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Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect
This study investigated the feasibility of employing Internet of Things (IoT) technology as an alternative data collection method for studying the Urban Heat Island Effect (UHIE). Urban Heat Islands (UHIs) are localised and typically built-up areas, that experience significantly higher temperatures...
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| Format: | Thesis |
| Language: | English English |
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Department of Civil Engineering
2025
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| _version_ | 1867613268156088320 |
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| access_status_str | Open Access |
| author | Alexander, Samuel |
| author2 | Okedi, John |
| author_browse | Alexander, Samuel Okedi, John |
| author_facet | Okedi, John Alexander, Samuel |
| author_sort | Alexander, Samuel |
| collection | Thesis |
| description | This study investigated the feasibility of employing Internet of Things (IoT) technology as an alternative data collection method for studying the Urban Heat Island Effect (UHIE). Urban Heat Islands (UHIs) are localised and typically built-up areas, that experience significantly higher temperatures than the surrounding undeveloped areas. This temperature difference is primarily due to increased heat absorption and reduced cooling from construction materials like concrete and asphalt, as well as the removal of shaded green spaces. An IoT Wireless Sensor Network (WSN) comprising 14 sensor nodes were implemented using readily available, ‘off-the-shelf' products in South Africa, resulting in a competitive build cost of R1523.14 per node. The sensor nodes were deployed at the University of Cape Town (UCT) campus in both shaded green spaces and unshaded paved areas to monitor temperature and humidity differences. Over the course of 116 days, from 7 September to 31 December 2023, the IoT WSN provided real-time temperature and humidity data, yielding 84 148 transmissions with only a 0.1% transmission error rate. The data was stored and managed using the MongoDB database. The investigation found that urban shaded green spaces were consistently cooler than unshaded paved areas; peak temperatures on the warmest days of each month reduced by 4°C on 28 September and by 2°C on 19 October, 15 November, and 27 December. This study demonstrates that IoT technology is highly capable of monitoring UHIE whilst remaining economically feasible to deploy. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/42154 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:33:26.520Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Department of Civil Engineering |
| publisherStr | Department of Civil Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/42154 Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect Alexander, Samuel Okedi, John Engineering Internet of Things Urban Heat Island This study investigated the feasibility of employing Internet of Things (IoT) technology as an alternative data collection method for studying the Urban Heat Island Effect (UHIE). Urban Heat Islands (UHIs) are localised and typically built-up areas, that experience significantly higher temperatures than the surrounding undeveloped areas. This temperature difference is primarily due to increased heat absorption and reduced cooling from construction materials like concrete and asphalt, as well as the removal of shaded green spaces. An IoT Wireless Sensor Network (WSN) comprising 14 sensor nodes were implemented using readily available, ‘off-the-shelf' products in South Africa, resulting in a competitive build cost of R1523.14 per node. The sensor nodes were deployed at the University of Cape Town (UCT) campus in both shaded green spaces and unshaded paved areas to monitor temperature and humidity differences. Over the course of 116 days, from 7 September to 31 December 2023, the IoT WSN provided real-time temperature and humidity data, yielding 84 148 transmissions with only a 0.1% transmission error rate. The data was stored and managed using the MongoDB database. The investigation found that urban shaded green spaces were consistently cooler than unshaded paved areas; peak temperatures on the warmest days of each month reduced by 4°C on 28 September and by 2°C on 19 October, 15 November, and 27 December. This study demonstrates that IoT technology is highly capable of monitoring UHIE whilst remaining economically feasible to deploy. 2025-11-07T13:11:22Z 2025-11-07T13:11:22Z 2025 2025-11-07T11:56:33Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/42154 en eng application/pdf Department of Civil Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Engineering Internet of Things Urban Heat Island Alexander, Samuel Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| thesis_degree_str | Master's |
| title | Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| title_full | Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| title_fullStr | Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| title_full_unstemmed | Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| title_short | Internet of Things (IoT) application for hydrological measurements: measuring the Urban Heat Island effect |
| title_sort | internet of things iot application for hydrological measurements measuring the urban heat island effect |
| topic | Engineering Internet of Things Urban Heat Island |
| url | http://hdl.handle.net/11427/42154 |
| work_keys_str_mv | AT alexandersamuel internetofthingsiotapplicationforhydrologicalmeasurementsmeasuringtheurbanheatislandeffect |