La Trobe University > Research > Research centres and institutes > Centre for Technology Infusion > Research > Asian Smart Cities Research Innovation Network > Research themes > Infrastructure and technology

Infrastructure and technology

Smart cities need all kinds of infrastructure that respond to the current and future needs of people living in them.

Technology can collect and analyse information to provide solutions as situations change, such as demands for power due to extreme heat or cold, or traffic and crowd management.

Experts working under this theme can develop solutions that support the infrastructure and technology challenges of smart cities.

Research

We are eager to work with people and organisations on research that fits this theme. Some possible research examples might be:

regular maintenance of capital infrastructure – does it live up to the promise?
developing low power consumption systems?
long distance radio frequency – can it achieve universal coverage?
how can everyone connect no matter where they are or how much money they have?

If you have an idea for research and want to be a part of our network, contact us with your ideas.

Engagement

We are able to undertake work for organisations and governments. Talk to us about how we can help you. Some examples include:

analysis of data and provision of a report to advise on smart technologies available or what is needed to solve a problem
feasibility studies
economic modelling – the cost benefits of technologies.

Externally Funded Projects

Operationalising ethical frameworks in critical tech industries

This project intends to provide Australian and Indian businesses with improved ethical policy and practice when outsourcing their technology to Indian providers. It will do this by improving the understanding of how they translate being signatories of Ethical Codes to their actual practice. Moreover, the project will analyse the emotions and views of stakeholders expressed in social media on the ethical issues found to be important in business surveys. In doing so, the project intends to advance the body of knowledge in artificial intelligence (AI) and cyber and critical technology, ethics and sustainability and risk by bringing together disciplines in business management and ethics, computer science and engineering, and AI and business analytics.

The outcomes expected include recommendations as to revised codes and practices of ethics and a framework using AI and advanced analytics to review ethical practices of companies.

Project Team:

Professor Suzanne Young (La Trobe University) - Project Leader
Professor Naveen Chilamkurti (La Trobe University)
Professor Damminda Alahakoon (La Trobe University)
Professor Murali Prasad Panta (IIT Kanpur)
Professor Praveen Kulshreshtha (IIT Kanpur)
Dr Sameer G Kulkarni (IIT Gandhinagar)

Together, they bring expertise in corporate governance, ethics and human behaviour, cyber threats and social engineering, and the use of predictive data for industry.

This project has been funded through the first round of the Department of Foreign Affairs and Trade - Australia-India Cyber and Critical Technology Partnership program

Current research projects

Feasibility studies for reusing construction and demolition waste for smart cities

This project seeks to study the feasibility of using construction and demolition waste (CDW) as an alternate low-carbon material in construction. Three types of CDW: crushed brick, recycled concrete aggregate and recycled asphalt pavement will be considered. It is hoped that this study will increase confidence by end users, contractors and design consultants to make use of this alternative material and reduce the amount of CDW going to landfill.

Investigators:

Professor Hossam Aboel Naga (La Trobe University)
Professor Anasua GuhaRay (BITS Pilani)

PhD candidate:

Sai Kiran Chukka

Project ID: 1-EOI-BITSP

Real-time crash prediction in disordered traffic

This project aims to develop real-time crash prediction models for disordered traffic on urban roads and intersections.

Utilising high resolution multimodal trajectory data being collected by an on-going project at IIT Kanpur, surrogate safety measure and crash precursors will be identified and analysed.

Real-time crash prediction models with different predictive horizons will then be developed using deep learning techniques such as short-term memory networks.

Investigators:

Dr Long Truong (La Trobe University)
Associate Professor Venkatesan Kanagaraj (IIT Kanpur)

Project ID: 2-EOI-IITK

Resilient ultra-strong composites for next-generation urban infrastructure

This project aims to provide a major breakthrough in design and analysis by developing an ultra-strong composite member combining the properties of carbon steel and ultra-high-strength concrete, thus reduce the carbon footprint through a reduction in building materials, reuse of structural members and prefabrications using advanced manufacturing techniques.

Investigators:

Dr Vipul Patel (La Trobe University)
Dr Mumtaz Hussain (La Trobe University)
Assistant Professor Arghya Das (IIT Kanpur)
Dr Amar Nath Roy Chowdhury (IIT Kanpur)

Project ID: 9-EOI-IITK

Citizens’ E-Collaboration : Collective Intelligence for Community Socio-Economic Upliftment in Smart Cities

This research aims to investigate how citizens e-collaborate to exploit smart technologies for shared value in the service economy. Although the smart technologies create a unique and connected information-based ecosystem, citizens have little understanding of what problems smart technologies will solve, and how smart technologies function. Consequently, the uptake of smart technologies has been limited or not been utilised.

Investigators:

Dr Malliga Marimuthu (La Trobe University)
Professor Clare D'Souza (La Trobe University)
Associate Professor Pradip Swarnakar (IIT Kanpur)
Associate Professor Deep Mukherjee (IIT Kanpur)

Project ID: 12-EOI-IITK

Advanced geometric algorithms for network optimisation and architectural layout design

This project aims to advance the theory and practice of automated design of minimum cost networks and architectural layouts to solve a range of problems including how to develop a mathematical approach for generating floorplan layouts which are an integral part of Urban Design, or to solve disc packing and covering problems.

Investigators:

Associate Professor Marcel Jackson (La Trobe University)
Dr Michael Payne (La Trobe University)
Dr Krishnendra Shekhawat (BITS Pilani)
Dr Manjanna Basappa (BITS Pilani)

Project ID: 16-EOI-BITSP

Intelligent planning of Prosumer Microgrid (PMG) Load Management in Smart Cities for Optimal Energy Consumption

This project aims to reduce the costs of energy consumption through intelligent monitoring of the loads and generations of the Prosumer Microgrid (PMG). When prosumers along with Net Zero Buildings (NZB) participate in energy bidding process, energy cost minimisation in PMG can be achieved.

