Document Details

Document Type : Thesis 
Document Title :
Monitoring and Detecting Water Leakage Using LoRaWAN in A Housing Complex
مراقبة واكتشاف تسرب المياه باستخدام الشبكة الواسعة بعيدة المدى في المجمع السكني
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : The automation of water leakage detection and monitoring systems has recently been made possible by the Internet of Things (IoT). However, the high cost is an obstacle when applying a network over a large area. The Low-Power Wide-Area Network (LPWAN) was created specifically to address long-range IoT applications. The Long-Range Wide-Area Network (LoRaWAN) is one of the most common LPWANs. In this study, a method for monitoring and detecting water leakage in a housing complex was tested using LoRaWAN. Water leakage was detected using a low-pressure system model comprising a water meter, presser sensor, and smart valve within a LoRa node. This study investigates the use of LoRaWAN for water monitoring and leakage detection by implementing a comprehensive case study to identify LoRaWAN’s feasibility, reliability, and scalability for water monitoring and leakage detection in simulated scenarios. The housing complex varied in several nodes. The purpose of the research is to determine the most suitable transmission interval between notifications of water leakage alerts within a housing complex using LoRaWAN quickly at a low cost. The LoRaWAN was evaluated by the FloRa simulator package through the Objective Modular Network Testbed (OMNeT++) platform. The results indicated that it was an e cient means of water monitoring and leakage detection in housing complexes. Therefore, the most suitable interval for sending notifications to homeowners was ten minutes, based on several measurements in terms of packet delivery ratio, energy consumption, throughput, and collisions. Furthermore, the most suitable bandwidth was 250 kHz, which reduced the energy consumption at a high packet delivery ratio. 
Supervisor : Dr. Enas Fawzi Khairullah 
Thesis Type : Master Thesis 
Publishing Year : 1444 AH
2023 AD 
Added Date : Sunday, May 14, 2023 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
أثير محمد الغامديAlghamdi, Atheer MohammedResearcherMaster 

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 49194.pdf pdf 

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