Dynamic Involvement of Deep Learning and Big Data in Smart Cities

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.