RETRACTED: An Artificial Intelligence Based Predictive Approach for Smart Waste Management (Retracted Article)

被引:8
|
作者
Jude, A. Belin [1 ]
Singh, Deepmala [2 ]
Islam, Saiful [3 ]
Jameel, Mohammed [3 ]
Srivastava, Sandeep [4 ]
Prabha, B. [5 ]
Kshirsagar, Pravin R. [6 ]
机构
[1] Saranathan Coll Engn, Dept Civil Engn, Tiruchirappalli 620012, India
[2] Asia Pacific Univ, Acad Collaborat, Management Dept, LBEF Campus, Kathmandu, India
[3] King Khalid Univ, Coll Engn, Dept Civil Engn, Abha, Saudi Arabia
[4] GL BAJAJ Inst Technol & Management, MCA Dept, Greater Noida, India
[5] Koneru Lakshmaiah Educ Fdn, Dept Comp Sci & Engn, Vaddeswaram, India
[6] AVN Inst Engn & Technol, Dept Elect & Commun Engn, Hyderabad, India
关键词
Artificial intelligence; Smart waste management; Prediction segregation; Recycling; Convolution neural network; CONSTRUCTION; GENERATION;
D O I
10.1007/s11277-021-08803-7
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Waste management is one of the world's biggest challenges, either in the developed or the emerging economies. The biggest problem with pollution is that the compost heap is well flowed in public areas before the next sanitation period starts. Demographic expansion has caused the hygienic condition with regard to the waste management system to deteriorate considerably. Disposal of waste is a fundamental element in waste disposal. Gradually, the technologies of artificial intelligence (AI) gained popularity in offering different computer ways to solving intelligent waste problem. The management of misdefined issues, experiences and uncertainties and partial data were efficient for AI. Even though this work did conduct much study, very few evaluations demonstrated the influence of AI to resolve many difficulties of intelligent management of waste. Accurate evaluation of garbage amount and quality is critical to Smart waste management system development and design. However, it is a challenging task to anticipate the quantity of trash created, given the several characteristics and its variability. The framework utilized in this document is the convolution neural network, a suitable approach for estimating the waste mass.
引用
收藏
页码:15 / 16
页数:2
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