Internet of Things Technologies - Blanchardstown

The Internet of Things (IoT) is about the new connected world, that is fast expanding, based on synergistic integration of Computer Science, Sensor Technology, and Engineering Science and Technology. It concerns the new generation of systems of networked devices that are becoming capable of sensing, transmitting and acting on data, e.g,: wearables, autonomous vehicles, drones, robots, smart homes, smart cities, smart industries, etc

The associated IoT coverage ranges from simple sensors at one end to complex services in the "cloud", and encompasses, among others; electronic engineering, software development/engineering, networking technologies, product design, encryption etc.

The programme structure consists of taught modules and research projects in two possible pathways (Pathway 1 and Pathway 2). Year 1, Semester 1 & 2 are common to both pathways, with two Core modules taken in each semester, including a Research Methods (Part 1) module, which is Part 1 of the individual Final MEng Research Projects [Total 30 ECTS].

For Pathways 1:
Semester 3 of Year 1, consists of three Core Modules [15 ECTS];
Semester 1 of Year 2, consists of five electives from which candidates are required to take [20 ECTS];
Semester 2 of Year 2 is dedicated to the Research Project (Part 2: Implementation Phase) [25 ECTS].

For Pathways 2:
Semester 3 of Year 1, consists of one Core Module [5 ECTS];
Semester 1 & 2 of Year 2 is dedicated to the Research Project (Part 2: Implementation Phase) [55 ECTS].

Subjects taught

Year 1, Semester 1 ( Pathway 1 and Pathway 2 )
Embedded Systems [10 ECTS]
Software Engineering [5 ECTS]

Year 1, Semester 2 ( Pathway 1 and Pathway 2 )
Information Transmission & Management [10 ECTS]
Research Project (Part 1: Research Methods) [5 ECTS]

Year 1, Semester 3

Pathway 1:
Statistical Analysis for Engineers [5 ECTS]
IoT Systems [5 ECTS]
Secure Communication & Cryptography [5 ECTS]

Pathway 2:
Statistical Analysis for Engineers [5 ECTS]

Year 2, Semester 1

Pathway 1:

Electives [Total 20 ECTS Required]

Technology & Innovation Management [5 ECTS]
Geodata Provisions [5 ECTS]
Advanced Signal Processing [5 ECTS]
Network Security [10 ECTS]
Programming for Big Data [10 ECTS]

Year 2, Semester 2

Pathway 1:
Research Project (Part 2: Implementation)[25 ECTS]

Year 2, Semester 1 & 2

Pathway 2:
Research Project (Part 2: Implementation) [55 ECTS]

Entry requirements

Honours/Level 8 degree in Electronic Engineering, Electrical & Electronic Engineering, Computer Engineering, Mechatronic Engineering, and Computer Science, or cognate disciplines.

All other applicants with degrees in the specified disciplines or cognate areas, will be assessed on a case-by-case basis, and on the basis of relevant work experience.

Application dates

Apply for this course online at


2 years part-time

Post Course Info

A major obstacle to more extensive and sustainable deployment of IoT Technologies is the impending major worldwide shortage of workers with appropriate knowledge and skills. Therefore, in order to ensure that Ireland can compete, and specifically to enable the SME sector to take full advantage of the opportunities presented by R&D in IoT technologies, there is an urgent need to bridge the predicted skills gap. This programme presents a real opportunity to its graduates to enter a developing technology support and research roles in industry, and to benefit from rapid career advancement.

The aim of this Dual-Pathway MEng in IoT Technologies programme is to contribute to meeting the skills needs for sustainable IoT deployment and expansion. Specifically, the programmes will produce graduates with: Comprehensive qualifications in research and project management skills that can be directly applied in to high-end research, development and innovation to support engineering practice in the predicted future growth in IoT; Knowledge and competences for design, commissioning and maintenance of IoT systems and processes.

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Part time,Evening

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