The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device.

A portable and automated IC system with a dual-capability for the analysis of both fresh and saline environmental waters has been developed. Detection of nitrate in complex matrices such as seawater was achieved by the employment of an automated two-dimensional (heart-cut) IC method utilised in tandem with on-column matrix elimination, using a sodium chloride eluent. The system also demonstrated the capability to switch to a second mode of analysis, whereby direct one-dimensional IC analysis was employed to rapidly detect nitrite and nitrate in freshwater, with direct UV LED based absorption detection in under 3 minutes. Calibration curves using a 195 µL sample loop were generated for both freshwater and artificial seawater samples. For marine analysis, an analytical range of 0.1 mg L-1 - 40 mg L-1 NO3- was possible, while an analytical range (0.1 mg L-1 - 15 mg L-1 NO2-, 0.2 - 30 mg L-1 NO3-) appropriate for freshwater analysis was also achieved. Chromatographic repeatability for both marine and freshwater analysis was verified over 40 sequential runs with RSD values of < 1% demonstrated for both peak area and retention times for each mode of analysis. The selectivity of both methods was demonstrated with interference tests with common anions present in environmental waters. Recovery analysis was carried out on marine samples from Tramore Bay, Co. Waterford, Ireland, and the systems analytical performance was compared with that of an accredited IC following environmental sample analysis.