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AI-enabled secure social industrial internet of things platform: leveraging the Industry 4.0


   Centre for Digital Innovation

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  Dr Zia Ush Shamszaman  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

We are pleased to invite UK, EU and international applications for a fully-funded PhD studentship in AI-enabled secure social industrial internet of things platform: leveraging the Industry 4.0 from Teesside University’s Centre for Digital Innovation.

Project description

We are experiencing a cabalistic transformation in manufacturing products because of the digitisation of the process of manufacturing products in the industries and factories. The key technologies in this transformation are, Cyber Physical Systems, Internet of Things (IoT) and Information Systems. The transformation is so significant and inevitable that it is being considered as the 4th industrial revolution called Industry 4.0.

Social IoT (SIoT) is a recent amendment in the IoT paradigm where human-centric online social network principles are implied into IoT to enable IoT object as a new social element. SIoT work as a common platform for the data coming from IoT devices and social network services to facilitate omnidirectional interactions (human to human, human to object and object to object) among human and objects for creating new services in the future intelligent smart spaces. Industrial IoT (IIoT) has been noticed seriously and largely by the scientific community as well as by the industry because of its tremendous possibilities to leverage automaticity and intelligence mainly in the production, supply chain and manufacturing industries, ie leveraging the 4th industry revolution. The progressing trends towards IIoT from the predominant IoT, necessity of CPS, the vision of utilising SIoT in the smart industries and factories, the immense possibility of AI to incorporate intelligence in the physical objects; and the scalability issues of existing security mechanisms on huge IIoT resources demand an approach that addresses the above mentioned issues and move forward with the vision and possibilities towards the Industry 4.0. Hence, this research proposes an AI-enabled Secure Social Industrial Internet of Things (ASIIoT) that includes the utilisation of resources ie machines, parts, devices, processes, human and physical objects intelligently.

The supervisor is Dr Zia Ush Shamszaman from the School of Computing, Engineering & Digital Technologies.

Entry requirements

You should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A master’s level qualification in a relevant discipline is desirable, but not essential, as well as a demonstrable understanding of the research area.

International applicants should have a standard of English at IELTS 6.5 minimum and will be subject to the standard entry criteria relating to ATAS clearance and, when relevant, UK visa requirements and procedures.

How to apply

Application is online.

Key dates

  • Closing date for applications is 5.00pm, 1 February 2023.
  • Shortlisting and online interviews are expected to be held mid-March 2023.
  • Successful applicants will be expected to start May or October 2023.

Funding Notes

The Fully Funded PhD Studentship covers tuition fees for the period of a full-time PhD Registration of up to four years and provide an annual tax-free stipend of £17,668 for three years, subject to satisfactory progress.
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