Mobile monitoring system: Vehicles with sensors to control air quality in Glasgow

Countries throughout the world have a need, and in many cases a legal obligation, to ensure air quality is meeting specific standards. Policies aim to reduce exposure to air pollution, by reducing emissions and setting limits and targets for AQI. Public authorities in cities have deployed static stations to monitor air quality data for a set of pollutant with specific, and high cost, sensing technologies. These stations provide highly accurate data but their cost limits the quantity of deployments, leaving large gaps in coverage.

  • Libelium
    Libelium designs and manufactures Wireless Sensor Network devices so that system integrators, engineering, and consultancy companies can deliver reliable Internet of Things (IoT), M2M and Smart Cities solutions with minimum time to market.Waspmote—Libelium’s open wireless sensor platform—is modular, easy to deploy and ready to integrate with third-party Cloud systems such as Microsoft, IBM, Indra, Esri, ThingWorx, or MQTT.Over 2,000 developers from 115 countries in companies ranging from startups to universities to large international corporations have adopted Libelium’s hardware and software technology for projects in North America, Australia, Asia and Europe.Commercial deployments based on Waspmote include applications as varied as parking, traffic congestion, environmental monitoring, and precision agriculture.Established in 2006, Libelium is privately held and has headquarters in Zaragoza, Spain.
  • Analytics & Modeling - Big Data Analytics
    Networks & Connectivity - Gateways
    Networks & Connectivity - LoRa
    Sensors - Gas Sensors
  • Cities & Municipalities
  • Continuous Emission Monitoring Systems
  • CENSIS, the innovation center of excellence for Sensor and Imaging Systems (SIS) technologies, has developed a low-cost system with Libelium Waspmote Sensor Platform in Glasgow (UK) that can be deployed flexibly and rapidly in mobile configurations to com
  • CENSIS has worked in partnership with the University of Strathclyde on this project that has been called “Sensing the City”. The aim was monitoring in real time key air parameters in different areas from a city in a dynamic way. For this last reason, they thought in a mobile wireless sensor network system placed on top of the vans to move through all the city. “Our initial requirement was for sensor nodes with a variety of configuration options. From an evolution point of view, we now have the potential to add new sensor nodes or to change sensor nodes”, argues Stuart Simpson, CENSIS Senior Engineer. The sensor node consist on a box with the Waspmote Plug & Sense! Smart Environment PRO inside and also the different sensors: CO, Particle Matter – dust sensor, (PM1, PM2.5 and PM10), temperature, humidity, pressure, NO, NO2 and O3. These are some of the most important parameters to control air quality and detect gas emissions or pollutants. All the information monitored by the Waspmote Plug & Sense! Sensor Platform is sent to the sensor hub, which is located in the vehicle glove box, through 802.15.4. Its is composed by Raspberry Pi2, a GPS Antenna (to allow the tracking) and Zigbee. The information gathered is sent to the cloud via 3G and visualized in CitySense, based on Microsoft Azure IoT platform. CitySense is a web-based user interface that allows data visualization, interaction with the cloud services and includes capability to embed data processing and analytic outputs. The Decision Support System allows to create spatial and temporal high resolution air quality maps. A low-cost deployment with great possibilities “Sensing the City” project can provide indicative air quality data in areas without coverage in order to support identification of pollution sources. Mobile systems can also gather data in a volume and with the rapidity required to support comparison of pollution models and to identify trends.

  • Air Quality (PMI), Pollutants detection
  • Impact #1
    [Efficiency Improvement - Operation]
    “Sensing the City” project can provide indicative air quality data in areas without coverage in order to support identification of pollution sources.
    Impact #2
    Impact #3
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