Fang Bingbing, Yu Jiacheng, Chen Zhonghao, Osman Ahmed I, Farghali Mohamed, Ihara Ikko, Hamza Essam H, Rooney David W, Yap Pow-Seng
Department of Civil Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, 215123 China.
School of Chemistry and Chemical Engineering, Queen's University Belfast, David Keir Building, Stranmillis Road, Belfast, BT9 5AG Northern Ireland UK.
Environ Chem Lett. 2023 May 9:1-31. doi: 10.1007/s10311-023-01604-3.
The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the application of artificial intelligence in waste-to-energy, smart bins, waste-sorting robots, waste generation models, waste monitoring and tracking, plastic pyrolysis, distinguishing fossil and modern materials, logistics, disposal, illegal dumping, resource recovery, smart cities, process efficiency, cost savings, and improving public health. Using artificial intelligence in waste logistics can reduce transportation distance by up to 36.8%, cost savings by up to 13.35%, and time savings by up to 28.22%. Artificial intelligence allows for identifying and sorting waste with an accuracy ranging from 72.8 to 99.95%. Artificial intelligence combined with chemical analysis improves waste pyrolysis, carbon emission estimation, and energy conversion. We also explain how efficiency can be increased and costs can be reduced by artificial intelligence in waste management systems for smart cities.
全球产生的垃圾量不断增加，引发了污染、废物管理和回收利用等问题，这就需要新的策略来改善垃圾生态系统，比如使用人工智能。在此，我们综述了人工智能在垃圾转化能源、智能垃圾桶、垃圾分类机器人、垃圾产生模型、垃圾监测与追踪、塑料热解、区分化石材料和现代材料、物流、处置、非法倾倒、资源回收、智慧城市、流程效率、成本节约以及改善公众健康等方面的应用。在垃圾物流中使用人工智能可将运输距离最多缩短36.8%，成本最多节约13.35%，时间最多节省28.22%。人工智能能够以72.8%至99.95%的准确率识别和分类垃圾。人工智能与化学分析相结合可改善垃圾热解、碳排放估算和能量转换。我们还解释了人工智能如何在智慧城市的垃圾管理系统中提高效率并降低成本。
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