Project Background
The aim of this project is to revolutionise the real-time monitoring of cargo vessels by developing bespoke Internet of Things (IoT) technologies that are optimised for the unique demands of the maritime setting.
Such vessels form the backbone of global trade, carrying billions of dollars of raw materials and goods each day. Despite their economic importance, cargo vessels, such as bulk carriers and container ships are relatively poorly instrumented, making it difficult for vessel owners and cargo charterers to monitor the state of goods in real time.
This is particularly important for perishable or hazardous cargos. Penetration of ‘off-the shelf’ IoT technologies have had limited success. The reason for this is twofold: Firstly, practical solutions need to be cheap, flexible, and adaptable to a wide variety of vessels, stakeholders, and regulations. Secondly, the communication environment poses major technological challenges due to the dispersive nature of the radio channels in cargo ships and the low-rate bursty nature of typical monitoring data.
In this project, we aim to design, develop, and implement a sensor network and communication solution for cargo vessels that is scalable, robust, and can be easily implemented in a multiuser communication setting.
This project will address these challenges by combining expertise in sensor networks, communications, and data science from both the academic and the industrial partner. It will involve collaborative working with Andrew Moore & Associates, who are a maritime science and engineering consultancy with a worldwide presence.
A key part of the training will be learning about the real challenges of and approaches to maritime IoT through taking part in real onsite vessel trials. The student will be exposed to all aspects of a company including consultancy, project implementation, and research and development. Whilst at the company’s Sheffield office the student will work closely with the research and development engineers to learn how technology is transferred to create new products and solutions.
Aims and Objectives
This research will explore scalable and low-cost solutions that monitor the containers without the need of relying on external communication providers. The proposed solution aspires to satisfy the following three objectives:
- The communication architecture will be reliable for intermittent bursty data sources operating in harsh dispersive environments.
- The sensor network will be flexible and scalable to enable different stakeholders to join the network in a decentralised fashion.
- The resulting system will be energy efficient and will be able to operate with intermittent energy resources, such as solar panels.
Environment
Students will benefit from a bespoke training scheme delivered by world leading experts from academia and industry, access to world leading experimental and computational facilities as well as close and regular contact with Andrew Moore & Associates. The supervisors will visit the student regularly at the Sheffield site.
Whilst primarily based in Sheffield, the student will have the opportunity to visit overseas sites which will provide an international context to the research. It is therefore likely that the student will spend close to the maximum allowed each year in the company. This time will be managed closely by the company and academic supervisors to ensure that the work complements and contributes to the PhD.
The project will be supervised by Dr Iñaki Esnaola, with the co-supervision of Prof Xiaoli Chu at the University of Sheffield in collaboration with Dr Bryn Jones from Andrew Moore & Associates.
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