Standard security protocols like SSL, TLS, IPSec etc. have high memory and processor consumption which makes all these security protocols unsuitable for resource constrained platforms such as Internet of Things (IoT). Blockchain (BC) finds its efficient application in IoT platform to preserve the five basic cryptographic primitives, such as confidentiality, authenticity, integrity, availability and non-repudiation. Conventional adoption of BC in IoT platform causes high energy consumption, delay and computational overhead which are not appropriate for various resource constrained IoT devices. This work proposes a machine learning (ML) based smart access control framework in a public and a private BC for a smart city application which makes it more efficient as compared to the existing IoT applications. The proposed IoT based smart city architecture adopts BC technology for preserving all the cryptographic security and privacy issues. Moreover, BC has very minimal overhead on IoT platform as well. This work investigates the existing threat models and critical access control issues which handle multiple permissions of various nodes and detects relevant inconsistencies to notify the corresponding nodes. Comparison in terms of all security issues with existing literature shows that the proposed architecture is competitively efficient in terms of security access control.