INTERNET OF THINGS - 2024/5

Module code: COM3023

Module Overview

Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. The resulting framework, known as the Internet of Things (IoT), incorporates several technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, and distributed systems.

The IoT module is designed to provide a comprehensive understanding of how machine communications contribute to creating smart, artificial intelligence-driven environments focusing on software networking and communication systems. The module provides an overview of the key concepts and enabling technologies for the Internet of Things. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for IoT across physical, media access, and network layers. This includes security considerations, satellite IoT, positioning and tracking for industrial applications, IoT Platforms (Hardware, Software), protocols and standards (e.g., 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module seamlessly integrates cutting-edge machine learning techniques tailored for IoT applications, ensuring optimal performance and adaptability.

Module provider

Computer Science and Electronic Eng

Module Leader

ELZANATY Ahmed (CS & EE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): 43

Overall student workload

Independent Learning Hours: 90

Lecture Hours: 20

Laboratory Hours: 10

Guided Learning: 10

Captured Content: 20

Module Availability

Semester 1

Prerequisites / Co-requisites

None. Expected prior/parallel learning:  Basic knowledge of hardware systems and Object Oriented Programming and C++, or equivalent knowledge of C++ or of Java programming.

Module content

Indicative content includes the following.


  • Introduction to the module, basic concepts in the Internet of Things domain, and the state of the art in technologies that are used to enable the Internet of Things systems, services and applications

  • Cyber-physical systems, smart devices, sensors, and actuators

  • Architectures and radio access technologies for Internet of Things

  • Software platforms and services

  • Intelligent data processing and semantic technologies

  • Reliability, security, privacy, and trust issues and solutions

  • Enabling technologies for low power wide area networks

  • Localization and tracking for Internet of Things

  • Machine learning/artificial intelligence for Internet of Things


Assessment pattern

Assessment type Unit of assessment Weighting
Coursework COURSEWORK 20
Examination Invigilated (Closed BOOK) EXAM WITHIN A 2-HOUR WINDOW 80

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the learning outcomes. The written examination will assess the knowledge, concepts and theory of key technologies, common protocols, and relevant techniques on the Internet of Things area, as well as the ability to analyse problems and apply the common solutions and techniques to solve different uses-case scenarios in this domain. The Assignment will assess the ability to design a basic Internet of Things system using a common platform and will also evaluate the ability to critically analyse an existing work in a related area.

Summative assessment


  • A programming assessment implementing a sensor node application.


  • Invigilated (Closed book) examination within a 2-hour window



Formative assessment and feedback


  • For the module, students will receive formative assessment/feedback in the following ways.

  • During lectures, e.g., question and answer sessions

  • During supervised computer laboratory sessions

  • During the seminar and class discussion

  • Via the marking of the written report

  • Via assessed coursework


Module aims

  • introduce the fundamental concepts of the Internet of Things and its applications and architecture models, followed by an introduction to the technologies and mechanisms for sensing, actuation, processing and cyber-physical data communication
  • To explore the modularity of IoT systems and their applications in the fields of communication systems and computer vision, robotics, and machine learning.
  • To offer hands-on experience through 20-hour labs covering embedded programming.
  • Enable students to develop practical skills that can be transferred into a real-world environment.
  • Discuss semantic technologies, service oriented solutions and networking technologies that enable the integration of Internet of Things data and services into the cyber world (i.e. the Internet and the Web).
  • To incorporate machine learning techniques in the context of IoT applications.
  • The module also aims to provide opportunities for students to learn about the Surrey Pillars listed below.

Learning outcomes

Attributes Developed
Ref
001 Explain the key concepts of the Internet of Things and its enabling technologies KC M1, M2
002 Apply software development concepts such as machine learning and techniques for embedded Internet of Things system PT M12, M16, M17
003 Describe the principles of design and development of Internet-of-Things systems and applications KCPT M5, M6
004 Describe and evaluate theoretical concepts and apply them to practical examples and use-cases KCPT M1, M3, M7
005 Describe and discuss recent developments, protocols, and technologies for the Internet of Things, such as 6LowPAN and CoAp PT M10, M14

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to achieve the following aims.

This module is designed to provide up-to-date knowledge that will enhance and extend the students’ theoretical and practical skills in related areas and will also improve their analytical and problem solving skills.  This will be achieved through a set of lectures and classroom practices and discussions that are designed to provide fundamental knowledge of the related areas to the students. The lectures will explore various technologies, methods and techniques, use cases and common practices in the lectures, where students will also learn how the fundamental concepts and solutions that can be applied in solving the problems or extending the frontiers in related areas. The practical sessions will be conducted as lab experiments and will be complimented by the coursework assignment. The coursework comprises a programming assignment and also writing an essay report. Students will be expected to not only investigate the relevant literature and write a report, but also to learn practical skills and develop a basic system and demonstrate it on a common platform.

Learning and teaching methods include the following.


  • Lectures to provide the fundamental knowledge 

  • Class discussion to encourage interaction and participation

  • Programming lab sessions 



 

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: COM3023

Other information

The COM3032 module contributes to the Surrey Pillars as follows: 

Sustainability: COM3032 enables the deep understanding of IoT systems joint with future internet and system technologies such as LTE and IoT-narrow band, CoAP,4G and 5G generations that play an important role for the postgraduates to link the IoT design to such technologies. Besides, by applying IoT network capabilities, they can cover the different environmental catastrophic events like fire in the forest, understand the Earth’s ecological effects and recognise how to manage the data through IoT network.

Global and cultural intelligence: IoT models and their related infrastructure-linked systems are a global system, and COM3032 helps to understand its details. Therefore, this module promotes the critical thinking (concerning the working of g of IoT networks) of our postgraduates as global citizens who can engage effectively and ethically with people from

Digital capabilities: The skills that COM3032 provides will enable postgraduates and their organisations to be able to participate actively in society and professional life, within a digital world, that will play a critical role in providing future services such as critical event detection, real-time analysis the data through critical infrastructure applications like remote surgency and smart grid and smart homes. 

 

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Computing and Information Technology BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Computer Science BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Computer Science MEng 1 Optional A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.