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.

Case Study

Pollution monitoring in the Ganges - the pilot stage.

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River water quality monitoring and big data - a service-led approach to real-time water quality monitoring.

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Fowzie Smith-Tahir

Fowzie Smith-Tahir

Marketing and Design at PMA Ltd

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