Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure
Master Thesis
2018
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University of Cape Town
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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.
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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.