Design and Implementation of a Self-Powered Smart Water Meter

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.

Section: Introductionmentioning

confidence: 99%

Image-Based Automatic Watermeter Reading under Challenging Environments

Hong

Yiwei

Lin

et al. 2021

“…Water and energy are strictly entangled: energy is used to treat and distribute water, while energy can be also harvested from water flows, especially in order to monitor its quantity and quality [27]. A demonstration of this nexus is the flourishing of self-powered devices and networks for smart metering, leveraging Internet-of-Things (IoT) electronics for monitoring water quality and consumption, especially aiming at leakage reduction [28,29]. Energy can be harvested from the flow of fluids in several ways [30,31], improving the efficiency, stability, and compactness commonly achieved, for instance, by solar panels [8].…”

Section: Introductionmentioning

confidence: 99%

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

Carminati

Turolla

Mezzera

et al. 2020

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.

Section: Introductionmentioning

confidence: 99%

“…Recently, these mechanical flow meters have been equipped with additional electronics allowing them to read remotely. These water meters are indicated as AMR (Automatic meter reading) [ 15 ]. The number of these water meters in the Czech Republic is still low, mainly due to the purchase price paid by the end customer.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Slaný

Lucansky

Koudelka

et al. 2020

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%.