Advances in Soft Sensors for Smart Food Drying: Innovations, Challenges, and Industrial Perspectives

Abstract

Efficient real-time monitoring of directly unmeasurable variables, such as product moisture content and quality attributes, is crucial for optimizing process control in smart dryers. Advanced soft sensing techniques, which integrate analytical hardware with mathematical models, have enabled the development of intelligent drying systems. This review comprehensively evaluates applications of soft sensors for online monitoring in food drying, emphasizing performance characteristics such as accuracy, response time, and robustness for real-time control. Key obstacles, including data contamination, model selection, and adaptability, are examined, and emerging solutions like adaptive algorithms and hybrid modeling strategies are discussed. The review highlights how soft sensors contribute to improved drying efficiency, energy savings, and product quality retention. Broader implications for related industries are also considered.