Investigators:

Associate Professor Abdun Mahmood (La Trobe University)
Professor Naveen Chilamkurti (La Trobe University)
Associate Professor Alivelu Manga Parimi (BITS Pilani)
Professor Hitesh Dutt Mathur (BITS Pilani)

PhD candidate:

Mr Aishvaria Gorityala

Project ID: 18-EOI-BITSP

MXene-Collagen Based Bioinks as Suitable 3D Bioprinting Materials for Tissue Engineering

This project aims to develop a nanocomposite bioink comprising of MXene nanosheets dispersed within collagen hydrogel for 3D bioprinting of permissive cell-laden scaffolds. Its rheological characteristics, electrical conductivity, printability, print fidelity, cytocompatibility and in vitro biocompatibility for tissue engineering applications will be investigated. An attempt will also be made to pursue an in vivo characterization of the 3-D printed scaffolds.

Investigators:

Associate Professor Ing Kong (La Trobe University)
Professor James Maxwell (La Trobe University)
Dr Avinash Baji (La Trobe University)
Professor Kantesh Balani (IIT Kanpur)
Professor J. Ramkumar (IIT Kanpur)

PhD candidate:

Mr Indrajeet Singh

Project ID: 23-EOI-IITK

Security of biometric authentication in the IoT

This project will develop secure biometric authentication systems using deep learning techniques to counter biometric-related threats in the IoT environment.

With template protection, the biometric authentication systems designed need to show strong security and good recognition performance.

Investigators:

Dr Song Wang (La Trobe University)
Associate Professor Ashutosh Bhatia (BITS Pilani)

PhD candidate:

Laxmi Chhibbar

Project ID: 25-EOI-BITSP

Building Multi-source knowledge base for AI-driven public health explainable chatbots

A common problem in public health is the ability to answer health related questions at scale. One solution is to use Machine Learning/Artificial Intelligence to learn the questions and answers so a machine can provide this service 24x7 to many people. However current techniques lack the capabilities to ensure answers are medically sound, so new algorithms need to be found to overcome these kinds of issues.

Investigators:

Dr Mei-Tai Chu (La Trobe University)
Dr Binh Tran (La Trobe University)
Dr Manik Gupta (BITS Pilani)

Project ID: 33-EOI-BITSP

Building Actionable and Smart Information Systems for Migrant Workers in Smart Cities

This project aims to test sustainable models of digital communication that support migrant workers’ welfare in urban spaces. Targeting information gaps, ethnographic research methods will be used to identify migrant capabilities for handling digital platforms. This data will guide design and construction of an appropriate information system to be deployed and tested with the communities studied, that caters to their capabilities and information needs.

Investigators:

Associate Professor Julie Rudner (La Trobe University)
Dr Martina Boese (La Trobe University)
Dr Dipanjan Chakraborty (BITS Pilani)

PhD candidate:

Chaitra C R

Project ID: 41-EOI-BITSP

Sustainable Performance-Oriented Maritime Transport in India and Australia: An Empirical Analysis

This project will collect data to test CO2 emmisions and to understand how to incorporate social cost factors into the maritime transport's structure and conduct that will achieve sustainable performance-oriented services to reduce CO2 emissions.

Investigators:

Dr Sobhan (Sean) Asian (La Trobe University)
Associate Professor Murali Prasad Panta (IIT Kanpur)
Professor Praveen Kulshreshtha (IIT Kanpur)
Dr NVM Rao (BITS Pilani)

Project ID: 45-EOI-IITK-BITSP

Future of India-Australia Agribusiness Trade in an Era of Reglobalization: A Supply Chain Management Perspective

This research aims to explore how supply chain collaboration among groups of importers and/or exporters can successfully reduce production/logistical costs along with work for new trade agreements. We will combine national input output data along with trade statistics to identify the global value chains in various sectors and decipher value added in bilateral trade flows. The study will generate innovative supply chain solutions and promote collaboration among multiple clusters of Indian and Australian exporters and importers, with special focus on micro, small and medium enterprises and low-income consumers.

Investigators:

Dr Sobhan (Sean) Asian (La Trobe University)
Dr Timothy Clune (La Trobe University)
Associate Professor Murali Prasad Panta (IIT Kanpur)
Professor Somesh Mathur (IIT Kanpur)

Project ID: 47-EOI-IITK

Improving data driven decision making in small-mid scale dairy cooperatives

Our research aims develop bespoke sensors and data analytics and traceability methods to identify causes of milk quality problems and enable development of strategies to improve milk quality.

Investigators:

Professor Aniruddha Desai (La Trobe University)
Professor Yi-Ping Phoebe Chen (La Trobe University)
Dr Markandeya Jois (La Trobe University)
Dr Mohsen Radfar (La Trobe University)
Professor Navneet Goyal (BITS Pilani)
Professor Suman Kapur (BITS Pilani)
Dr Poonam Goyal (BITS Pilani)
Associate Professor Ashutosh Bhatia (BITS Pilani)
Professor Shantanu Bhattacharya (IIT Kanpur)

PhD candidate:

Anupama Ranjan (BITS Pilani)

Project ID: 50-EOI-IITK-BITSP

Implementation of an ultra-energy efficient brain-inspired computing platform using spintronics

In this project, synapse and neuron circuits will be designed using spintronic devices and spintronic neuromorphic implementations of various neural networks, such as Convolutional or Long/Short Term Memory Neural Networks. This work will contribute to the body of knowledge in spintronic neuromorphic systems by providing new models and platforms to implement such networks in a more practical way.