Data Analysis System Based on REST Architecture for In-Pipe Inspection

Abstract

Abstract To solve the problems of high maintenance cost, low reusability and poor scalability of in-pipe inspection data analysis system, an in-pipe inspection data analysis system based on REST (Representational State Transfer) architecture is designed and implemented. A multilayer service-oriented architecture based on REST is designed, which decouples the functions of client, middleware, server and data storage to improve the maintainability of the software. REST APIs (Application Program Interfaces) based on HTTP (Hypertext Transfer Protocol) are designed, which encapsulate the core functions such as data analysis, signal processing, automatic identification and quantization into language and platform independent services to meet the needs of multiuser, cross platform and online data analysis. An adaptation method of in-line inspection tool based on metadata is designed, which abstracts the in-line inspection tool into a separate metadata file and decouples it from the client and server programs to improve the scalability of the software. Practice has proved the architecture can improve the maintainability, reusability and scalability of the software, and provide a basis for constructing online in-pipe inspection data analysis service based cloud.