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ECE5702 · Machine-to-machine storage and communication

Official Handbook

2026 Handbook6 credit pointsLevel 5Department of Electrical and Computer Systems Engineering

Last checked: 23 Aug 2026 UTC

Overview

This unit is designed to provide a deep understanding of Machine-to-Machine (M2M) storage for the Internet of Things (IoT). You will gain a comprehensive understanding of the architectural design, key principles, and technologies that underpin M2M storage. The unit emphasises practical implementation, guiding you in creating engineering-based applications using IoT storage services and establishing M2M engineering services through diverse technological elements.

Areas of study: E6013 Master of Applied Engineering - Specialisation: IoT systems and technologies

Offerings

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

Assessment

The Handbook lists an examination for this unit.

#AssessmentTypeWeightHurdle
1AssignmentsProject20%Threshold
2Test/Quizzes/ProjectQuiz / Test30%Threshold
3Final assessmentExamination50%Threshold

Continuous assessment: 50% Final assessment: 50% This unit contains a hurdle requirement 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

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

  1. Explain the architecture design, key design principles and technologies of machine-to-machine storage for Internet of Things (IoT).
  2. Construct machine-to-machine engineering-based applications using Internet of Things (IoT) storage services.
  3. Create machine-to-machine engineering services using different technologies elements such as virtual machines, web apps and mobile services with data migration techniques.
  4. Solve a physical/engineering problem using Internet of Things (IoT) and machine-to-machine technologies.

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
Laboratories24 hours
Workshops24 hours

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