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OnDemand Panel Discussion: Digital twins and AI as the intelligent operating layer for cities

Jul 08, 2026  Twila Rosenbaum 22 views

The convergence of digital twin technology and artificial intelligence is reshaping how cities plan, operate, and respond to complex challenges. In a recent virtual panel held as part of the SmartCitiesWorld Summit 2026, urban leaders, technology providers, and policy experts examined how these innovations can become the intelligent operating layer that underpins municipal governance. The discussion, set against the backdrop of London Climate Action Week, highlighted the urgent need for cities to integrate AI into mainstream operations for long-term resilience and sustainability.

Digital twins—virtual replicas of physical systems—have evolved from simple 3D models into dynamic platforms that simulate real-time data from sensors, IoT devices, and infrastructure networks. When combined with AI, these twins can predict traffic congestion, optimize energy distribution, model the impact of extreme weather, and even test policy interventions before they are implemented. Panelists noted that cities around the world are already piloting such systems, but scaling them requires robust data governance, interoperability standards, and a clear regulatory framework.

Energy Systems and the Grid of Tomorrow

A major focus of the panel was how local authorities can shape energy systems through renewables, flexibility, storage, and smarter networks. Digital twins enable granular visibility into energy consumption patterns, allowing cities to identify peak demand periods and integrate distributed energy resources like rooftop solar and community batteries. AI algorithms then optimize the dispatch of stored energy and manage load balancing in real time. This approach not only reduces carbon emissions but also lowers operational costs for municipalities.

Several cities have begun deploying these solutions. For instance, the city of Sunderland in the UK has positioned itself as a leading smart city by using digital infrastructure and low-carbon innovation to build a resilient, future-focused economy. A recent SmartCitiesWorld City Profile highlighted how Sunderland is leveraging AI-driven analytics to improve energy efficiency in public buildings and to support the electrification of its transport fleet. Similarly, Dublin's smart city initiatives include digital twin projects that model traffic reduction strategies, economic growth patterns, and community service improvements.

AI in Urban Operations: From Pilot to Mainstream

The panel explored the practical steps needed to move AI from experimental pilots into everyday government operations. Youssef Nadiri of PNY Technologies, speaking on the SmartCitiesWorld podcast, emphasized the concept of sovereign AI—where cities maintain control over their data and algorithms. This is particularly relevant in sectors like public safety, transportation, and social services, where trust and inclusivity are paramount. Panelists agreed that building a solid data foundation is the first crucial step. Sunderland's experience demonstrates that preparing data for AI involves not only technical infrastructure but also organizational change management and citizen engagement.

Gareth Tang, President of Urban Solutions at ST Engineering, provided a glimpse into the future of urban AI applications. He detailed projects where AI is already making significant impact, such as using computer vision to monitor building occupancy, predict maintenance needs in public housing, and optimize waste collection routes. Tang noted that the next frontier is integrating these isolated AI systems into a unified digital twin that can simulate cross-domain scenarios—like how a flood event might affect both transportation and energy networks simultaneously.

Global Examples of AI-Powered Urban Innovation

Malaysia is emerging as a leader in AI-powered urban innovation. The first Southeast Asian Smart City Expo took place in Kuala Lumpur, showcasing how the region is adopting digital twins for urban planning, disaster management, and climate adaptation. Panelists pointed out that emerging economies have an opportunity to leapfrog legacy systems by adopting AI-native infrastructure from the start.

Meanwhile, the Urban Exchange podcast brought a firsthand account of city resilience from Quezon City in the Philippines. Following unexpected extreme rainfall, the city deployed a digital twin integrated with real-time weather data to coordinate emergency responses and allocate resources more effectively. This practical example illustrated how AI can enhance situational awareness and reduce response times during crises.

Smart Sensor Networks and Indoor Safety

Another area highlighted in the discussion was the role of smart sensor networks in improving indoor safety. By detecting risks such as gas leaks, structural anomalies, or occupancy overload early, these systems improve situational awareness and support healthier, more secure, and sustainable buildings. Combined with digital twins, building managers can simulate evacuation scenarios, optimize ventilation during pandemics, and reduce energy waste without compromising comfort.

Data Groundwork and Preparing for AI Adoption

A recurring theme was the importance of data groundwork. An OnDemand webinar on preparing for AI, featuring Sunderland City Council, underscored that without clean, standardized, and accessible data, even the most advanced algorithms will fail. Cities must invest in data platforms that can ingest information from disparate sources—traffic cameras, utility meters, social services records—and make it usable for machine learning models. This includes addressing issues of privacy, security, and equity to ensure that AI benefits all residents.

The panel concluded with a forward-looking discussion about the need for continuous learning and adaptation. As AI technologies evolve, so too must the governance structures that oversee them. The SmartCitiesWorld Summit 2026 set the stage for ongoing collaboration between cities, technology partners, and academia to refine the intelligent operating layer that will define urban living in the coming decades.


Source:Smart Cities World News


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