An Integrated IoT Architecture for Smart Metering Using Next Generation Sensor for Water Management Based on LoRaWAN Technology: A Pilot Study

Author:

Slaný VlastimilORCID,Lučanský Adam,Koudelka Petr,Mareček Jan,Krčálová Eva,Martínek RadekORCID

Abstract

This pilot study focuses on the design, implementation, optimization and verification of a novel solution of smart measuring of water consumption and crisis detection leading to a smart water management platform. The system implemented consists of a modular IoT platform based on a PCB (Printed Circuit Board) design using the M2.COM standard, a LoraWAN modem and a LoraWAN gateway based on the Raspberry Pi platform. The prototype is modular, low-cost, low-power, low-complex and it fully reflects the requirements of strategic technological concepts of Smart City and Industry 4.0, i.e., data integration, interoperability, (I)IoT, etc. The study was produced in cooperation with M.I.S Protivanov and VODARENSKA AKCIOVA SPOLECNOST, a.s. (industry partners distributing drinking water in the Olomouc and South-Moravian regions) to depict the current situation in the Czech Republic, characterized by extreme weather fluctuations and increasingly frequent periods of drought. These drinking water distributors are also constantly placing new demands on these smart solutions. These requirements include, above all, reliability of data transmission, modularity and, last but not least, low cost. However, smart water management (water consumption, distribution, system identification, equipment maintenance, etc.) is becoming an important topic worldwide. The functionality of the system was first verified in laboratory conditions and, then, in real operation. The study also includes checking signal propagation in the municipal area of the village of Zdarna, where the radius of the proposed measuring system was tested. A laboratory test with simulation of water leakage is also part of this work. Subsequently, the system was tested in a residential unit by means of water leakage detection using the MNF method (minimum night flow); the detection success rate was 95%.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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