Priya Kedia

Title: Innovations in Food Quality Monitoring by Priya Kedia

Introduction

Priya Kedia is an accomplished inventor based in Pune, India. She has made significant contributions to the field of food quality monitoring through her innovative patent. Her work addresses critical challenges in real-time shelf-life prediction of food items, which is essential for ensuring food safety and reducing waste.

Latest Patents

Priya Kedia holds a patent for a "Method and system for real-time shelf-life prediction of food items." Traditional food quality monitoring systems often fail to track the variation of food quality in real-time scenarios. Existing machine learning approaches require dedicated data models for different classes of food items due to the differences in their characteristics. Additionally, generating such data models necessitates a substantial amount of annotated data per food item, which can be costly. Her patent introduces a system that generates a data model using a knowledge graph indicative of a hierarchical taxonomy for various categories of food items. This model contains metadata that represents similarities in the physio-chemical degradation patterns of different food classes. As a result, this data model serves as a generic framework for real-time shelf-life prediction across diverse food items.

Career Highlights

Priya Kedia is currently employed at Tata Consultancy Services Limited, where she applies her expertise in food quality monitoring and machine learning. Her innovative approach has the potential to revolutionize how food items are monitored and their shelf-life predicted, making significant strides in the food technology sector.

Collaborations

Priya has collaborated with notable colleagues, including Jayita Dutta and Parijat Dilip Deshpande, who contribute to her innovative projects and research endeavors.

Conclusion

Priya Kedia's work in real-time shelf-life prediction of food items exemplifies the intersection of technology and food safety. Her innovative patent not only addresses existing challenges but also paves the way for future advancements in food quality monitoring.