Module Catalogue 2024/25

CSC8112 : Internet of Things

CSC8112 : Internet of Things

  • Offered for Year: 2024/25
  • Module Leader(s): Professor Raj Ranjan
  • Co-Module Leader: Dr Tejal Shah, Dr Tomasz Szydlo
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System
Pre-requisite

Modules you must have done previously to study this module

Pre Requisite Comment

N/A

Co-Requisite

Modules you need to take at the same time

Co Requisite Comment

N/A

Aims

The Internet of Things (IoT) is a distributed system, in which autonomous devices, sometimes called motes, collect environmental data (such as location, speed, temperature, humidity and sound level) or, more recently, medical data (such as heart rate, blood oxygen level and pulse rate). The data is collected across the network, aggregated and fed into data processing IoT applications. Sensor and actuator networks, telemetry, data processing, distributed data bases, machine vision, AI and analytics are enablers for IoT applications across multiple disciplines, including environmental monitoring and control, agricultural monitoring, healthcare, habitat monitoring and military surveillance.

In order to successfully design and build scalable application systems in the IoT, a range of knowledge and skills are needed. This module will introduce and examine the core concepts, theoretical underpinnings and software frameworks relevant to the IoT. It will describe the network protocols, hardware resources, data programming models, and virtualization technologies from which the IoT cloud infrastructure and applications are constructed. Methods for building scalable IoT applications that span across multiple parts of infrastructure (sensor, edge, and cloud) will be described and explained. Case studies drawn from industrial applications of IoT will be used throughout to motivate the teaching and learning process.

Outline Of Syllabus

The syllabus will cover following topics:
•       IoT theory, concepts, components and delivery models
•       IoT architecture and topologies
•       Sensors and Actuators in IoT
•       IoT Standards and Communication Protocols
•       Fundamentals of Software Defined Networking and its role in IoT
•       Issues and Challenges in building IoT applications
•       IoT Data Management and Data Integration
•       IoT knowledge graph and data fusion
•       IoT and Blockchain
•       IoT in Context of Cloud Computing and Analytics
•       IoT and Edge/Fog Computing

Learning Outcomes

Intended Knowledge Outcomes

To be able to describe and discuss:

-       How businesses and society can benefit from the IoT paradigm
-       The role of IoT of data for automatic decision making workflows in a chosen field or industry
-       The legal and ethical implications of collecting and processing data using IoT
-       Strength and weakness of the IoT paradigm

Intended Skill Outcomes

Upon successful completion of this subject students should be able to:
•       Integrate skills and knowledge gained in the course as a whole for solving real-world problems
•       Explain an integrated, multidisciplinary approach for IoT based solutions, and apply it to solving real-world problems.
•       Analyse, design and implement a distributed IoT application system, its components and address its connectivity issues.
•       Explain the principles of sensing/actuation, data transmission and processing, visualisation and analytics, as well as, cybersecurity issues in IoT
•       Execute independent investigation of new IoT applications, methods, technologies, programming models and tools, as well as, application development concepts
•       Recognize and appreciate the collaborative nature of IoT development and the teamwork involved

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion101:0010:00Lecture material follow up via Microsoft Teams in asynchronous setting
Scheduled Learning And Teaching ActivitiesPractical62:0012:00In person practicals (6 x 2-hour practical sessions in the lab (PiP)
Guided Independent StudyProject work92:0018:00Coursework
Guided Independent StudyIndependent study401:0040:00background reading
Scheduled Learning And Teaching ActivitiesModule talk62:0012:00Online synchronous delivery of course material & discussions.
Scheduled Learning And Teaching ActivitiesModule talk42:008:00In person delivery of course material
Total100:00
Teaching Rationale And Relationship

Lectures explain the underpinning principles for the module and technologies of Internet of Things. Lectures are complemented by supervised practical sessions to guide the application of these principles using suitable computational tools. Further practical work takes place during private study hours

Reading Lists

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Digital Examination901A60open book, testing of conceptual knowledge
Other Assessment
Description Semester When Set Percentage Comment
Report1M40Testing of programming skills, will include code demonstration + report. 3-4 weeks to complete
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Report1MProgramming exercises in the lab
Assessment Rationale And Relationship

The reports test the students' ability to apply the range of knowledge presented in the module. This builds on practical work and develops and tests the students' ability to design and implement IoT systems.
The exam will be an open-book exam at the end of Semester 1 . In a controlled environment (examination room), students will be asked to provide answers to exam questions testing conceptual knowledge.

Timetable

Past Exam Papers

General Notes

N/A

Welcome to Newcastle University Module Catalogue

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Disclaimer

The information contained within the Module Catalogue relates to the 2024 academic year.

In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.

Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.