Advanced Techniques for Monitoring and Management of Urban Water Infrastructures—An Overview

Hângan, Anca; Chiru, Costin-Gabriel; Arsene, Diana; Czako, Zoltan; Lisman, Dragos Florin; Mocanu, Mariana; Pahonțu, Bogdan; Predescu, Alexandru; Sebestyen, Gheorghe

doi:10.3390/w14142174

Cited by 18 publications

(15 citation statements)

References 135 publications

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“…(Leadership in Energy and Environmental Design) is frequently employed, sought after by many businesses in their business plans [6]. Consumption signatures are used to identify the individual consumption of each device [7], enabling the identification of more complex consumption patterns.…”

Section: Methodsmentioning

confidence: 99%

“…While studies on urban water consumption in broad areas have been conducted [5], research on specific buildings is scarce. For individual buildings, the LEED certification (Leadership in Energy and Environmental Design) is frequently employed, sought after by many businesses in their business plans [6]. Consumption signatures are used to identify the individual consumption of each device [7], enabling the identification of more complex consumption patterns.…”

Section: Introductionmentioning

confidence: 99%

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The Scientific Landscape of Smart Water Meters: A Comprehensive Review

Zapata-Sierra,

Salmerón-Manzano,

Alcayde

et al. 2023

Water

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This review underscores the escalating global research trend in this field since 2000. The primary scientific disciplines contributing to extensive research on smart water meters are engineering, computer science, and energy. In terms of countries, the analysis reveals that the United States, India, and China exhibit the highest scientific production. Concerning affiliations, prominent contributors include Griffith University, Politecnico di Milano, and the Università degli Studi di Salerno. Regarding worldwide research trends, an examination of distinct clusters defined by their principal keywords was conducted. The following clusters were identified in order of significance based on the number of publications: Urban Water Meters, IoT Connection, Communication and Security, Grid Management, Water Networks, Hot Water, Groundwater Monitoring, and Smart Irrigation. Of particular note is the growing use of machine learning applications, especially in the management of distribution networks. This trend opens up a promising avenue for addressing complex problems in real time.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Scientific Landscape of Smart Water Meters: A Comprehensive Review

Zapata-Sierra,

Salmerón-Manzano,

Alcayde

et al. 2023

Water

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“…Linjing et al (2020) explain the benefits and standout characteristics of blockchain-enabled IoT applications and contrast them with centralized, more established IoT-based smart water systems. Hangan et al (2022) examine the potential applications of big data and blockchain in the field of water resources and argue that blockchain can act as a link between a locally used solution and a global infrastructure that is accessible globally and is controlled by a coalition of international organizations using consensus mechanisms.…”

Section: Water Governancementioning

confidence: 99%

Blockchain Applications and Opportunities for Water Resources and Hydrology: A Systematic Review

Satilmsioglu¹,

Sermet²,

Demir³

2023

Preprint

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Although blockchain technology was first applied for peer-to-peer financial transactions, it has been used for the digitalization of physical asset management and data management processes in many areas in the industry and academia, including the water domain. Its potential as an immutable data storage system and smart contract integration has provided a plethora of use cases and utility in the domain of hydrology and water resources. In this article, a comprehensive systematic literature review on blockchain applications, opportunities and challenges for the water sector is conducted. The study provides the examination of academic publications, technical reports, whitepapers, hackathon projects, non-academic content and evaluation of the published year, focused hydrology sub-domain, utilized blockchain networks, tools, and development level of application of reviewed content. The current status of blockchain technology in the hydrology literature, potential application areas in the water sector, research gaps, and challenges are discussed from different perspectives, and future study areas are recommended.

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“…It is worth mentioning two of the predictive models using meaningful physical, chemical, and microbial indicators, namely, the Adaptive Frequency Analysis proposed to solve scalability in the time domain [15], and the LASSO (Least Absolute Shrinkage and Selection Operator) regression model proposed to predict the biological risk [16]. Moreover, computational intelligence techniques are developed and tested on a small scale, aiming to achieve smart water management systems [17]. On the other hand, when large training sets cannot be provided in water supply systems, statistic modelling of data remains a useful tool, i.e., for depicting regional models of drinking water quality.…”

Section: Introductionmentioning

confidence: 99%

A Multivariate Model of Drinking Water Quality Based on Regular Monitoring of Radioactivity and Chemical Composition

Tăban,

Benedek,

Stoia

et al. 2023

Applied Sciences

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From a public health perspective, the monitoring of water quality intended for human consumption belongs to the operational and audit management of the supply zones. Our study explores the spatial and temporal patterns of the parameters of drinking water in Sibiu County, Romania. We related the relevant physical-chemical parameters (ammonia, chlorine, nitrates, Al, Fe, Pb, Cd, Mn, pH, conductivity, turbidity, and oxidizability) and radioactivity (gross alpha activity, gross beta activity, and radon-222 content) from a 5-year survey to the water source (surface water and groundwater, which may be of subsurface or deep origin), space (sampling locality) and time (sampling month and year). We conducted a combined evaluation using the generalized linear mixed models (GLMMs), Pearson correlation analysis of the physical-chemical parameter, multivariate linear redundancy analysis (RDA), t-value biplots construction, and co-inertia analysis. The obtained regional model shows that the source, locality, and month of sampling are significant factors in physical-chemical parameters’ variation. Fe and turbidity have significantly higher values in surface water, and nitrates and conductivity in groundwater. The highest values are recorded in January (nitrates), March (Cl, ammonia, pH) and August (Fe, turbidity). The RDA ordination diagram illustrates the localities with particular or similar characteristics of drinking water, two of which (rural sources) being of concern. The water source is the best predictor for radioactivity, which increases from surface to ground. The gross alpha and beta activities are significantly and positively correlated, and are both correlated with conductivity. In addition, the gross alpha activity is positively correlated with nitrates and negatively with pH, while the gross beta activity is positively correlated with Mn and negatively with Fe; these relationships are also revealed by the co-inertia analysis. In conclusion, our model using multilevel statistical techniques illustrates a potential approach to short-term dynamics of water quality which will be useful to local authorities.

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Advanced Techniques for Monitoring and Management of Urban Water Infrastructures—An Overview

Cited by 18 publications

References 135 publications

The Scientific Landscape of Smart Water Meters: A Comprehensive Review

The Scientific Landscape of Smart Water Meters: A Comprehensive Review

Blockchain Applications and Opportunities for Water Resources and Hydrology: A Systematic Review

A Multivariate Model of Drinking Water Quality Based on Regular Monitoring of Radioactivity and Chemical Composition

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