A Spatial Framework for Managing Sewer and Water Networks Using Sensor Networks: A Case of the University of Zambia

Abstract

The University of Zambia like any public institution has a lot of infrastructure which require maintenance and management. There’s however uncertainty of the utility lines locations and their depths. This causes destruction of water pipes and sewer lines when undertaking new constructions or any excavations. The lack of accurate location of underground and un-updated lines makes maintenance, management and planning of the utilities very difficult. Therefore this study aimed to build a framework for Managing Sewer and Water Networks Using Sensor Networks at the University of Zambia. The Resident Engineer’s office only has some old scanned pdf sketches of both sewer and water networks. The field engineers locate most lines and other facilities using memory and experience. The methodology involved understating the existing operations of the Resident engineer’s office to ascertain the user needs. These needs formed the basis of the research, the development and design of the prototype of the Webbased Framework. Data Collection tools included Records (old maps) and Secondary Data (satellite images), Field Observations, Interviews and field Surveys. A presurvey (Reconnaissance Survey) was done to have an idea of the existing infrastructure and a more accurate survey was done using GPS GNSS equipment. The raw data was processed and GIS software was used to merge the collected datasets and the existing data. Georeferencing of existing maps and the satellite images was done using the GPS field data in ArcMap. New shapefiles were created from the point data from the survey and from digitising the existing scanned maps. New maps of the water and sewer networks (using the new shapefiles) and satellite imagery were created. A 15 digit coding system was created and was used to assign unique identification numbers and extra attribute information to the water and sewer network shapefiles. A QR code was generated for each node and the serial number recorded. Tagging was done using the QR code for each structure. All the shapefiles were loaded into a PostGreSQL spatial database and were used as input in the Web GIS application. The web application had some tools imbedded in it including; query, measure, add point/vertex, zoom, view, search and identify. Using internet of things (IOT) technology, water level sensors were placed on some critical manholes to help with the monitoring of the sewerage network. The system can therefore be used for identification of any infrastructure by scanning the QR code and a map showing the structure is seen online by the field technicians. Monitoring of the sewer system can be done using the sensors and ultimately the framework will ease the management of the water and sewer systems at the University of Zambia.