Leakage Detection and Automatic Billing in Water Distribution Systems Using Smart Sensors
Kofi Sarpong Adu-Manu (),
Charles Adjetey and
Nana Yaw Ofosu Apea
Additional contact information
Kofi Sarpong Adu-Manu: University of Ghana
Charles Adjetey: Lancaster University
Nana Yaw Ofosu Apea: Valley View University
A chapter in Digital Transformation for Sustainability, 2022, pp 251-270 from Springer
Abstract:
Abstract Reading household and industrial meters are essential activities performed by water companies in most developing countries. Meter readings involve the collection of water consumption units, diagnostics, and status data from the meter devices. In Ghana, meter reading officers go from house to house, institutions, organizations, and other consumers to record the water consumed every month. Two main challenges arise from manual water readings: (1) under-reading, which results in undercharging the customer, and (2) over-reading, which results in overcharging the customer. In each case, either the utility company or the customer is affected during the billing processes. This study adopted wireless sensor devices to automatically collect water readings and detect leakages in pipes. The sensors are configured with a set calibration factor to measure water flow readings accurately. We discovered that the sensors could detect leakages in the pipe by analyzing the readings obtained. Our results showed that an automatic water monitoring system accurately measures water consumption. We observed that 20 ml/sec and 30 ml/sec were recorded from the two sensors at low pressures. The volumes recorded were 500 ml/sec at high pressures, indicating that the volume of water increases at high pressures.
Keywords: Water Leakage Detection; Smart Sensors; Water Distribution System; Smart Meter Billing; Wireless Sensor Networks; WSNs (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-15420-1_12
Ordering information: This item can be ordered from
http://www.springer.com/9783031154201
DOI: 10.1007/978-3-031-15420-1_12
Access Statistics for this chapter
More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().