The Aim is to develop an implementation methodology and knowledge framework to maintain the integrity of the semantic model across platforms and ensure processes are developed and implemented successfully to achieve the strategic targets.
The research will work towards identifying a standardized framework and support processes for information exchange, based on the BIM implementation framework. It will address the size of individual organizations and government bodies, core domain and complexity, along with measurable assessments aligned to the strategy. The goal is to help stakeholder engagement and on-boarding to aid strategy awareness, adoption and alignment, as well as knowledge creation rather than information exchange.
o Process and goal-driven, integrated or unified BIM and city information models offer the appropriate granularity for more accurate predictability than fragmented analysis of individual facility BIM models or current city information models.
o Better prediction models are obtained by stakeholder awareness, engagement, on-boarding and feedback. Gamification has a far greater level of success in ensuring engagement and strategic alignment, than other means.
o The key challenge of Intelligent Unified City Modelling Implementation is strategically aligned change management. Gamification through AR and VR tools leads to a greater level of success.
o Critical KPIs / targets for any developments and design change in the city fabric given today’s climatic upheaval is sustainability and resilience.
City Information Modelling implementation across all new and existing projects, as well as integration of BIM models, will lend the much-needed agility and iterative ability to municipalities augmented by live data at the relevant and required granularity and scale. This would subsequently lower the cost of assessing the impact of proposals, designs and development.
1. Develop the framework which helps the city transform to intelligent and unified city information modelling paradigm rather than a physical or digital graphical and/or information record;
2. Align city development strategy using simulation and prototyping;
3. Develop tested tools to aid the on-boarding of the various departments, stakeholders;
4. Enable correct and timely feedback and knowledge contribution.
Step 1: Adoption of the Delphi method to facilitate optimised process formulation along the supporting standards . The conducted analysis would be qualitative as well as quantitative. The XML exchange formats, enabling the integration of BIM and CIM into a UBM will require information exchange process and standard definition and execution. The vast number of stakeholders in the various project teams work on varying model authoring and federation software, the complexity levels, and global teams, subject to individual subjectivity, competence and understanding. This is the key challenge the research aims to address.
Step 2: Developing the analysis framework with the help of machine learning data analytics to provide accurate forecasts and enable the Unified City Modelling implementation to strategically align design for resilience. Using SMR Tools, in case of a disaster, would allow optimal utilization of the city infrastructure and optimized resource management through scenario-based planning simulation and smart alerting notifications.
Step 3: Utilizing City design parameters and predictive analytical framework to create algorithms for resilience mapping using City Information Modelling, VR & AR gamification for strategy alignment and sensors to collect and record real-time data.
Step 4: Validation. This leg of the research will assess the success of implementation framework and utilising strong industry and government alliances in data collection and post implementation.
Application Web Page
Applicants must apply using the online form on the University Alliance website at https://unialliance.ac.uk/dta/cofund/how-to-apply/
. Full details of the programme, eligibility details and a list of available research projects can be seen at https://unialliance.ac.uk/dta/cofund/
The final deadline for application is 12 April 2019.