TY - JOUR
T1 - Intelligent approaches for sustainable management and valorisation of food waste
AU - Said, Zafar
AU - Sharma, Prabhakar
AU - Thi Bich Nhuong, Quach
AU - Bora, Bhaskor J.
AU - Lichtfouse, Eric
AU - Khalid, Haris M.
AU - Luque, Rafael
AU - Nguyen, Xuan Phuong
AU - Hoang, Anh Tuan
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/6
Y1 - 2023/6
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Circular bioenergy
KW - Food waste valorisation
KW - Machine learning
KW - Sustainability
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UR - http://www.scopus.com/inward/citedby.url?scp=85151004042&partnerID=8YFLogxK
U2 - 10.1016/j.biortech.2023.128952
DO - 10.1016/j.biortech.2023.128952
M3 - Review article
C2 - 36965587
AN - SCOPUS:85151004042
SN - 0960-8524
VL - 377
JO - Bioresource Technology
JF - Bioresource Technology
M1 - 128952
ER -
