Decision Support Strategies for Household Water Consumption Behaviors Based on Advanced Recommender Systems

Arsene, Diana; Predescu, Alexandru; Truică, Ciprian-Octavian; Apostol, Elena-Simona; Mocanu, Mariana

doi:10.3390/w15142550

Cited by 4 publications

(4 citation statements)

References 31 publications

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“…Simplified household water consumption data as a basis for recommending changes in consumption behavior (for shower, bathtub, toilet, and kitchen, the data describes liter p.a.). In the context of optimizing household water consumption, recommender systems can be applied to sensitize users in terms of adapting, i.e., reducing their water consumption (Arsene et al, 2023). Table 12 provides a simple example dataset representing different households with corresponding consumption data.…”

Section: Tablementioning

confidence: 99%

“…Household h 1 can be regarded as a nearest neighbor of household h 3 . The corresponding differences in consumption can be used as a basis for generating corresponding explanations (Arsene et al, 2023). Depending on the water device specific differences, recommendations can propose actions such as taking shorter showers, using lower-flow shower-heads, and turning off taps during tooth-brushing (Arsene et al, 2023).…”

Section: Householdmentioning

confidence: 99%

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Reviews in Recommender Systems: 2022

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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Section: Tablementioning

confidence: 99%

Section: Householdmentioning

confidence: 99%

Reviews in Recommender Systems: 2022

2024

Frontiers Research Topics

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“…In the context of optimizing household water consumption, recommender systems can be applied to sensitize users in terms of adapting, i.e., reducing their water consumption (Arsene et al, 2023 ). Table 12 provides a simple example dataset representing different households with corresponding consumption data.…”

Section: Recommender Systems For Sustainabilitymentioning

confidence: 99%

“…Household h 1 can be regarded as a nearest neighbor of household h 3 . The corresponding differences in consumption can be used as a basis for generating corresponding explanations (Arsene et al, 2023 ). Depending on the water device specific differences, recommendations can propose actions such as taking shorter showers, using lower-flow shower-heads, and turning off taps during tooth-brushing (Arsene et al, 2023 ).…”

Section: Recommender Systems For Sustainabilitymentioning

confidence: 99%

Recommender systems for sustainability: overview and research issues

Felfernig,

Wundara,

Tran

et al. 2023

Front. Big Data

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Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.

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Automatic Detection of Water Consumption Temporal Patterns in a Residential Area in Northen Italy

Cristiano,

Biddau,

Delogu

et al. 2024

Water Resour Manage

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One of the main challenges for city development is to ensure a sustainable water resource management for the water supply system. A clear identification of the urban water consumption patterns supports policy and decision makers in managing the water resources, satisfying the total demand and, at the same time, reducing losses and identifying potential leakages or other issues in the distribution network. High resolution smart meters have widely shown to be an efficient tool to measure in-pipe water consumption. The collected data can be used to identify water demand patterns at different temporal and spatial scales, reaching the end-uses level. Water consumption patterns at building level can be influenced by multiple factors, such as socio-demographic aspects, seasonality, and house characteristics. The presence of a garden that requires summer irrigation strongly alters the daily consumption pattern. In this framework, we present an innovative approach to automatically detect the presence of garden irrigation, identifying daily average water consumption patterns with and without it. The proposed methodology was tested in a residential area in Northen Italy, where 23 smart meters recorded data at 1-minute resolution for two years. Results show very good performances in distinguishing between days with and without garden irrigation. The derived average normalized water consumption patterns for both scenarios can help decision makers and water managers to regulate the pressure regimes in the distribution network correctly.

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Decision Support Strategies for Household Water Consumption Behaviors Based on Advanced Recommender Systems

Cited by 4 publications

References 31 publications

Reviews in Recommender Systems: 2022

Reviews in Recommender Systems: 2022

Recommender systems for sustainability: overview and research issues

Automatic Detection of Water Consumption Temporal Patterns in a Residential Area in Northen Italy

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