Comparison of Machine Learning Approach for Waste Bottle Classification

Fadlil, Abdul; Umar, Rusydi; Sunardi, Sunardi; Nugroho, Arief Setyo

doi:10.28991/esj-2022-06-05-011

Cited by 14 publications

(12 citation statements)

References 31 publications

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“…Compared with the research results conducted on household subjects, students have about 8 times higher rates of laptop ownership. Specifically, the survey results in 120 households in Can Tho city with 507 people recorded only 60 computers in use, which is only 0.12 units/person [20]. Thereby, it can be seen that the university is the place where a large number of laptops are used, and students are an important contributor to the increase in the number of these devices.…”

Section: Current Status Of Owning a Laptopmentioning

confidence: 99%

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Assessment of E-Waste Management and Potential for Laptop Reuse and Recycling

2023

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Reusing and recycling laptops has many positive benefits, both environmentally and economically. Therefore, this study was conducted with the objectives of assessing (1) the current state of ownership, (2) the current state of use and disposal, and (3) quantifying the potential reuse and recycling of laptops for students at Can Tho University, Vietnam. Based on data collected by document review and face-to-face interviews with students, with a usage rate of 1 laptop per student, it is estimated that the whole of Can Tho University has 42,918 laptops in use. The actual use lifespan of the laptop is 5.28 years, lower than the expected lifespan of 6.8 years. The results of the correlation analysis show that the actual usage life does not have any correlation with the consumption behavior of students. In addition, the study estimates that 96.67% of laptops will be disposed of before 2031. In which, the potential for direct reuse is 2.33%, reuse with support is 88.33%, and recycling is 9.33%. The results show that universities have great potential to implement safe e-waste collection and treatment activities. Doi: 10.28991/CEJ-2023-09-06-013 Full Text: PDF

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Section: Current Status Of Owning a Laptopmentioning

confidence: 99%

“…In addition, only a few related studies have been carried out to estimate the generation of household e-waste in households such as mobile phones, personal computers, televisions, refrigerators, etc. [20][21][22]. The results of these studies show that laptops are not commonly used in households.…”

Section: Introductionmentioning

confidence: 99%

Assessment of E-Waste Management and Potential for Laptop Reuse and Recycling

2023

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“…For instance, Narayanswamy et al [11] explored the optimal multiclass waste classification methods, and compared three image algorithms for waste classification. Fadlil et al [12] studied two methods, namely Convolutional Neural Network and Support Vector Machine, by comparing the training process and the accuracy results of the classification. They found that Convolutional Neural Network is more accurate than Support Vector Machine.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Penalty on Residents’ Waste Separation Behavior: A Moderated Mediation Model

Hao¹,

Xu²

2023

Pol. J. Environ. Stud.

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To alleviate the plight of municipal solid waste management, penalties were implemented in China. However, it is unclear how penalty affects residents' waste separation behavior. This study aims to analyze the impact of penalty on residents' waste separation behavior and the role of personal norms and trust in authorities. A theoretical model of the impact of penalty on residents' waste separation behavior was established based on deterrence theory and normative activation model. Using online survey data from 628 respondents in Zhengzhou, China, an empirical analysis was performed by employing the moderated mediation model. The results showed that residents' perceived penalty certainty and penalty severity positively influenced their waste separation behavior through the mediation effect of personal norm. Penalty certainty had a direct impact on waste separation behavior, whereas penalty severity had no direct impact on waste separation behavior. Trust in authorities positively moderated the mediation effect of personal norm. The higher the trust in authorities, the stronger mediating effect of personal norm. Some recommendations were proposed to improve residents' waste separation behavior under the mandatory policy. This paper presents a new perspective and theoretical guidelines for the local government to improve residents' waste separation behaviors in China and offers useful insights into waste separation management for other countries.

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“…The former aims to locate all instances of transparent containers present in an image, usually involving both identifying the transparent containers and localizing the rectangular boundary surrounding each one. Nevertheless, in spite of vast applications in areas such as service robots [ 9 , 10 ], waste classification [ 11 , 12 ], security checks [ 13 , 14 ] and so on, it provides only very limited information, i.e., no more than presence and localization, about the detected transparent containers. The latter is intended to perceive or estimate the liquid (such as water, alcohol, and other beverages) inside transparent containers by predicting the height of the liquid levels or filled status within the containers.…”

Section: Introductionmentioning

confidence: 99%

Liquid Content Detection In Transparent Containers: A Benchmark

Yang

et al. 2023

Sensors

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Various substances that possess liquid states include drinking water, various types of fuel, pharmaceuticals, and chemicals, which are indispensable in our daily lives. There are numerous real-world applications for liquid content detection in transparent containers, for example, service robots, pouring robots, security checks, industrial observation systems, etc. However, the majority of the existing methods either concentrate on transparent container detection or liquid height estimation; the former provides very limited information for more advanced computer vision tasks, whereas the latter is too demanding to generalize to open-world applications. In this paper, we propose a dataset for detecting liquid content in transparent containers (LCDTC), which presents an innovative task involving transparent container detection and liquid content estimation. The primary objective of this task is to obtain more information beyond the location of the container by additionally providing certain liquid content information which is easy to achieve with computer vision methods in various open-world applications. This task has potential applications in service robots, waste classification, security checks, and so on. The presented LCDTC dataset comprises 5916 images that have been extensively annotated through axis-aligned bounding boxes. We develop two baseline detectors, termed LCD-YOLOF and LCD-YOLOX, for the proposed dataset, based on two identity-preserved human posture detectors, i.e., IPH-YOLOF and IPH-YOLOX. By releasing LCDTC, we intend to stimulate more future works into the detection of liquid content in transparent containers and bring more focus to this challenging task.

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Comparison of Machine Learning Approach for Waste Bottle Classification

Cited by 14 publications

References 31 publications

Assessment of E-Waste Management and Potential for Laptop Reuse and Recycling

Assessment of E-Waste Management and Potential for Laptop Reuse and Recycling

The Impact of Penalty on Residents’ Waste Separation Behavior: A Moderated Mediation Model

Liquid Content Detection In Transparent Containers: A Benchmark

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