1. Introduction: example applications {home, sports, health, cities, retail, transport}. 2. IoT ecosystems. 3. Business, Technology and Economic Drivers for IoT: anticipated benefits, 4. Changes to business processes and business models… 5. Legal challenges, privacy and security issues. 6. Societal implications, Persuasive technology and behavioural change, the quantified self. 7. IoT Services: brokering, big data analytics, dependability, maintainability. 8. IoT Sensing and Display modules; human interaction with IoT. 9. Data analysis and decision making. 10. Design methods and approaches.
Learning Outcomes
By the end of the module students should be able to:
Explain the layered architecture underpinning modern network models, and understand the implications of working in particular layers to IoT devices
Demonstrate how devices joining the network are able to obtain identities and communicate with other devices
Use integral transforms proficently
Estimate data loss within the communications channel used, and contextualise that information with respect to the potential impacts on the task being performed
Understand the impact of different web service paradigms on the delivery of data to / from IoT devices
Devise / select appropriate models for data exchange between IoT devices, taking into account key properties such as the need to retain data context, effective use of available bandwidth, and timeliness of delivery
Secure IoT devices from common attacks
Assessment
Assessment Methods & Exceptions
Assessment 25% assessed by design report (1000 words) 75% assessed by 3 hour written unseen exam