Please use this identifier to cite or link to this item: https://etd.cput.ac.za/handle/20.500.11838/4054
Title: Smart monitoring of sewage infrastructure to alleviate environmental pollution
Authors: Ndlovu, Musawenkosi 
Keywords: Environmental pollution;Sewage -- Environmental aspects;Sewage disposal;Sewerage -- Maintenance and repair;Sewage disposal plants;Sewage -- Purification;Environmental protection;Environmental protection;Smart sensors;Real-time monitoring;IEEE standards;Ndlambe Local Municipality
Issue Date: 2024
Publisher: Cape Peninsula University of Technology
Abstract: The problem of environmental pollution resulting from sewage spillage is a significant concern in South Africa, a country with aging infrastructure. Municipalities, particularly local municipalities located in rural and semi-rural areas, are tasked with the collection and treatment of household sewage. Manual monitoring methods currently in use are labour-intensive, prone to inaccuracies, and lack real-time data capabilities. This study investigates the feasibility of deploying intelligent monitoring technology to address sewage-related pollution issues. The proposed intelligence involves the utilization of sensors capable of real-time data collection and feedback, aimed at preventing sewage spillage and addressing it promptly. The research is conducted within a local municipality in semi-rural South Africa, serving as a worst-case scenario with findings applicable to more developed regions within the country. The envisioned system leverages advanced technologies and adheres to IEEE standards such as IEEE 1451 for sensor interoperability and IEEE 802.11 for wireless communication. Its primary objectives are real-time monitoring, early pollution detection, and rapid intervention to prevent sewage spillage. A comprehensive literature review highlights the shortcomings of manual sewage monitoring and explores the potential of smart sensors and data-driven solutions in mitigating sewage pollution. The research involves the development of monitoring models and data analytics using MATLAB, with a specific focus on the pump station and sump section of the sewer network. The implementation of this smart sensor and data-driven sewage monitoring system enhances resource allocation efficiency, enables targeted maintenance, and ensures timely responses. The integration of electrical and automation technologies further enhances the reliability, accuracy, and scalability of sewage monitoring operations. The study's findings contribute to the formulation of effective pollution management strategies, inform policy-making decisions, and provide guidance for the implementation of smart monitoring systems in municipalities. These outcomes contribute to sustainable development efforts and a cleaner, healthier environment in South Africa, offering a transferable solution applicable to regions worldwide facing similar challenges.
Description: Thesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2024
URI: https://etd.cput.ac.za/handle/20.500.11838/4054
DOI: https://doi.org/10.25381/cput.25225124.v1
Appears in Collections:Electrical, Electronic and Computer Engineering - Master's Degree

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