Why The Term “Smart City Surveillance” Needs An Update In The Era Of AI And 5G

Smart city surveillance is rapidly evolving beyond traditional monitoring, thanks to real-time streaming technologies, AI, and 5G. In this blog, based on my recent LinkedIn post, you’ll learn the definition of smart cities and how the concept is evolving in 2025, gain an overview of the market, see how AI is revolutionizing this space, and discover what technology capabilities are now available to transportation agencies, public safety departments, disaster response teams, and other groups using smart city solutions.

Watch a short version of this blog in video format on YouTube.

What Is A Smart City? 

Smart city concept shown in an illustration.

A smart city is an urban area that uses smart technologies like ICT, IoT, and real-time streaming to enhance services and improve quality of life. With connected cameras, sensors, and software, cities can monitor feeds, detect incidents, and balance safety with privacy. These technologies integrate data-driven decision-making into everyday operations.

Smart City Market Overview

According to Statista, the United States is at the forefront of smart city development, with cities like New York and San Francisco leading the way in implementing advanced technologies for efficient infrastructure and improved quality of life. In terms of global comparison, the United States is projected to generate the highest revenue, with US$27.06 billion expected in 2025. It is anticipated that the revenue will demonstrate an annual growth rate (CAGR 2025–2029) of 7.27 percent. This growth will lead to a market volume of US$35.84 billion by 2029.

The U.S. government is also putting real momentum behind smart city innovation. Congress passed the Smart Cities and Communities Act of 2024 and followed with the 2025 version, both designed to fund projects, create standards, and boost cybersecurity. The Department of Transportation is running the SMART Grants Program, channeling resources into connected transportation and safety. On top of that, agencies like NIST and NSF are pushing research that takes these ideas well beyond big cities and into the communities where people actually live and work.

The Future Of Smart Cities 

Smart city systems are used by various state and regional agencies.

I’ve been thinking about that a lot lately as we’ve worked on projects that go well beyond the traditional “smart city” pitch deck.

With modern AI and real-time video infrastructure combined with growing 5G connectivity, we’re no longer limited to passive surveillance or slow post-event analysis. Today, systems can detect critical conditions as they unfold, so humans can intervene faster, or in some cases, not intervene at all.

One problem I have with the term “smart cities” is that so many of the use cases have nothing to do with cities at all. We’re not just talking about big city surveillance. These “smart city” systems are already being used by regional transportation agencies, public safety departments, and disaster response teams which cover rural areas too. Smart Cities was probably the right term when it was created, but times have changed. With today’s low-cost cameras, 5G connectivity, and cloud-hybrid infrastructure, it’s possible to put intelligence at the edge everywhere.

How Does AI Improve Smart City Surveillance? 

In these new deployments, AI does a lot of the heavy lifting. The job of the operator becomes less about staring at feeds and more about responding to actionable insight. For example:

• Cameras detect crowd congestion in a stadium and reroute foot traffic.
• A traffic feed flags a stopped vehicle inside a tunnel and alerts rescue teams in real time.
• Edge-based systems detect early signs of wildfires or floods and trigger rapid response, potentially saving lives.
• Teams can even record and share key footage as on-demand video with law enforcement to aid in investigations.

Cameras Everywhere? Finding The Right Balance

Pros and cons of widespread video surveillance cameras.

“What about big bother?” you might ask. “Should we have cameras like this everywhere?” This is honestly a difficult question. There’s a saying that with every new technology it can be used for good and for evil. Plus, it’s pretty clear that the cat is out of the bag, and we aren’t going back. I prefer to embrace the possibilities and do what we can to prevent the bad stuff while enabling life saving use cases that make a difference. Cameras everywhere can actually be a good thing if we use them with the right intent, the right architecture, and the right safeguards.

At Red5, we’ve built streaming infrastructure for smart cities that supports all of this:

• Ultra-Low Latency Streaming. Our sub-250 ms latency and ability to ingest video at the edge, feed it directly into GPU-powered AI models, and share results instantly, whether live or as on-demand content.
• Cross-Department Sharing. Seamlessly share video feeds across traffic management, emergency services, and public safety departments while maintaining secure access controls.
• Scalable City-Wide Deployment. Support thousands of cameras across urban environments while maintaining sub-250ms latency for real-time monitoring and response.
• Automated Alert System. AI-powered detection automatically alerts relevant departments to incidents, from road hazards to emergency vehicle deployment.
• Flexible Infrastructure Integration. Integrate with existing urban infrastructure and camera systems while enabling future expansion and technology adoption.

Let’s Discuss This In Person

Chris Allen’s talk at RTC.On 2025

If you’re in Krakow, Poland from September 17 to 19, 2025 I’ll be speaking more about how we put AI to work with Smart City style surveillance applications at RTC.On, a developer conference focused on streaming, WebRTC, and AI. My talk, “The Future in Focus: AI and the Next Wave of Real-Time Video Intelligence”, will explore large language models (LLMs) and Red5 Pro’s Brew API can be used to detect everything from crowd control issues and forest fires to firearms and inappropriate content in live user streams. I’ll also walk through real-world architectures and what’s coming next in this space.

Conclusion

Smart cities are no longer just about urban infrastructure. With AI, 5G, ultra-low latency streaming, and edge-powered analytics, surveillance systems can now detect issues as they unfold and support faster, safer decision making. Follow me on LinkedIn to keep up with my latest #ChrisAllenTalks posts and videos.