Risk Analysis and Early Warning of Food Safety Testing Based on Big Data

Abstract

With the development of the market economy, people’s income is increasing, and food health is becoming more and more important. Especially in recent years, the frequent occurrence of food safety accidents has exacerbated people’s attention to food safety. The inspection for food safety is mainly done by manpower, which is not only inefficient, but also has disadvantages such as long inspection cycle and one-sided inspection data. With the development of Internet information technology, cloud computing, the Internet of Things and other emerging technologies have entered the market. The above technologies are combined by big data, which can effectively improve the effectiveness of food safety monitoring, and not only can provide detailed data for regulatory authorities, but also provide comprehensive data services to manufacturers, consumers, and third-party supervisors. With the in-depth development and maturity of related technologies, this model will definitely become a major development trend in the future. This study explores the risk characteristics of food safety from the perspective of big data through the study of big data related theories, and creates a food safety risk analysis and early warning framework based on operational data sources and big data technology as the core, so as to provides theoretical basis for applied research of relevant field in the future.