AI Driving Innovation, Security and Efficiency in Transport

The UK Government recently unveiled its AI Opportunities Action Plan, a long- term strategy for the UK’s AI infrastructure to ramp up adoption, boost economic growth and improve people’s everyday lives. Specifically, in the UK public sector, AI is now being heralded as a transformative opportunity to improve services and productivity.

The announcement specifically highlighted public sector industries, including transport as primed for AI transformation. Digitalisation of the UK’s public transport sector has long been a priority in the drive for greater efficiency. However, technology-driven public sector projects are often criticised for being fragmented and limited in scale. Now, the newly released AI action plan seeks to take advantage of available technologies to revitalise digital operations across public services.

So, what will this transformation look like in practice, and how will AI shape the future of transport operations?

The power of AI-driven video analytics

Viable AI solutions are already transforming industries like transportation and smart cities with real-time monitoring, proactive security alerts and actionable data, enabling organisations to improve decision-making capabilities, optimise resources, and enhance efficiency.

Every day, cameras and sensors across transport networks generate millions of data points that, when harnessed effectively, can unlock powerful business insights. It should be noted that ensuring strong data privacy, security, and regulatory compliance is crucial to safely collect, store, and analyse this information without compromising trust or ethical standards.

Once data foundations are in place, comprehensive end-to-end AI-powered solutions can be used to transform complex video and images into actionable insights in real time.  These solutions are designed to work with various existing technology and different types of CCTV cameras (analogue, IP, etc).

With edge-enabled intelligent transport hubs, operators can also process video streams at the edge in real time using AI algorithms that reduce network bandwidth.

AI-Powered Surveillance

AI enabled surveillance products can analyse activities much like a human would, and can be used to accurately detect objects, people and behaviours to provide information for people to take appropriate action.

This can play a vital role in train stations and airports. For example, an AI solution can detect when queue lengths are increasing and send automatic alerts to manage employees tasks to ensure fluidity of resources and reduce waiting times. Through features such as flow and path map analytics, business efficiency can be improved and bad customer experiences avoided. 

Similarly, real time analytics can make rail infrastructure safer and more efficient, specifically level crossings which cause some of the highest severity incidents, largest delays, and highest costs in any rail network. By using AI analytics people, vehicles, and other objects can be detected that stop or deviate from the path on the level crossing, giving early warning to a possible incident. By analysing collected data over time, the system can also support strategic decision-making by identifying high-risk crossings, recommending closures, and highlighting areas that require additional safety measures. 

The same technology can also enhance transport safety and traffic management by combining real-time and historical data to detect hazards, monitor traffic flow, and respond swiftly to incidents. Cameras in car parks, roads, tunnels, and bridges detect potential incidents early, such as breakdowns, to enable faster intervention and prevent escalation. By analysing traffic patterns, AI can also help regulate signals, re-route vehicles and manage lane usage to improve road efficiency and minimise air pollution.

Revolutionising Security in Transport

Another innovative feature of AI transport solutions is Tag and Track technology, which improves security operations by facilitating real time tracking of individuals and vehicles seamlessly across both overlapping and non-overlapping CCTV camera networks. Real time, AI video surveillance can monitor hundreds of CCTV cameras to detect abnormal behaviour and limit potential violations. For example, intrusion detection, smoke detection and perimeter protection.

Easily configurable solutions make video searchable, actionable and quantifiable, providing crucial operational insights resulting in reduced operator response times. Vitally, these systems don’t require staff to be on site, as cameras could be deployed across a wide area, with alarms sent back to a centralised monitoring room. As a result, every location from individual train carriages to fence lines around trains can be monitored for vandalism, theft and risky individuals and an immediate alarm can be raised.

AI-Driven Biometric Security Redefining Identification

AI solutions are also setting a new standard for biometric security. AI surveillance based on facial recognition technology, state-of-the-art algorithms and advanced machine learning techniques can ensure accurate identification and authentication of individuals. The solution can also trigger watchlist alarms, offering unparalleled reliability and peace of mind to organisations worldwide.

Advanced solutions powered by cutting-edge AI technology can even provide accurate license plate detection, seamless vehicle tracking, integration with watchlists, and effortless compatibility with IP cameras.

The Future of AI in Transport is Smarter Integration, Greater Efficiency, and Stronger Governance

With government investment and support for AI initiatives, further advancements in AI-driven transport applications are expected. This has the potential to significantly improve public services and optimise transport operations across the UK.

As AI develops, it will no longer be used for specific tasks in isolated areas, like predicting train delays, and instead will evolve to make decisions in a more connected way. AI will increasingly share and use information across different systems, like public transport, traffic management, and ride-sharing to understand the bigger picture and make smarter, more coordinated decisions.

Consequently, more complex business use cases will be able to be executed or handled by AI to dramatically increase efficiency and the speed at which decisions can be made and actions taken. Such advanced automation requires robust regulation, stringent data security, and oversight to prevent unintended consequences. As AI continues to reshape industries, ensuring safety, ethical compliance, and accountability must be at the forefront of its development and deployment.