Product hardware

During the REVIS project, TerOpta has developed a sensing system which monitors ambient air quality in external environments. Fully cloud-connected via in-built 2G/4G cellular technology, each self-contained unit monitors multiple pollutants and other atmospheric conditions, reporting autonomously to a cloud-based analysis platform. Capable of mounting on poles, posts or walls, the unit is installed by simply connecting a 12V DC power supply. It will then automatically and securely connect to the TerOpta cloud and begin sending data immediately with no user intervention. Extensions to measure ambient noise (SPL) and local road traffic types and volumes are in development

Parameters measured

  • Nitrogen Dioxide
  • Carbon Dioxide
  • Particulate Matter
  • Temperature
  • Relative Humidity
  • Atmospheric Pressure
  • Geographic Location
Measured quantity Units Accuracy Comments
Temperature °C ±0.4 For best accuracy, protect unit from direct sunlight
Relative Humidity % ±3 start of life
±0.25 /yr drift
For best accuracy, protect unit from direct sunlight
Pressure hPa ±1
PM2.5 and PM10 µ/m3 ±10 µ/m3 ±10 % Over 0 − 100 µ/m3 range Over 100 − 1000 µ/m3 range
CO2 ppm ±(30ppm +3% of reading)
NO2 µ/m3 Approx. ±15 Preliminary. Note that unit is designed to provide sufficient accuracy to indicate DEFRA Daily Air Quality Index (DAQI) levels for NO2

The Teropta hardware unit has been designed to comply with all the following regulations

Radio Equipment Directive (2014/53/EU), IEC 62368-1 Audio/video, information and communication technology equipment ‐ Part 1: Safety requirements, EN61000-6-1 Electromagnetic compatibility (EMC) ‐ Part 6-1: Generic standards ‐ Immunity, EN 61000-6-3 Electromagnetic compatibility (EMC) ‐ Part 6-3: Generic standards ‐ Emissions, RoHS (2011/65/EU) as amended by Directive (EU) 2015/863, WEEE (2012/19/EU).

  • 186 x 164 x 64 mm ruggedized enclosure
  • Capable of mounting on poles, posts, walls or other surfaces
  • Average power consumption <0.3 Watts ‐ can be solar powered
  • Waterproof "M12" connector for power and serial communication interface for connection to extension units e.g. traffic type and count
Pin 1 RS-232 Serial Transmit
Pin 2 Supply (+11 to +14.5 V DC)
Pin 3 Ground (0V)
Pin 4 RS-232 Serial Receive
Pin 5 Not Connected

Complimentary Machine Learning Data

Using CCTV data that can be accessed through the customers existing infrastructure, REVIS can undertake machine learning to make predictive analysis based on vehicle flows, regular journeys by the public and vehicle usage patterns.

REVIS Traffic pattern and speed analyser uses a camera and does real-time on-board processing of traffic flow using Artificial Intelligence and object detection models. All data is processed on-device and only the processed traffic patterns are reported in keeping with strict confidentiality and data protection. Hourly Traffic density and average speed will allow councils to determine and demonstrate the impact of traffic density, traffic type and speed limits on NO2 and carbon emissions.

REVIS graphic
  • Support vehicle types: Heavy goods, Light goods, Buses, Vans, Cars, Plant
  • Minimum vehicle size: 30x30 pixels
  • Accuracy of classifying vehicle type (ie. Car, Van, Bus, Mini, Sedan): greater than 95%
  • Max traffic speed: 60 mph
  • View angles: front, rear, side view
Image of traffic monitoring

System Architecture

During our development phase the infrastructure is hosted on an on-site server (located at UWE, Bristol) with plans for the system and AI models to be moved to a secure cloud platform once the project goes live. Sensor data from REVIS will be pushed through Telit (IoT cloud service) and other external public sources such as UK Air department and UK Met Office, where they will be aggregated and stored for trend analysis on the same server.

Data loss and protection against theft are ensured using robust daily backups and secure data encryption/redaction techniques.