Open Datasets and IoT Sensors for Residential Water Demand Monitoring at the End-Use Level: A Pilot Study Site in Naples (Italy)

Mauro, Anna Di; Santonastaso, Giovanni Francesco; Venticinque, Salvatore; Nardo, Armando Di

doi:10.1007/978-3-030-95844-2_4

Cited by 1 publication

(1 citation statement)

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“…The proposed solution promotes awareness of the use of water resources, encouraging consumers and suppliers to make the right decisions to maintain a sustainable water supply system. An IoT-based pilot study was described in [7] for monitoring water consumption in a residential apartment in Naples. The data collected are public and can be used by the community to train different algorithms in order to raise awareness of responsible consumption, promoting water conservation.…”

Section: Introductionmentioning

confidence: 99%

Advanced Strategies for Monitoring Water Consumption Patterns in Households Based on IoT and Machine Learning

Arsene

Predescu

Pahonțu

et al. 2022

Water

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Water resource management represents a fundamental aspect of a modern society. Urban areas present multiple challenges requiring complex solutions, which include multidomain approaches related to the integration of advanced technologies. Water consumption monitoring applications play a significant role in increasing awareness, while machine learning has been proven for the design of intelligent solutions in this field. This paper presents an approach for monitoring and predicting water consumption from the most important water outlets in a household based on a proposed IoT solution. Data processing pipelines were defined, including K-means clustering and evaluation metrics, extracting consumption events, and training classification methods for predicting consumption sources. Continuous water consumption monitoring offers multiple benefits toward improving decision support by combining modern processing techniques, algorithms, and methods.

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Section: Introductionmentioning

confidence: 99%