# Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey
## 4 Synergy of Machine Learning, Blockchain, and IoT in Smart Cities
### Similar Aspects  
The technological integration of ML, blockchain, and IoT in smart cities is driven by several key similarities. First, all three technologies drive data-driven decision-making. ML analyzes vast datasets from IoT devices to optimize urban operations in real-time, while IoT continuously collects essential data across city services. Blockchain ensures the integrity and security of these data, enabling reliable decision-making processes. Another commonality is decentralization; ML benefits from decentralized data processing methods like FL, which reduces latency and enhances privacy. Similarly, IoT networks are inherently  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Topic** & **References** & **Description** \\ \hline Blockchain for & & Discusses the role of blockchain in enhancing security and ensuring data integrity within IoT systems in smart cities, focusing on aspects like cryptographic security and protection against cyber threats. & \\ Blockchain \& Cybersecurity & [47; 48; 49; 50; 51] & Focuses on how blockchain can be used to prevent cyber threats, such as DDoS attacks, data breaches, and unauthorized data modifications in IoT networks. & \\ \hline FL vs Blockchain for & [52; 53; 54; 55] & Compares FL to blockchain, focusing on how these technologies maintain data privacy and security in smart city environments, with blockchain ensuring data integrity through decentralized ledgers. & \\ \hline Blockchain \& FL & Discusses the challenges of integrating blockchain with FL in IoT systems, including issues like model poisoning and balancing privacy with security. & \\ \hline Blockchain & & Examines the integration of blockchain technology into smart city infrastructure, highlighting its use in public health monitoring, energy management, and urban governance. & \\ \hline Smart Contracts \& Blockchain & [64; 65; 66; 67; 68] & Explores the application of smart contracts within blockchain frameworks in smart cities, enabling automated processes like energy trading and enhancing transparency in urban management. & \\ \hline Blockchain & & Discusses challenges related to the scalability of blockchain networks in smart cities, and explores solutions like sharding and layer-two protocols to improve performance. & \\ \hline Consensus & & Evaluates different blockchain consensus mechanisms (e.g., proof of stake, sharding) and their impact on scalability, energy efficiency, and security in smart cities. & \\ \hline Blockchain \& Smart City & [76; 77; 78] & Provides insights into the practical applications of blockchain in smart cities, including challenges and opportunities for enhancing urban resilience and sustainability through blockchain technology. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Use of blockchain in smart cities.  
decentralized, with numerous devices operating autonomously. Blockchain complements these by providing a decentralized, secure framework that ensures no single point of control over data, aligning perfectly with the distributed nature of IoT and ML. In addition to data-driven decision-making and decentralization, scalability and adaptability are shared challenges and goals. ML models need to scale and adapt to growing data volumes and varying urban conditions, as IoT systems do, and must handle increasing devices and fluctuating network demands. Finally, although blockchain faces scalability challenges, particularly with the rise in IoT transactions, advanced solutions are being developed to enhance its scalability and performance.