Abstract
Deep learning is an extension of Artificial Intelligence (AI) or cognitive
learning that is used to optimize performance via the application of neural networks.
And, big data analytics includes managing a plethora of continuous streams of data
while obtaining valuable insights from them. Deep learning and Big Data analytics
have been implemented in various avenues to obtain real-time optimized results, like
biomedical applications, Computer Vision, and enhancing results for Internet of Things
applications. This study aims to provide a deep insight into the application,
performance, and values provided by Deep learning and Big-data analytics in the
various intricacies of smart cities, smart governance and workflows in the same.
Firstly, we provide applications or areas of smart cities that create Big-data, then
provide techniques and literature where Big-data analytics is used to handle the same.
Then, we present the different computing infrastructures used for IoT big data
analytics, which include cloud, fog, and edge computing. Finally, we provide insights
into various Deep learning modules that are successfully implemented in smart cities.