INTERNET OF THINGS

SHE Level 5
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code MMI123998
Module Leader Peter Barrie
School School of Computing, Engineering and Built Environment
Subject Computing
Trimester
  • B (January start)

Summary of Content

This module provides fundamental and practical coverage of the set of converging technologies known as the Internet of Things (IoT). It focuses on representative IoT applications, technologies, frameworks and associated standards that support and underpin IoT applications, such as sensor networks, messaging protocols, security, data storage, analytics, services and human interaction. The module provides in-depth practical coverage of representative IoT implementation frameworks incl uding cloud-based service delivery models.

Syllabus

IoT application domains and related business-awareness. Societal impact. Historical perspective related to machine-to-machine (M2M) systems. Technology evolution and convergence of consumer, business and industrial Internet. IoT architectural models. Enabling technologies. Overview of Wireless Sensor Networks. Reliable and secure messaging for IoT. Service-oriented architectures and cloud-based computing for IoT. Data collection, management and analysis. Complex event processing. High velocity data processing. Privacy, security and governance. The role of standardisation. Critically appraisal of current IoT platforms such as IBM Bluemix and Microsoft Azure IoT. Implementation of end-to-end solutions using industry-standard technology frameworks, including cloud-based computing with web-services. Challenges for IoT industry applications. IoT case studies in representative areas such as smart cities, transportation, health and smart buildings. IoT strategic research directions. Knowledge of international affairs. Examples of tasks undertaken by students in practical sessions are: -360b7 Configuring and applying a wireless-sensor-network. b7 Using messaging protocols to connect to cloud-based IoT services. b7 Implementing cloud-based analytics for IoT. b7 Generating actions based on data-analytics. b7 Implementing an end-to-end solution for IoT. b7 Building human-interfaces for IoT systems.

Learning Outcomes

On successful completion of this module a student should be able to:Demonstrate in-depth knowledge of the requirements and implementation strategies for a representative range of IoT applications.Demonstrate a detailed understanding of how IoT applications can add value to business, industry and society.Critically appraise IoT technology, standards and services including cloud system technology, architecture and deployment models.Demonstrate the ability to analyse and solve representative problems in the IoT domain.Develop IoT applications that generate/process data-streams, provide cloud-based storage, provide/consume analytical services and feature appropriate human interfaces.

Teaching / Learning Strategy

The learning and teaching strategy for this module has been informed by the university's 'Strategy for Learning' design principles. The course material is introduced through lectures and laboratory sessions that draw upon and extend the lecture material to deepen students' knowledge. The laboratory sessions are designed as a set of formative exercises and a substantial summative exercise spanning several weeks. The formative exercises introduce a range of technologies that allow students to gain confidence and build knowledge of the range of solutions that can be applied to particular problems. Summative exercises provide experience in real-world problem-solving and challenges students to demonstrate analytical skills and capacity for divergent thinking. Tutorials will be used to help explain and elaborate on both the lecture material and the laboratory exercises; these will include a range of case studies that bring a global perspective to the subject matter. During all lab and tutorial sessions students receive formative feedback on their performance in undertaking the laboratory and tutorial exercises. Summative feedback and grades are also provided for the coursework assignments undertaken as part of the module, using GCULearn. GCU Learn is also used to provide the students with module specific Forums and Wikis to stimulate student and lecturer interaction outwith the normal lecture, laboratory and tutorial sessions. Flexible learning is encouraged and supported. All teaching materials and self-testing exercises are made available on GCULearn and links are provided to external materials such as podcasts, MOOCs, videos and relevant literature. All the computing resources used for laboratories are made available either by virtual machine images (supplied to students for use on their own computers) or online using industry standard cloud computing services provided by major global computing industry vendors. Due to the provision of all material and computing facilities online, the module is suitable for use where Flexible and Distributed Learning (FDL) is required. Small items of IoT hardware are made available as loan items to all students; the outcome of this provision is that students can access complete laboratory facilities in their own time.

Indicative Reading

" Rethinking the Internet of Things, A Scalable Approach to Connecting Everything." Author: Francis daCosta. Publication Date: January 6, 2014 ISBN13: 978-1-4302-5740-0 Internet of Things Worms: http://iotworm.com/ IoT Case studies, technologies and societal impact. Good coverage of wearable technology, smart cities, healthcare, smart manufacturing, innovation. IEEE Internet of Things: http://iot.ieee.org/ IoT News Network : http://www.iotnewsnetwork.com/ Introduction to IBM Bluemix: www.ibm.com/Bluemixfd http://www.ibm.com/Bluemix https://www.youtube.com/watch?v=8GZq9uV73sE https://www.youtube.com/watch?v=XePkWytg_-M Microsoft IoT: https://www.microsoft.com/en-gb/server-cloud/internet-of-things/overview.aspx Dr. John Bates. "Thingalytics: Smart Big Data Analytics for the Internet of Things": http://thingalyticsbook.com/ "Big Data and The Internet of Things: Enterprise Information Architecture for A New Age" 2015th Edition by Robert Stackowiak, Art Licht, Venu Mantha and Louis Nagode : http://www.amazon.com/Big-Data-The-Internet-Things/dp/1484209877 Three Free Big Data books from O'Reilly on Amazon: http://www.kdnuggets.com/2013/10/3-free-big-data-books-from-amazon.html

Transferrable Skills

D1 Specialist knowledge and application D2 Critical thinking and problem solving D3 Critical analysis D4 Communication skills, written, oral and listening D6 Effective information retrieval and research skills D7 Computer literacy D8 Self-confidence, self-discipline & self-reliance (independent working) D9 Awareness of strengths and weaknesses D10 Creativity, innovation & independent thinking D11 Knowledge of international affairs D14 Ability to prioritise tasks and time management D17 Commercial awareness

Module Structure

Activity Total Hours
Lectures (FT) 24.00
Assessment (FT) 20.00
Independent Learning (FT) 120.00
Practicals (FT) 24.00
Tutorials (FT) 12.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 1 n/a 50.00 45% Report on IoT applications and underpinning technologies. (approx. 2000 words)
Coursework 2 n/a 50.00 45% Analysis, design, development and demonstration of a complete IoT application.