Digital Infrastructure Management

Digital Infrastructure Management Team

Professor Sherif Mohamed is Head of the School of Engineering and Built Environment and a member of Cities Research Institute. Sherif leads the Digital Infrastructure Management team who are currently researching 'Asset intelligence' and 'Resilience of critical facilities and infrastructure systems'.

Asset Intelligence: Digital infrastructure asset management platform

‘Asset intelligence’ is the study of designing infrastructure and assets that can take care of itself.
It uses advanced technologies such as sensors, digital platforms and analytics to provide decision support to infrastructure asset managers such as current state of the asset, its future maintenance requirements, optimisation of cost of maintenance and repair etc.
With increasing numbers of infrastructure assets, the uncertainty about their lifespan and the conditions they might face, along with the declining availability of funds for maintenance and upkeep, future asset management will need to be smart and intelligent.
Australians expect infrastructure networks to support a high quality of living, which cannot be achieved if the networks and systems are not appropriately managed. To demonstrate, according to the Australian Local Government Association (2013), there is a forecast shortfall of $17 billion for maintenance and renewable expenditure for local roads across Australia between 2010 and 2024, representing 39% above the estimated funding availability for the corresponding period. In addition, poor maintenance of rail lines has led to more freight being transported by road, which imposes additional burdens.
Therefore, optimisation of available limited resources for maintenance of infrastructure is critical and ‘asset intelligence’ can assist infrastructure managers with real-time information about asset condition and optimise maintenance schedule and use of resources.

To lay the foundation for a novel digital infrastructure asset management platform that consists of integrated and shared asset data repositories for intelligent decision making in infrastructure maintenance, repair and rehabilitation planning.
To develop a common understanding of asset intelligence, its information requirement and required structure for management and communication of these information.
To identify the asset information requirements to setup an asset intelligence platform, i.e. the life cycle meta-data, for effective infrastructure asset management.
To identify innovative ways to map the interrelationships of the asset information requirements (e.g. temporal, logical or spatial interrelationships).
To develop a clear methodology to link information between different asset life cycle phases
Use asset intelligence to develop decision tools which would be able to collect real-time information from assets, process them to assess their health (i.e. maintenance and repair requirements) and use advanced optimisation analytics to suggest optimum method and time for conducting maintenance.

Sherif Mohamed: s.mohamed@griffith.edu.au

Zhonghua Gou: z.gou@griffith.edu.au

Rodney Stewart: r.stewart@griffith.edu.au

Ruwan Fernando: r.fernando@griffith.edu.au

Sherif Mostafa: sherif.mostafa@griffith.edu.au

Fahim Tonmoy: f.tonmoy@griffith.edu.au

Fan Zhang: fan.zhang@griffith.edu.au

Resilience of Critical Facilities and Infrastructure Systems

Critical facilities such as health and emergency services; critical infrastructures such as telecommunications, electric power generation and transmission, transportation, water supply systems, sewage treatment facilities have become elements in a bigger city system.
These facilities and systems not only provide basic civic service to our communities, they also allow business and economic activities to move forward and are therefore crucial for national security and economy.
Any disruption in the operation of these systems and services due to natural or man-made hazards can disrupt our daily life, lead to ripple effects in our economy and communities in general.
Resilience of critical infrastructure systems and facilities is often defined as the ability of a system to resist to and/or to recover from some shock so that it can maintain the status quo or can reorganize after stress or shock.
Analysis and quantification of ‘resilience’ of these critical systems are complex as they are influenced by multiple factors such as technical features of the system (i.e. its location, design capacity, in-built engineering safety features and redundancies), capacity of the organisation to manage the system (i.e. organisation’s resource availability to recover a ‘down’ system), behaviour of its users (i.e. how critical a given system is to its user) and dependency of the particular infrastructure on other systems.
Identifying system vulnerabilities to natural and man-made hazards through modelling and analysis can assist infrastructure operators to take necessary precautions so that overall reliability of the system can be increased and desired level of service can be achieved.

Provide better understanding and characterisation of resilience of critical infrastructure systems
Develop insights to better manage critical ‘socio-technical systems’ under natural and man-made disasters
Develop analytical methods and decision support tools for understanding interdependency of critical infrastructure systems, so that critical nodes for maintaining services under disaster scenarios can be identified and made resilient.
Investigate the use of big data analysis techniques in understanding infrastructure interdependency
Develop innovative use of smart technologies in increasing disaster resilience of critical infrastructure systems
Engage with critical infrastructure operators (e.g. transport, water supply, electricity generation, transmission and supply, health service providers) and disaster managers to develop innovative strategies and decision support systems for increasing disaster resilience of local scale critical infrastructure.
Engage with communities to improve our disaster resilience.

Sherif Mohamed: s.mohamed@griffith.edu.au

Rodney Stewart: r.stewart@griffith.edu.au

Hong Guan: h.guan@griffith.edu.au

Oz Sahin: o.sahin@griffith.edu.au

Fahim Tonmoy: f.tonmoy@griffith.edu.au

Anisur Rahman: a.rahman@griffith.edu.au

Cecilia Bischeri: c.bischeri@griffith.edu.au

Cheryl Desha: c.desha@griffith.edu.au