1. Intelligent approaches for sustainable management and valorisation of food waste.
- Author
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Said, Zafar, Sharma, Prabhakar, Thi Bich Nhuong, Quach, Bora, Bhaskor J, Lichtfouse, Eric, Khalid, Haris M., Luque, Rafael, Nguyen, Xuan Phuong, and Hoang, Anh Tuan
- Subjects
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FOOD waste , *ARTIFICIAL intelligence , *MACHINE learning , *BIOTECHNOLOGICAL process monitoring , *FOOD industrial waste , *TECHNOLOGICAL innovations - Abstract
[Display omitted] • Food waste (FW) contains potential nutrients and compounds for circular bioeconomy. • Efficient management and valorization of FW is the most sustainable method. • Artificial Intelligence (AI) application could help in optimizing FW supply chain. • Machine learning (ML) can predict quite exactly the quantity and composition of FW. • Combination of AI and ML could monitor and manage well FW-based bioprocess. Food waste (FW) is a severe environmental and social concern that today's civilization is facing. Therefore, it is necessary to have an efficient and sustainable solution for managing FW bioprocessing. Emerging technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) are critical to achieving this, in which IoT sensors' data is analyzed using AI and ML techniques, enabling real-time decision-making and process optimization. This work describes recent developments in valorizing FW using novel tactics such as the IoT, AI, and ML. It could be concluded that combining IoT, AI, and ML approaches could enhance bioprocess monitoring and management for generating value-added products and chemicals from FW, contributing to improving environmental sustainability and food security. Generally, a comprehensive strategy of applying intelligent techniques in conjunction with government backing can minimize FW and maximize the role of FW in the circular economy toward a more sustainable future. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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