This truly spectacular case study demonstrates what can be achieved using s::can sensors in a complete water quality monitoring station setup. In this case, the s::can system was designed to capture pollution events along the entire length of a river to both define the baseline water quality, and identify point sources of pollution.
The remote water quality stations consisted of a spectro::lyser, a pH::lyser, a condu::lyser, an oxi::lyser and an ammo::lyser to continuously monitor 11 parameters. In addition to monitoring COD, BOD, NO3, NO2, TSS, pH, O2, EC, NH4+, Cl– and temperature, the event detection software ana::tool was used to utilise the full UV-Vis spectral data to identify and characterise pollution events. The keep power consumption low, the spectro::lyser was cleaned using a rucksack submersible brush. The initial ten stations in the pilot utilised compressed air cleaning.
All the real-time data generated was sent back using the concube controller via a GPRS network to a central repository where it could be analysed and used to track long-term water quality throughout the river. 36 of these stations are now in place in the river.
River water quality monitoring and big data - a service-led approach to real-time water quality monitoring.
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