Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure
| dc.contributor.advisor | Winberg, Simon | |
| dc.contributor.author | Singh, Subha | |
| dc.date.accessioned | 2019-02-11T13:27:32Z | |
| dc.date.available | 2019-02-11T13:27:32Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2019-02-11T10:38:47Z | |
| dc.description.abstract | The World Health Organization estimates around 3.7 million premature deaths world-wide were due to ambient air pollution in 2012, 88% of which occurred in low to middle income countries such as South Africa. This project focuses on the development of an event-driven real-time air quality index application for the City of Cape Town. Event streams are being more commonly adopted in data centric applications that aim to produce trend analyses and prediction models. Event-driven systems store immutable raw event data, providing both a history of what has happened in the database, and the current state, thereby assisting with debugging and providing audit trail support. In addition to increasing public accessibility to the city's air quality information, the application has been designed for scalability, extensibility and data analysis through the incorporation of the Command Query Responsibility Segregation, Event Sourcing and Model-View-Controller architectural patterns. The design of the application itself serves as a basic reusable template for any new applications that may require the scalability, extensibility and is inherently data-centric nature as is found in this implementation. By taking advantage of the city's existing air quality monitoring sensor network, the real-time application has the capability to highlight problematic areas within the City of Cape Town with regard to high pollution levels, create greater public awareness, and lays the foundation for the future development of predictive air quality models and pollution forecasts. | |
| dc.identifier.apacitation | Singh, S. (2018). <i>Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure</i>. (). University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/29477 | en_ZA |
| dc.identifier.chicagocitation | Singh, Subha. <i>"Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure."</i> ., University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering, 2018. http://hdl.handle.net/11427/29477 | en_ZA |
| dc.identifier.citation | Singh, S. 2018. Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Singh, Subha AB - The World Health Organization estimates around 3.7 million premature deaths world-wide were due to ambient air pollution in 2012, 88% of which occurred in low to middle income countries such as South Africa. This project focuses on the development of an event-driven real-time air quality index application for the City of Cape Town. Event streams are being more commonly adopted in data centric applications that aim to produce trend analyses and prediction models. Event-driven systems store immutable raw event data, providing both a history of what has happened in the database, and the current state, thereby assisting with debugging and providing audit trail support. In addition to increasing public accessibility to the city's air quality information, the application has been designed for scalability, extensibility and data analysis through the incorporation of the Command Query Responsibility Segregation, Event Sourcing and Model-View-Controller architectural patterns. The design of the application itself serves as a basic reusable template for any new applications that may require the scalability, extensibility and is inherently data-centric nature as is found in this implementation. By taking advantage of the city's existing air quality monitoring sensor network, the real-time application has the capability to highlight problematic areas within the City of Cape Town with regard to high pollution levels, create greater public awareness, and lays the foundation for the future development of predictive air quality models and pollution forecasts. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure TI - Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure UR - http://hdl.handle.net/11427/29477 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/29477 | |
| dc.identifier.vancouvercitation | Singh S. Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure. []. University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29477 | en_ZA |
| dc.language.iso | eng | |
| dc.publisher.department | Department of Electrical Engineering | |
| dc.publisher.faculty | Faculty of Engineering and the Built Environment | |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Electrical Engineering | |
| dc.title | Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc |