A dynamic neural network model for predicting risk of Zika in real-time
Background In 2015 the Zika virus spread from Brazil throughout the Americas, posing an unprecedented challenge to the public health community. During the epidemic, international public health officials lacked reliable predictions of the outbreak’s expected geographic scale and prevalence of cases, and were therefore unable to plan and allocate surveillance resources in a timely and effective manner.
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Smart City: A Traffic Signal Control System for Reducing the Effects of Traffic Congestion in Urban Environments
This thesis addresses the detrimental effects of road traffic congestion in the Smart City environment. Urban congestion is a recognisable problem that affects much of the world’s population through delays and pollution although the delays are not an …
