| Title |
Intelligent approaches for sustainable management and valorisation of food waste |
| ID_Doc |
8013 |
| Authors |
Said, Z; Sharma, P; Nhuong, QTB; Lichtfouse, E; Khalid, HM; Luque, R; Nguyen, XP; Hoang, AT; Bora, BJ |
| Title |
Intelligent approaches for sustainable management and valorisation of food waste |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.biortech.2023.128952 |
| 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. |
| Author Keywords |
Artificial intelligence; Machine learning; Food waste valorisation; Circular bioenergy; Sustainability |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001053379700001 |
| WoS Category |
Agricultural Engineering; Biotechnology & Applied Microbiology; Energy & Fuels |
| Research Area |
Agriculture; Biotechnology & Applied Microbiology; Energy & Fuels |
| PDF |
https://hal.science/hal-04200679/document
|