# AI-Driven Optimization of Blockchain Scalability, Security, and Privacy Protection
## 3 AI-Driven Blockchain Solutions
### AI-Driven Smart Contract
#### 3.2.3 AI-Driven Smart Contract Applications in Specific Domains  
Nowadays, blockchain smart contracts have been widely used. For an AI-driven implementation of smart contracts in specific applications, relevant scholars have done the following research: [PERSON] et al. [162] proposed a tamper-proof framework for storing and retrieving data. The framework leverages AI techniques to evaluate the mathematical computations of smart contracts, including overhead, execution time, average computational cost, standard deviation, throughput, and resource utilization. To address the issues of widespread fake restaurant reviews, unreliable rating authenticity, and low customer satisfaction with recommended dishes, [PERSON] et al. [163] introduced a peer-to-peer architecture based on blockchain smart contracts. Additionally, AI-powered predictive analytics were employed to enhance data analysis and improve recommendation accuracy. [PERSON] et al. [164] proposed a plastic-credit-driven incentive system composed of a recyclability index (RI) and plastic credits to promote plastic recycling and enhance the quality of recyclable plastics. This system relies on a market self-regulation mechanism to guide industry participants in self-regulating and optimizing plastic production and trading processes. [PERSON] et al. [165] proposed a consortium blockchain and smart-contract-based framework for tracking and tracing agricultural supply chain workflows. This approach enhances traceability and data sharing while mitigating information silos among enterprises, reducing the reliance on centralized institutions. Moreover, it improves the integrity, reliability, and security of transaction records. [PERSON] et al. [166] explored the potential of leveraging smart contracts in Byzantine Fault Tolerant (BFT) blockchain platforms. Specifically, they examined the BFT blockchain platforms Tendermint and Hyperledger Besu and applied them to a decentralized e-prescription management case study to evaluate their effectiveness and feasibility. [PERSON] et al. [167] investigated the design of a blockchain-based resource-sharing collaborative framework, leveraging smart contracts to facilitate decentralized resource allocation. This framework is particularly well suited for broader networks or ecosystems beyond conventional supply chains, where established collaboration mechanisms and hierarchical structures exist to enhance resource management transparency and data authenticity. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Author** & **Core Innovation** & **Algorithm** &
\begin{tabular}{c} **Performance** \\ **Comparison** \\ \end{tabular} & **Advantages** & **Limitations** \\ \hline [PERSON] et al. [157] & Smart contract broker for reusability & Broker mechanism & Improved reuse flexibility & Enhances management \\ \hline [PERSON] et al. [158] & Smart contract meta-modeling (UML) & UML-based modeling & Standardized modeling framework & Aids automation & Needs further extension \\ \hline [PERSON] et al. [159] & Smart contract recommender system & OpenZeppelin + ML & Reduced development time & Supports EVM contracts & Relies on OpenZeppelin ecosystem \\ \hline [PERSON] et al. [160] & AI-assisted contract annotation generation & Code annotation + AI & BLEU score +27\% & High automation & Limited to specific domains \\ \hline [PERSON] et al. [161] & AI-assisted word segmentation for contract generation & AI-based segmentation & Multi-language support & Compatible & Requires NLP capabilities \\ \hline \hline \end{tabular}
\end{table} 
Table 20: Comparison of smart contract optimization and generation research. As shown in Table 21, the research on smart contract applications in specific domains such as smart cities, food supply chains, agriculture, and healthcare has primarily focused on leveraging their capabilities in data management, trust mechanisms, and traceability.