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食品废弃物可持续管理与增值的智能方法。

Intelligent approaches for sustainable management and valorisation of food waste.

作者信息

Said Zafar, Sharma Prabhakar, Thi Bich Nhuong Quach, Bora Bhaskor J, Lichtfouse Eric, Khalid Haris M, Luque Rafael, Nguyen Xuan Phuong, Hoang Anh Tuan

机构信息

Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah, P. O. Box 27272, United Arab Emirates; U.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), Islamabad, Pakistan; Department of Industrial and Mechanical Engineering, Lebanese American University (LAU), Byblos, Lebanon.

Mechanical Engineering Department, Delhi Skill and Entrepreneurship University, Delhi-110089, India.

出版信息

Bioresour Technol. 2023 Jun;377:128952. doi: 10.1016/j.biortech.2023.128952. Epub 2023 Mar 24.

Abstract

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.

摘要

食物浪费(FW)是当今文明面临的一个严峻的环境和社会问题。因此,有必要找到一种高效且可持续的解决方案来管理食物浪费生物处理。诸如物联网(IoT)、人工智能(AI)和机器学习(ML)等新兴技术对于实现这一目标至关重要,其中利用人工智能和机器学习技术对物联网传感器的数据进行分析,实现实时决策和过程优化。这项工作描述了利用物联网、人工智能和机器学习等新策略在食物浪费增值方面的最新进展。可以得出结论,将物联网、人工智能和机器学习方法相结合,可以加强生物过程监测和管理,以便从食物浪费中生产增值产品和化学品,有助于提高环境可持续性和粮食安全。一般来说,结合智能技术并获得政府支持的综合策略可以减少食物浪费,并最大限度地发挥食物浪费在循环经济中的作用,迈向更可持续的未来。

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