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ECE4810 · Internet of Things: Communication, data and security

Official Handbook

2026 Handbook6 credit pointsLevel 4Department of Electrical and Computer Systems Engineering

Last checked: 23 Aug 2026 UTC

Overview

This unit will cover aspects constituting the Internet of Things (IoT) including communications, data analytics and cybersecurity. The unit covers network protocols, management and control standards. It will also cover fog computing and machine learning for data analytics, and the fundamentals of cybersecurity. The unit will focus on learning through Industrial IoT (IIoT) case studies related to critical infrastructures such as smart city, smart grids, healthcare and Industry 4.0.

Areas of study: Minor: Artificial intelligence in engineering Minor: Intelligent manufacturing Minor: Internet of Things (IoT)

Offerings

CampusTeaching periodMode
MalaysiaSecond semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook lists an examination for this unit.

#AssessmentTypeWeightHurdle
1LabDemonstration20%Threshold
2Quiz/TestQuiz / Test10%Threshold
3ProjectProject20%Threshold
4Final assessmentExamination50%Threshold

Continuous assessment: 50% Final assessment: 50% This unit contains hurdle requirements that you must achieve to be able to pass the unit. You are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final assessment component. The consequence of not achieving a hurdle requirement is a fail grade (NH) and a maximum mark of 45 for the unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

prerequisite

  • ECE3141 — Information and networks
  • ECE3073 — Computer systems
  • TRC3500 — Sensors and artificial perception
  • MEC3456 — Engineering computational analysis

Joined by OR.

Learning outcomes

  1. design a low power and long-range communication system for different types of IoT network, based on standards such as Lorawan, 6LowPAN and Bluetooth Low Energy
  2. apply techniques such as fog computing with supervised and unsupervised machine learning to analyse IoT data
  3. analyse cybersecurity risks of IoT systems and propose relevant security solutions
  4. develop practical skills in the IoT domain related to networking and data analytics using industry-standard IoT tools
  5. show commitment by participating productively to achieve project goals in a team
  6. evaluate the feasibility of an IoT implementation using cost-benefit analysis.

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

ActivityDuration
Laboratories22 hours
Workshops24 hours

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