| Autor: |
R Shanthini, Y Sowmiya, M Swetha, M Lakshmanan, M Ashokraj |
| Jazyk: |
English<br />French |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
E3S Web of Conferences, Vol 399, p 02006 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202339902006 |
| Popis: |
This system for monitoring and identifying theft from domestic water supplies utilizes advanced sensors and machine learning algorithms to detect and analyze patterns of water usage, identifying anomalies and potential instances of theft. The system can be easily installed and integrated into existing water supply infrastructure, allowing for real-time monitoring and analysis of water usage data. By providing actionable insights and alerts, the system enables water supply companies to quickly respond to instances of theft, reducing losses and ensuring a more equitable distribution of resources. It utilizes various sensors and algorithms to detect anomalies in water usage patterns, which could indicate theft. The system includes a dashboard that allows water supply companies to monitor usage and receive alerts in real-time. By using this system, water supply companies can improve their efficiency, reduce water losses, and save costs associated with theft. The system is easy to install and can be integrated with existing water supply networks. The system has the potential to significantly reduce water losses due to theft, improving water supply sustainability and reducing costs for water providers. The system has the potential to significantly reduce water losses due to theft, improving water supply. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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