Data Visualization for Designing F2C IoT Agricultural System

Abstract

This paper presents a visual traceability system for the Farm-to-Customer (F2C) IoT agricultural model, aimed at improving product traceability and quality. The system integrates intelligent hardware such as sensors, RFID chips, and smart labels, and employs blockchain, big data, cloud computing, and AI technologies for comprehensive product traceability services. The system uses a data-driven approach, leveraging data mining and analysis to provide consumers with intuitive and personalized traceability information. Its visual design, encompassing product identification, traceability information display, and data monitoring interfaces, is key to its success, offering a seamless user experience. This innovative system significantly enhances product quality and safety management, promoting a safe consumption environment. Its success relies on the integration of multiple technologies and continuous design refinement. Applicable across various industries, it ensures product quality and safety, boosting consumer confidence. © 2023 SPIE.