Urbanisation is advancing rapidly, according to a report by the United Nations Department of Economic and Social Affairs. By 2050, approximately 70% of the global population is projected to reside in cities, resulting in tremendous pressure on urban infrastructure and governance.
In response, smart cities are emerging as a transformative approach to efficiently and sustainably managing complex urban systems.
Central to this evolution is the integration of artificial intelligence (AI) smart city technologies, which are rapidly becoming the backbone of safety, security, and operational resilience in these environments.
Smart cities rely on an ecosystem of technologies, be it sensors, connectivity solutions, data platforms, and automated systems, to collect and act on real-time information. Yet it is AI that enables these components to work together as a smart network, unlocking insights and driving autonomous decision-making.
This capability is crucial not just for convenience and efficiency but also for safeguarding critical infrastructure and public welfare. In this article, we’ll lay down some of the ways AI technologies are keeping the safety and security of these novel smart cities up to standard.
Enhancing Urban Mobility and Transport Safety
One of the most immediate areas where AI is making a difference is in smart mobility. Today’s smart rail and road solutions incorporate AI-powered analytics to optimize traffic flow, manage traffic-related incidents, and even predict when and where congestion might occur.
For instance, AI algorithms process feeds from traffic cameras and vehicle sensors to detect anomalies such as stalled vehicles or accidents, which then trigger timely alerts to control centres and allow for the automatic redirection of traffic.
On rail systems, predictive maintenance powered by machine learning helps to foresee equipment failure before it occurs. This not only reduces service disruptions but also enhances passenger safety.
Securing Water Systems
Safe and secure cities depend heavily on efficient water distribution. AI contributes significantly to modernising these traditionally manual sectors. Contemporary water and wastewater treatment systems now use AI technologies to monitor water quality in real-time. It is also used to optimise chemical dosing and to predict equipment maintenance needs.
This level of intelligence reduces human error and enhances operational efficiency, all while ensuring compliance with public health standards. Moreover, during extreme weather events, which are certainly a growing concern today due to climate change, AI helps cities better manage flood risks by predicting overflow points and optimising drainage system performance.
Making Solid Waste Management More Reliable
Reliable waste management is equally critical to urban safety. In solid waste management, AI is used for route optimisation in waste collection, as well as for smart bin systems that monitor fill levels and predict collection needs. These improvements help in reducing operational costs and also in preventing sanitation issues that can arise from delayed waste removal from neighborhoods.
Expanding the Urban Safety Net with Satellite Technology
While most urban safety systems operate at the street level, AI-driven satellite technology adds a critical layer of strategic intelligence. Today’s modern satellite communication solutions, along with satellite imagery and geospatial services, enable wide-area monitoring that complements ground-based sensors.
Through AI-based image analysis, cities can monitor urban sprawl, detect illegal construction, and assess damage from natural disasters, for example, and they can do these things more quickly and accurately than traditional methods. Satellite systems, enhanced by AI, support applications ranging from maritime surveillance to border security, which offer a comprehensive view of urban zones and their peripheries.
In particular, AI’s role in satellite data interpretation significantly reduces the time needed to analyse complex geospatial information. According to a 2022 report by the World Economic Forum, AI-driven geospatial analytics are increasingly being used to track infrastructure development and environmental changes, which is crucial for long-term urban planning and safety.
Supporting Urban Security, Public Health, and Disaster Responses
Security in smart cities extends beyond physical threats to encompass areas such as cybersecurity, emergency response, and public health. AI is instrumental in integrating data across various municipal departments, enabling coordinated action and rapid response to incidents.
For example, integrated command and control systems can use AI to correlate data from CCTV feeds, emergency hotlines, and IoT devices, creating a real-time operational picture for decision-makers.
This integration of data enables authorities to effectively detect and respond to threats, which can range from fire accidents and traffic incidents to crimes and natural disasters, all of which can be challenging to manage when using siloed legacy systems.
Tomorrow’s Challenges Faced Head On By AI
As smart cities continue to grow in scale and complexity, AI will become even more indispensable. Whether it’s about managing energy consumption and transportation or improving disaster response and urban planning, AI ensures that cities are not only more efficient but fundamentally safer and more resilient.
Indeed, in an era when urban risks are as diverse as they are unpredictable, AI provides the agility and intelligence needed to protect what matters most: people, infrastructure, and the future of our cities.
Deeply embedding AI into urban systems enables smart cities to anticipate challenges, adapt in real-time, and safeguard their populations in ways that were once thought impossible.
