Smart Monitoring with Industrial IoT - 2025 entry

The Industrial Internet of Things (IIoT) is a collection of sensors, actuators, and servers networked together specifically for industrial applications. By adopting IIoT technologies in industrial settings, many legacy assets and equipment can be turned into smart systems to improve business performance and stay competitive. IIoT technologies allow assets and processes to be monitored and analysed remotely, which is very important because industrial environments can be isolated (down in the valleys, forests, and sea) and hazardous (radioactive, extreme temperatures) where having these sites permanently staffed is not viable. Offering smart monitoring using IIoT, experts who work remotely off-site can better manage and make informed decisions and take well planned action based on evidence shown by smart monitoring systems. In this module, you will be introduced to the fundamental concepts, architecture and technologies of the IIoT. You will learn about the importance of emerging enabling technologies, such as device connectivity, cloud analytics and energy harvesting technology, in supporting the growth of IIoT. Focusing on monitoring, you will develop skills in capturing and analysing the collected data using an IIoT solution in a simulated industrial environment.

This module aims to provide a roadmap for the real-world implementation of IIoT with industrial sensors, energy harvesting, connectivity, and cloud analytics. You will understand how to improve business performance using IIoT via smart monitoring. Through both lectures and laboratory sessions, you will learn and develop skills in smart monitoring using IIoT based on industrial platforms using cutting-edge mobile network technologies to establish the connectivity and industrial widely accepted tools such as Acceleronix in the analysis and presentation of the collected data.

The learning outcomes for this module have been mapped to the output standards required for an accredited programme, as listed in the current version of the Engineering Council’s ‘Accreditation of Higher Education Programmes’ document (AHEP-V4).

1. Describe the concept of IIoT and apply smart monitoring in industrial applications (M1)

2. Evaluate how IIoT can help to improve business performance including environmental and societal sustainability (M7)

3. Explain semantic and enabling technologies for the growth of IIoT (M1)

4. Use practical laboratory and workshop skills to conduct data processing and analytic based on commercially available IIoT solution (M12)

5. Create engineering and industrial requirements in condition monitoring applications (M5)

6. Analyse the requirements of industrial environments for implementation of IIoT (M5)

7. Apply IIoT solutions to process data in other applications (M1)

8. Demonstrate clear, evaluative and critical written communication (M17)

9. Plan for and develop and demonstrate effective use of learning and lab resources (M13)

The module will provide an overview of IIoT, emphasising a typical use case for smart monitoring. The syllabus plan is:

• Introduction to the concept of smart monitoring with IIoT
• Introduction to IIoT architecture
• Introduction to the semantic and enabling technologies of IIoT
• Powering IIoT sustainably
• Monitoring technologies
• Intelligent technologies, focusing on cloud computing and data analytics
• Systematically presents typical IIoT application cases

Deferral – if you have been deferred for any assessment you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of referral will be capped at 50%. 

Basic reading:

• Lecture slides (compulsory)

• Academic papers recommended by the Module Convenor (compulsory)

• Recorded webinars recommended by the Module Convenor (compulsory)

• All learning materials and resources will be provided before or during the course

Other reading:

• R. Anandan, S. Gopalakrishnan, S. Pal and N. Zaman (Eds,), Industrial Internet of Things (IIoT): Intelligent Analytics for Predictive Maintenance, Wiley, 2022.

• D. Uckelmann, M. Harrison and F. Michahelles (Eds.), Architecting the Internet of Things, Springer, 2011.

• A. McEwen and H. Cassimally, Designing the Internet of Things, Wiley, 2013.

• P. Lea, IoT and Edge Computing for Architects, Packt Publishing Limited, 020.

• K. Iniewski (Ed.), Smart Sensors for Industrial Applications, CRC Press, 2017.

• J. Lee, Industrial AI: Applications with Sustainable Performance, Springer, 2020.

• G. Keramidas, N. Voros and M. Hbner, Components and Services for IoT Platforms: Paving the way for IoT standards, Springer, 2016.

• MQTT Specification. http://mqtt.org/mqtt-specification/

• A. Guerrieri, F. Cicirelli and A. Vinci (Eds.), Smart Monitoring and Control in the Future Internet of Things, MDPI, 2020.

• C.-M. Kyung, Smart Sensors for Health and Environment Monitoring, Springer, 2015.

Reading list for this module: