In August 2025 I completed Yunex Traffic's Smart Mobility and Environmental Sustainability virtual work experience via Springpod. Yunex Traffic is one of the largest providers of intelligent transport systems in the world. The programme explored how digital technology improves urban air quality and traffic efficiency.
Before this experience, I thought of traffic lights as solved infrastructure. I was wrong.
What Yunex Traffic actually does.
Yunex Traffic designs and operates intelligent transport systems. This includes traffic signal controllers, adaptive signal control software, vehicle detection sensors and urban traffic management centres. Their systems are deployed across hundreds of cities and directly influence how millions of road users move every day.
The connection to IoT is direct. Sensors collect data at intersections, cameras detect vehicle types and counts and software makes real-time decisions to optimise traffic flow. Modern traffic management is a distributed IoT system operating at city scale with real safety and environmental consequences.
Adaptive signal control is the part that interests me most. Rather than running on a fixed timer, an adaptive system uses real-time vehicle detection data to extend or reduce green phases based on actual demand. This reduces idling, improves throughput and decreases the stop-and-start cycling that contributes most to vehicle emissions at urban junctions.
Zephyr air quality sensors.
The most technically interesting part of the programme was the Zephyr air quality monitoring system. Zephyr sensors measure nitrogen dioxide, ozone and particulate matter in real time using electrochemical and optical methods. These pollutants are directly linked to respiratory health and are regulated under UK and EU air quality standards.
The data pipeline from a Zephyr sensor to a policy decision is a good example of how engineering and public health connect in practice. A sensor reading below a threshold is just a number. But connected to a traffic signal timing algorithm, a reading above a nitrogen dioxide threshold can trigger an adaptive response: extending green phases to reduce idling, rerouting heavy vehicles away from school zones or generating an alert for the local authority's air quality team.
For the programme I produced an infographic explaining how Zephyr sensors are deployed in an urban environment, how data transmits in near real time to a cloud platform and how local authorities use the readings against air quality index thresholds to make operational decisions. Building the infographic required understanding the full pipeline from sensor to policy. That exercise is one I returned to when designing the Phaemos data pipeline. The questions are structurally identical: how does a raw sensor reading become a decision a human can act on?
The engineering roles.
The programme gave insight into different career paths within Yunex Traffic. Software engineers build the traffic management platforms and adaptive control algorithms. Electrical and systems engineers design and qualify sensor hardware for outdoor deployment across all weather conditions. Project managers coordinate city-scale deployments spanning multiple local authorities, contractors and regulatory certification bodies.
What struck me is that the engineering challenges at Yunex Traffic are the same challenges I am working on in miniature with Phaemos: reliable sensor data collection, a processing pipeline that handles data faster than it arrives, anomaly detection that distinguishes signal from noise and a human-facing interface that presents the right information at the right moment. The scale differs by several orders of magnitude. The fundamental structure is identical.
What I took from it.
Smart city technology is not abstract. It is physical infrastructure that affects air quality, journey times and road safety for real people every day. The engineering behind a traffic signal controller or an air quality sensor network is not glamorous in the way a consumer product might be but the scale and the measurable real-world impact are significant.
This confirmed my interest in IoT at scale: systems where sensors, connectivity, real-time data processing and measurable outcomes are connected in a continuous feedback loop. That is the kind of engineering I want to build.
Thank you for reading. More issues to come.
Zac
