Data-Driven processes design for Real-Time Service Provisions in Urban Computing Environment

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Urban computing uses ubiquitous computing technologies to gain a better understanding of how to improve our cities (Marciniak and Owoc, 2013). Urban Computing consists of four layers sensing, data management, analytics and service provision. While the sensing and data management layers are well established, it can be argued that to date there is a limited effort in utilising the data analytics layer to inform the design of processes to influence the service provision. It is propositioned that continuous analysis of data in real-time, allows immediate action to be taken when attempting to improve service provisions. Several techniques can be used to bridge this gap by utilising the structured and unstructured data to design processes, referred to as Data-driven Process Design.

Thus, it facilitates identifying process changes in real-time to improve performance and how we can offer service provisions. However, the lack of process layer in urban computing frameworks averts the efforts of sensing, analysing, and managing data to be practically applied for improving service provisions in urban areas. In addition, data-driven approaches can identify complex and nonlinear patterns in data that can be utilised to design processes and process modelling, data management, and process mining. Process mining is useful for conformance checking, performance analysis and predictions, which help diagnose problems and improve processes. Hence, this research will explore some of these data-driven techniques, develop a model including algorithms for mining processes in order to offer a systematic approach for designing processes to support real-time service provisions.

The potential candidate would be expected to be familiar with programming computer games technology, virtual and augmented reality as well as game based learning.

More information on the project, from potential impact to references, can be found on the accompanying PDF.

To apply, please complete the project proposal form and the online application.

Duration: 36 Months

Deadline to Apply: 19 January 2020

Unfortunately, this PhD Offer has expired!

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