Deep learning with blockchain to deploy secure multimodal smart city applications

Abstract

Smart cities are quickly becoming data-driven environments that are dependent on intelligent technologies to make cities efficient and their citizens happy. In this chapter, the author introduces a comprehensive concept of deep learning and blockchain that will be used to secure and improve multimodal smart city applications. It explores the heterogeneity issues of Internet of Multimedia Things (IoMT) data, such as security, privacy, and trust, and shows how deep learning can facilitate intelligent analysis by means of feature extraction, multimodal fusion, and real-time decision-making. Data integrity and transparency, as well as decentralized governance, are guaranteed by blockchain and secure access control and policy automation through smart contracts. It is also in this chapter that mechanisms of identity and trust management, secure data and model management, and privacy are discussed. Applied benefits are demonstrated by use cases in surveillance, transportation, and energy management, whereas challenges and future research discussions provide a basis for secure, resilient, and intelligent urban ecosystems.