This module will look at the following generic topics:

Overview and principles of ambient systems

Ambient system domains – context aware, ubiquitous, pervasive, location, health, informational, operational, etc.

Characteristics of Intelligent environments (adaptive, responsive, and embedded)

Key elements and technologies associated to ambient systems
- Ethical, privacy, and responsible design considerations
- Architecture of ambient and context-aware systems (edge, cloud, IoT integration (light-touch))

Data in ambient systems (e.g. sensor, time-series, multi-modal data)

Context-aware computing: context modelling and reasoning techniques
- Context-Aware Computing concepts and definitions
- Types of contexts (e.g. location, time, activity, social, environmental)
- Context modelling approaches (e.g. key-value structures, ontologies) to support context-aware system design
- Behaviour modelling and user profiling
- User modelling techniques
- Overview of activity recognition approaches in context-aware systems
- Interpretation of behavioural patterns in context-aware environments
- Personal data and profiling implications

Personalisation and adaptive systems
- Adaptive system design principles
- Recommendation and personalisation concepts
- Context-driven adaptation (e.g. smart environments responding to users)

Human-centred design and user experience in intelligent environments

Current standards and quality processes in development

Team working roles within the industry and management processes

Enterprise, Entrepreneurship, and Innovation within Artificial Intelligence

Stakeholder and users roles and requirements

Small to large project address, issues of scalability and problem solving

Design process from requirements through to implementation

Risks and identification of these throughout design

Design and Architectural Patterns in ambient systems

User centric design and approaches (societal, and environmental impact of designs)
- Key focus on users accessibility and inclusion

Testing and proving success in developments

Quality, metrics, testing, and process improvement

Professional, legal, and ethical, societal, and environmental issues

Areas current and emerging related to research into ambient systems

Development platforms, architectures and development environments

Costing models and trade-offs

Designing for sustainability

BCS / TechSkills / Employability elements:

Application process, design, evaluation and trade-off approaches.

Teamworking and individual roles within ambient systems development.

Enterprise, Entrepreneurship, and opportunity in Artificial Intelligence and Ambient Systems.

PRESENTATION - The presentation (team based) is to be used to demonstrate solutions to a set of simulated stakeholder requirements which have be translated into designs, implementation, and testing documentation related to components of an ambient system, following existing industry standards and best practices. Teams will discuss and present their end solution in a simulated showcase style 30-minute presentation. Each team member must be allocated an equal amount of time within the presentation and use this to showcase part of the created solution and their specific contribution to it.

REPORT – This is an individual reflective report, which represents an account of the student’s learning and skill development during the module. The reflection needs to identify entrepreneurship, innovations and any career considerations that have developed through completing the assessment.

Formative assessment opportunities will be provided throughout the module. For the presentation staff will review your draft ideas and guide you further in forming your final presentation. There will also be a practice session where you can have a practice run of your final presentation. For the individual reflective report staff will regularly guide you as to progress milestone’s, and will also review a single draft when near to hand in.

The module will be delivered through a combination of weekly lectures and tutorial sessions over the semester. Lectures will introduce key concepts in ambient intelligence and context-aware systems, while tutorials will provide hands-on, workshop-style activities where students analyse simulated datasets, apply context modelling techniques, and engage in problem-solving tasks. Sessions will also include discussions, case studies, and group-based activities to encourage critical thinking and peer learning. In addition, students will be supported through guided independent study, formative exercises, and drop-in support sessions to assist with coursework and practical elements of the module.

1. Design, create and test artefact solutions to solve complex problems in the ambient systems domain as part of a development team.

Application & Problem Solving
Digital Literacy

2. Critically evaluate the features and processes involved in developing ambient system-based applications through teamwork.

Knowledge and Understanding
Critical Reasoning & Collaboration

3. Investigate, analyse, research and evaluate ambient systems development from the perspective of both developer and provided user experience, being able to communicate effectively to both audiences.

Communication
Research Skills

4. Reflect critically on personal skills developed during the production of ambient systems using industry standards and technologies, in relation to a future career.

Reflection
Personal Development and Entrepreneurship

Virtual Learning Environment (e.g. Blackboard) and collaboration tools (e.g. Microsoft Teams) for accessing learning materials, communication, and assessment submission

Data analysis and visualisation tools (e.g. Python, Jupyter Notebook, Microsoft Excel, Power BI) to support exploration and interpretation of simulated ambient datasets

Sample datasets and scenario-based materials representing intelligent environments (e.g. smart homes, healthcare, workplace settings) to support practical and simulation-based learning

Reporting and presentation tools (e.g. Microsoft Word, Microsoft PowerPoint) for coursework preparation and communication of findings

University Library resources, including access to academic databases and digital journals (e.g. Google Scholar), to support independent study and research

Joshi, A. (2023), Artificial Intelligence and Human Evolution: Contextualizing AI in Human History. 1st ed. Berkeley, CA: Apress

Markakis, E.K. and Panagiotakis, S. (2024), Pervasive Computing in IoT. MDPI - Multidisciplinary Digital Publishing Institute

Bravo, j. et. al. (2026), Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2 (Lecture Notes in Networks and Systems, 1819), Springer

Bornet, P. (2025), Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work and Life, Young Press

Mishra, A. (2025), AI 2025: The Future Unfolded - Top Trends Reshaping Business Society & Innovation (Artificial Intelligence & Machine Learning), Access Press Group

How do intelligent environments understand and respond to you? In this module, you’ll explore the foundations of ambient intelligence and context-aware systems, learning how data from sensors and user interactions is used to model context, behaviour, and adaptive responses. You’ll examine key topics including context modelling, user profiling, personalisation, and human-centred design, alongside ethical and privacy considerations. Through applied and simulation-based activities, you’ll develop skills in interpreting ambient data and designing intelligent system behaviours, supporting your development in AI-driven and data-centric careers.