Implementation of Smart Contract-Based Audit System of Vehicles with Data Misdelivery

With the advancement of Internet of Things (IoT) technology, various types of IoT data are being generated. Among these are spatio-temporal data (STD), which are related to specific times and locations, and STD-RS, which uses vehicles to distribute these data. However, there is a risk of vehicles with location errors distributing data outside the designated area. Previous research proposed a system using a multi-layered blockchain to detect and audit such vehicles, which has been validated through simulations but not yet in real-world settings. This study implements this detection and audit mechanism using smart contracts and a multi-layered blockchain in a real-world setting. We evaluate performance on actual devices, using configurations that closely resemble the simulations. Our method involves storing STD hash values and area information in a smart contract to identify malfunctioning vehicles. To implement this, we utilized Ethereum for smart contract deployment, with Geth as the CUI Ethereum node, and the web3.js library in Node.js for writing to Ethereum blocks. Additionally, we employed Solidity to develop the smart contracts and GraphQL to specify the search range within the blockchain. The results show that as the scale of the data increases, the search time also increases, with real-world implementation reflecting similar characteristics to simulations. Furthermore, we confirmed that the rate of increase in search time per unit of data scale differs between simulations and real-world scenarios due to application variance. The implementation results show linearly increasing search time per data size, concluding equivalent scalability to the simulation.