Urban Air Quality & Traffic Analytics
Urban Air Quality & Traffic Flow Analytics.
A metropolitan municipality sought to understand the relationship between traffic congestion patterns and air quality deterioration across their city center. Existing fixed air quality monitoring stations were too sparse (only 3 stations for a 450 km2 area) to capture hyperlocal pollution hotspots near schools, hospitals, and high-traffic intersections.
Artes Solution designed and deployed a dense IoT sensor network with 85 air quality nodes and 40 traffic counting stations across the city. Each air quality node measures PM2.5, PM10, NO2, O3, CO, temperature, and humidity at 1-minute intervals. Traffic nodes use radar-based vehicle detection to count traffic volume, classify vehicle types, and measure average speed on major arterial roads - all connected via LoRaWAN and 4G cellular networks.
The correlation analytics revealed that 3 specific intersections were responsible for 28% of the city center's PM2.5 peaks during morning rush hours. The municipality used this data to implement signal timing optimizations and low-emission zone policies that reduced peak PM2.5 levels by 19% within the first year. The public-facing air quality map increased citizen awareness and won the municipality a national Smart City Innovation award.
Project Results
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PM2.5 Reduction
19% -
Monitoring Coverage
94%
System Architecture.
Air Quality Sensor Nodes
Custom IP67-rated enclosures with Sensirion SPS30 (PM2.5/PM10 laser scattering), Alphasense electrochemical cells (NO2, O3, CO), and BME680 (temperature, humidity, pressure). Each node includes an ESP32 MCU, 4G Cat-M1 modem, GPS receiver, and solar panel with supercapacitor backup. Automated fan-based intake with heated inlet prevents condensation and ensures measurement accuracy across all weather conditions.
Traffic Detection Stations
Radar-based vehicle detection (24GHz FMCW) mounted on existing street light poles. Each station detects vehicle count, speed, and classifies into 4 categories (car, bus/truck, motorcycle, bicycle) across up to 4 lanes simultaneously. No camera or privacy concerns - pure radar signatures ensure GDPR compliance while providing accurate traffic flow data at 1-minute aggregation intervals.
Correlation Analytics
Time-series correlation analysis between traffic volume/composition and pollutant concentrations with wind direction and speed adjustments. Spatial dispersion modeling identifies which road segments contribute most to pollution at sensitive receptor points (schools, hospitals). Machine learning models predict next-day air quality based on traffic patterns and weather forecasts.
Public Air Quality Map
Citizen-facing web application with real-time air quality index (AQI) map using color-coded markers. Spatial interpolation between sensor nodes creates continuous pollution surface visualization. Health recommendations based on WHO guidelines, 24-hour forecast, and historical comparison charts. Available in Turkish and English with accessibility features for visually impaired users.
Signal Optimization
Traffic flow data feeds into the municipality's adaptive signal control system to optimize green wave corridors during peak hours. Congestion detection triggers dynamic speed limit recommendations on variable message signs. The system identified 3 critical bottleneck intersections where signal retiming alone reduced idling time by 23% and associated emissions.
Open Data Platform
RESTful API providing real-time and historical air quality and traffic data to researchers, app developers, and other city departments. InfluxDB time-series storage with Grafana dashboards for internal municipal use. Data export in CSV, JSON, and SensorThings API format for EU environmental reporting compliance and academic research partnerships.
Building a Smarter City?
From air quality monitoring to traffic analytics, parking management, and smart lighting, we help municipalities deploy IoT infrastructure that improves citizens' quality of life with measurable, data-driven outcomes.
