Artificial intelligence of things and distributed technologies as enablers for intelligent mobility services in smart cities-A survey

• Deploys AIoT and DLT to create novel business models for improved data driven services in smart cities. • Provides understanding on the integration of AIoT and DLT in achieving intelligent mobility services in smart cities. • Bridges the gap between theory and practice by providing insights on the potential benefits of converging AIoT and DLT. • Grounded on the TOE framework this study presents the factors that impacts the convergence of AIoT and DLT in smart cities. • Present use cases on the applicability of AIoT and DLT to support intelligent mobility services in smart cities. The society is witnessing an accelerated large-scale adoption of technology with transformative effects on daily transport operations, with cities now depending on data driven mobility services. Disruptive technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and decentralized technologies for example Distributed Ledger Technologies (DLT) are being deployed in smart cities. However, AI is faced with data security and privacy issues due to its centralized mode of deployment. Conversely, DLT which employs a decentralized architecture can be converged with AI to provide a secure data sharing across various IoT thereby overcoming the existing setbacks faced in deploying AI in smart cities. Evidently, the convergence of AI and IoT as AIoT and DLT have great potential to create novel business models for improved data driven services such as intelligent mobility in smart cities. Although research on the convergence of AI, IoT and DLT exists, our understanding of its integration in achieving intelligent mobility services in smart cities remains fragmented as current research in this area remains scarce. This study bridges the gap between theory and practice by providing researchers and practitioners with insights on the potential benefits of converging AIoT and DLT. Grounded on the Technology Organization Environment (TOE) framework this study presents the technological, organizational, and environmental factors that impacts the convergence of AIoT and DLT in smart cities. Additionally, findings from this study present use cases on the applicability of AIoT and DLT to support intelligent mobility services in smart cities.