Computer Science (Mobile and Ubiquitous Computing)

Course Structure

1. ["Visions of mobile and ubiquitous computing gives students a broad knowledge of the current development in the area of mobile and ubiquitous computing and familiarises them with the most significant of the many `visions\' that guide ongoing research in the area.", \'Data communications and wireless networking provides in-depth theoretical and practical knowledge of Internet protocols and the most important wireless communication standards in current and likely future use along with their strengths and weaknesses.\', \'Embedded systems addresses the development of complex embedded systems that control real-world artefacts by taking input from a variety of sensors and acting on the assessment of this data.\', \'Middleware for mobile and ubiquitous computing covers the most important paradigms for building distributed applications for use in mobile and ubiquitous computing settings.\', \'Sensing and context awareness covers advanced sensing techniques for ubiquitous computing and the techniques used to build highly contextualized systems that adapt to their users, tasks, and environments.\', \'Human computer interaction and design addresses the main issues underlying the usability of systems and the main techniques and processes for interaction. It gives students a firm understanding of the principles of information design and of usability problems in interactive system design, the reasons underlying these problems and the methods which have been developed to address these issues within systems development.\', \'Knowledge management explores the management, delivery and inter-operability of information and information systems as well as machine learning and inference techniques. It includes such areas as integration of heterogeneous information repositories, schema and semantic (ontology) representation, adaptive hypermedia transformation and delivery, and dynamic semantic web service composition.\', \'Computer vision is a practical course where along with gaining an understanding of the theory underlying the processing and interpretation of visual information, students are encouraged to apply the theory to realistic problems to gain practical experience of the difficulties involved in developing computer vision solutions .\']