Tech adoption crucial to meet population growth demand

With Australia’s population projected to reach 30 million between 2029 and 2033, adding pressure to the quality and delivery of services for the community, it’s becoming more important to leverage modern technology to improve experiences and the efficiency of infrastructure, public transport, travel and roads. Government must adopt more smart city technology to cope with the scale and expansion as population rapidly grows, and offers four workable ideas.

Urban populations are growing at unprecedented rates, so we need to keep investing in smart city technology to create a brighter and more stable future. When further demand is added to systems such as public transport and traffic networks, some will struggle to cope — leading to overcrowding and poor-quality experiences.

Modern technology is making safe, scalable, sustainable cities and performant governments a reality. In particular, smart city technology helps accommodate large and rapid urban population growth, facilitate resource conservation such as water and carbon, and improve the quality of services for the community across utilities, transport, health care, waste management, air quality, safety and wellbeing, and emergency response.

We’re already starting to see various levels of government engage in public–private partnerships and sponsored collaboration to modernise and advance services through technology. It’s a great step in improving access for citizens and the broader community and one we hope will continue in response to the changing population’s needs.

Four key technology solutions

Four smart city technology solutions government could adopt to improve citizen services amid a rapidly growing urban population:

1. Smart meters, sensor technology and AI in buildings to reduce environmental footprint

Government bodies and large organisations have extensive physical footprints spanning office buildings and other facilities, which traditionally result in high environmental impact around energy consumption, water usage and waste management. To lower costs and minimise green footprint, government should employ smart ‘digital’ energy readers measuring usage and sensor technology that takes continuous readings of a space to create a pool of data, in combination with AI that analyses the data and helps make decisions. These technologies are transforming commercial buildings into smart, sustainable, safe and comfortable environments that intelligently adapt and respond to the needs of their occupants.

Historically, we’ve seen a focus on greenfield development precincts to showcase highly efficient building systems, but to have a truly scalable impact, we must leverage these modern technologies to cheaply and readily deploy into existing building sites. These technologies used in combination can control temperature and lighting systems in real time, and achieve up to 25% more efficiency.

2. VR simulation testing to make real-world spaces easier to navigate prior to construction

3D representations of real-world spaces are being built and tested in virtual reality (VR) simulations to understand how people respond to built environment and transportation designs and event modelling. This can be used to better accommodate accessibility for people with mobility challenges and create maximum impact with signage placements. For example, in response to an innovation challenge from an Australian state transport department, NCS NEXT used VR simulation testing to understand how users would respond to the physical train station environment in a digital format to optimise design prior to construction.

Testing these use cases using 3D representation and VR simulation can save huge amounts of money that is currently spent to build real-world physical replicas of train stations. As more infrastructure is built to accommodate more dense urban areas, it reduces errors when going from concept to the physical built space. The traditional method was to test spaces once partially or fully built. Optimising buildings and public transport for inclusiveness and ease of use is a key priority for scaling urban areas without adding frustration and aggravation to commuters.

3. ‘Whole of journey’ planning via a single digital app to optimise travel for minimum time and emissions.

With roads and parking stations getting busier as the population grows, travellers want to optimise the time it takes to reach their destination while being in minimal traffic and also ensuring they have somewhere to park prior to arriving. ‘Whole of journey planning’ brings together services — which were historically separate such as maps, parking services and amenity searches — into one place via an app to make the end-to-end experience easier for users.

These apps work by sharing data sources and enabling API functions to work together and be delivered to the user in one simple format. Using these platforms, it’s possible to ensure drivers can book parking ahead of a journey and be incentivised to travel off-peak; be aware of real-time changes in traffic conditions so they can respond to and make changes to their journey; and have road networks advise a vehicle of its optimum travel speed to avoid stopping at traffic lights — all of which is done using one platform. Not only does this reduce travel time but it also optimises journeys for minimum emissions.

4. Sensor and monitoring coverage for real-time data sharing during emergency events

During the pandemic, ARQ Group (now NCS NEXT) used CCTV networks and machine learning technology for an Australian state transport department to identify high-density hotspots on train station platforms. It used this information to explore ways to improve consumer health and safety and monitor overcrowding during physical distancing. As the population grows and urban sprawl occurs — expanding to areas which may not have immediate emergency response units or have been previously inhibited by poor data and communication access — sensors and monitoring coverage can monitor activity over a wider geospatial area and provide real-time data sharing for an array of emergency response scenarios.

The use of AI to identify emergency events such as fire, flood and earthquake can also automatically enable response measures via pre-optimised models, such as adjusting traffic signals to allow for greater emergency vehicle access while simultaneously accommodating greater community flow.

In an emergency event, data from sensors and monitors would be made available to multiple emergency service providers in real time, so everyone has the same access to information and can provide better coordination.

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