Smart Cities yields many benefits for society, including enhanced opportunities for education, improved job prospects, better access to healthcare and cleaner water. Yet it is also associated with immense societal and environmental challenges. Inefficient planning and management practices lead to unsustainable settlements that do not enable people to advance personally, socially or economically. Smart and innovative technologies, including artificial intelligence, are revolutionising the way cities address the challenges associated with smart growth.
AI in Smart Cities
Such technologies help cities to utilise existing assets more effectively, allocate resources more efficiently and improve how data and information are managed and shared across systems. Increasingly, satellite data is becoming a fundamental component of smart cities and an essential tool for city management and governance. From understanding connectivity between cities to measuring economic growth, detecting power outages or identifying where resources should be allocated after disasters, the increasing availability of satellite data is transforming how cities are managed and helping to improve their functionality.
From the point of view of urban governance, machine learning and artificial intelligence (AI) provide near-real-time information on how cities change in practice, e.g. through the conversion of green spaces into built-up structures. By ‘teaching’ computers what to look for in satellite images, rapidly expanding sources of satellite data are leveraged in combination with machine learning algorithms to quickly reveal how actual city development aligns with planning and zoning or which communities are most prone to flooding. Machine learning techniques help to automatically detect and map different types of land cover and land use across space and time, and generate important insights, analytics and visualisations.
AI a buzzword, a kind of magic formula
Today, AI is almost a buzzword, a kind of magic formula, based on some ‘intelligent agents’ and sophisticated algorithms that make decisions and take action for humans. But AI will never replace human validation or effective governance on the ground. ‘Smart’ technologies that collect data on the ground or from space must be leveraged to monitor and manage urban systems and to provide guidance and recommendations for better decision-making, which will in turn make cities more sustainable.
Planning for scalability and sustainability
Plan for both physical and digital scalability. If you want to upscale activities to other locations or cities by installing additional sensors or performing additional analytics – does the system allow for this?
Consider the longevity of the project and how the hardware may be used during and after it has completed. In some circumstances a Service Level Agreement (SLA) for maintenance or drift correction may be needed.
If you are building AI feedback into the system, it is good to make it as adaptive as possible. This allows systems to be able to take advantage of suggested optimisation by ensuring capacity to extend the functionality of the hardware and software, should it be identified as desirable by the AI.