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Module

CSC8112 : Internet of Things

  • Offered for Year: 2022/23
  • Module Leader(s): Professor Raj Ranjan
  • Lecturer: Dr Masoud Barati, Dr Tejal Shah
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

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

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

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Report1M100Report: describing the conceptual understanding of IoT system
Formative Assessments
Description Semester When Set Comment
Report1MReport describing the development of the IoT system
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.

Reading Lists

Timetable