A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems

Abstract

A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

Keywords: biofilm; energy harvesting; impedance; interdigitated microelectrodes; scaling; smart pipe; wireless sensor network.

Figure 1

The architecture of the proposed network composed of sensing nodes (monitoring 6 chemo-physical water parameters) powered by kinetic energy harvesting and connected through long-range radio links to a Cloud server, providing visualization, feedback control, and analytics.

Figure 2

User interface of the ThingSpeak™ Cloud displaying in real-time acquired data on a password-protected website (a) and on smartphone app (b). Possible installation approaches of the sensing node: (c) in the main pipe or (d) in a derivation branch, whose flow can be controlled.

Figure 3

Slime thickness monitor based on planar interdigitated microelectrodes (a), of thickness t_e, width W, and spacing D (b), fabricated in different technologies and geometries (c). Impedance is measured at a single frequency f_s.

Figure 4

Photograph of the fully assembled node, showing the in-line sensors, the plastic holder of the slime monitor, the electronic boards, and the GSM antenna.

Figure 5

Scheme of the electronic platform, controlling the node: it is composed of the main board for conditioning, acquiring, and transmitting data and by a power management board for harvesting.

Figure 6

Laboratory setups for dynamic and continuous characterization of the sensors in the hydraulic loop with controlled conditions of temperature, flow, chemical concentration, and pressure: up to 4 bar in the low-pressure loop (a) and up to 9 bar in the high-pressure one (b).

Figure 7

The response curve of the slime monitor for increasing thickness H of limestone, showing three regions of sensitivity.

Figure 8

Map of the installation sites of the three nodes during the field validation in a water distribution network in Romagna, Italy. They are located in Y-junction.

Figure 9

Temperature values recorded for the three nodes for 50 days (a), and elaboration, showing daily variations (b) and correlation (c) between Node 1 and 3.

Figure 10

Normalized conductivity tracking for 3 identical probes in Node 3, showing fault detection and isolation of Probe 1 (whose fault was stimulated on purpose).

Figure 11

Recording of the node current consumption during an operation cycle.

Figure 12

Operation of the energy harvesting unit, showing the display of the DC/DC converter for two values of the water flow rate Q in the pipe. The power manager sets an output voltage 6 V and selects the optimal battery charging current.