Cities usually measure air quality at a small number of fixed stations and estimate conditions everywhere in between. For pollutants that vary over short distances — dust, traffic gases, pollen — that leaves most streets unmeasured. Adding enough fixed devices to close the gap means more sites, equipment, power, permits and maintenance, a cost few cities can justify for monitoring no regulation requires.
Refuse collection vehicles already travel every street on a predictable schedule. Fitting them with environmental sensors turns those rounds into a moving survey of the city at very little marginal cost. In Fujisawa, each vehicle carried a custom sensor board running a CIL-based virtual machine developed by NTT, with a u-blox C027 mbed board for communications. GPS positions were logged every second and readings were sent over 3G every 30 seconds to a remote server using XMPP.
Because the routes repeat, the data is consistent over time as well as dense in space. The same dataset serves two audiences: residents get street-level pollen and PM2.5 information to plan their day, and the city gets location and route data it can use to optimise collection rounds, reducing mileage and CO₂ emissions.
– Thirteen atmospheric parameters: carbon monoxide, ozone, nitrogen dioxide, two further pollutant gases, dust, PM2.5, pollen, light, UV, temperature, humidity and background noise
– GPS positioning every second, data transmission every 30 seconds over 3G
– Custom sensor board with a CIL-based virtual machine (NTT) and u-blox C027 mbed communications board
– XMPP messaging to a remote server and into the BigClouT city data platform
– Route and location data reusable for collection-route optimisation
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