and high-quality data stream availability. By embedding agentic AI, the system will self-learn, self-heal, and adapt to changing conditions, while non-invasive methods will reduce user burden and increase acceptance (Shipunova, Berezovskaya, Pozdeeva, Evseeva, & Barlybayeva, 2022). Together, these innovations will improve the reliability, scalability, and IoT stream quality-enabled trustworthiness of wearable and ambient IoT technologies.

Applications will be explored in critical domains such as Ambient Assisted Living and digital health, where unobtrusive monitoring is vital for elderly care, chronic disease management, and remote patient support. The project aligns with societal priorities in digital trust, healthcare innovation, and responsible AI, offering the opportunity for a PhD researcher to shape next-generation IoT systems that are not only intelligent but also ethical, inclusive, and impactful.

If you are passionate about building technologies that are not only intelligent but also trusted, inclusive, and impactful, this PhD offers a unique opportunity to lead innovation in one of the most exciting areas of computing today. You will work at the intersection of emerging technologies and societal impact, with opportunities to develop expertise in agentic AI, non-invasive computing, and edge/cloud IoT software architectures.

Academic qualifications

Have, or expect to achieve by the time of start of the studentship a first-class honours degree, or a distinction at master level, ideally in Computer Science, Software Engineering, AI/ML, or equivalent numerate discipline with good fundamental knowledge of Software Engineering, Internet of Things, Semantic Technologies and Modelling, Machine Learning including Artificial Intelligence, and Cloud/edge Computing

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

• Only a first-class honours degree, or a distinction at master level in a subject relevant to the PhD project will be considered, or equivalent achievements.
• Good familiarity with Software Engineering process and Programming languages
• Competent in scientific research
• Good knowledge of IoT
• Good written and Oral communication skills
• Strong motivation and evidence of undertaking independent research
• Excellent Time management

Desirable attributes:

• Practical experience in research or industry will be considered an advantage.
• Familiarity with data processing and analysis of wearable IoT
• Understanding of large graph models
• Generative AI

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.
• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use

• the advertised title as project title

For informal enquiries about this PhD project, please contact O.Bamgboye@napier.ac.uk