Smart waste management paradigm in perspective of IoT and forecasting models

Anjum, Mohd; Shahab, Sana; Umar, M. Sarosh

doi:10.1504/ijewm.2022.120621

Cited by 9 publications

(3 citation statements)

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“…In the hardware subdimension, there is a need for sensor devices with functionality, namely to (1) detect the movement of people throwing rubbish into containers using motion sensors [51] and passive infrared (PIR) sensors [12]; (2) capturing images of trash using an image sensor [41]; (3) detecting the presence of waste using ultrasonic sensors [9,16,43] and infrared sensor [44]; (4) weighing the weight of the waste stored in the container [19,42] and to find out in more detail the type, weight and ratio of waste impurities [53] with using load-cell sensors [21,59]; (5) measuring the level of waste in the container using an ultrasonic sensor [21,22,37,49,59], overfill sensor [41], tracker sensor [43] infrared sensor [45]; (6) detecting the number of solid or liquid particles in the waste container using an ultrasonic sensor [12], (7) detecting wet or dry waste using a capacitive sensor based on water content [49], temperature and humidity sensors based on temperature and humidity levels [50], and moisture sensors and touch sensors [51]; (8) detecting the presence of metal waste using metallic sensors [49], induction sensors [46], and inductive proximity sensors [48,50]; (9) detecting the presence of plastic and wood waste using capacitance proximity sensors [48]; (10) storing and managing time in the waste recycling process, namely using a real-time clock (RTC) sensor [12].…”

Section: Information Technology Dimensionmentioning

confidence: 99%

“…A smart system for managing household waste can be a tool for achieving sustainability goals by reducing waste, increasing awareness and education, improving the economy, and developing information technology infrastructure. A smart system uses information technology components and data to address household waste problems [7]. Based on the Integrated Sustainable Waste Management (ISWM) framework, there are 11 waste management processes: generation, separation, collection, transfer, transport, treatment, disposal, reduction, reuse, recycling, and recovery [8].…”

Section: Introductionmentioning

confidence: 99%

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Framework of Smart and Integrated Household Waste Management System: A Systematic Literature Review Using PRISMA

Wirani,

Eitiveni,

Sucahyo

2024

Preprint

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Household waste is the primary source of environmental pollution due to global population growth compared to other sources of waste. This research aims to develop a smart and integrated household waste management system framework. The resulting framework not only focuses on dimensions of information technology but also links it with other integrated dimensions. This research attempts to conduct a Systematic Literature Review (SLR) using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) protocol to produce a smart and integrated household waste management framework. The framework's design is carried out by identifying the type of household waste management process based on the Integrated Sustainable Waste Management (ISWM) framework, dimensions that support smart household waste management, and stakeholders involved. The SLR results, namely dimensions and subdimensions that support the framework of a smart and integrated household waste management system, were validated by a resource person from the Indonesian Ministry of Environment and Forestry. The smart and integrated household waste management framework that has been developed in this research contains five main dimensions: Information Technology, Operational Infrastructure, Governance, Economy, and Social-culture. This framework also addresses stakeholder engagement to support smart household waste management systems and identifies waste management processes based on the ISWM framework. This research uses the PRISMA technique to provide a framework for smart and integrated household waste management systems in the initial stage. The proposed framework has been validated and can be further developed as a smart and integrated household waste management system. This research also contributes to the involvement of various dimensions identified to deal with waste problems.

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Section: Information Technology Dimensionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Framework of Smart and Integrated Household Waste Management System: A Systematic Literature Review Using PRISMA

Wirani,

Eitiveni,

Sucahyo

2024

Preprint

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“…The comparison of similarity distance outcomes shows that the earth mover's distance has the highest precision to measure the similarity of images and shows more efficiency than other distance methods. In [25,26], the author has reviewed and analyzed the information and communication technologies (ICTs) and their applications in various SWM tasks. This systematic review of ICTs concluded that ICTs have emerged as an integral part of the SWM architecture design.…”

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confidence: 99%

Application of Event Detection to Improve Waste Management Services in Developing Countries

Anjum

Shahab²,

Umar³

2022

Sustainability

Self Cite

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This study illustrates a proof-of-concept model to improve solid waste management (SWM) services by analyzing people’s behavior towards waste. A deep neural network model is implemented to detect and identify the specific types of events/activities in the proximity of the waste bin. This model consists of a three-dimensional convolutional neural network (3D CNN) and a long short-term memory (LSTM)-based recurrent neural network. The model was trained and tested over a handcrafted data set and achieved an average precision of 0.944–0.986. This precision is promising to support the implementation of the model on a large scale in the actual environment. The performance measures of all individual events indicate that the model successfully detected the individual events and has high precision for classifying them. The study also designed and built an experimental setup to record the data set, which comprises 3200 video files duration between 150–1200 s. Methodologically, the research is supported through a case study based on the recorded data set. In this case study, the frequencies of identified events/activities at a bin are plotted and thoroughly analyzed to determine people’s behavior toward waste. This frequency analysis is used to determine the locations where one of the following actions is required to improve the SWM service: (i) people need to be educated about the consequences of waste scattering; (ii) bin capacity or waste collection schedules are required to change; (iii) both actions are required simultaneously; (iv) none of the actions are needed.

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Design of a high-dimensional information decision model for smart supply chains using IoT data traceability in the post-public health crisis era

Gao,

2024

Electron Commer Res

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Smart waste management paradigm in perspective of IoT and forecasting models

Cited by 9 publications

References 0 publications

Framework of Smart and Integrated Household Waste Management System: A Systematic Literature Review Using PRISMA

Framework of Smart and Integrated Household Waste Management System: A Systematic Literature Review Using PRISMA

Application of Event Detection to Improve Waste Management Services in Developing Countries

Design of a high-dimensional information decision model for smart supply chains using IoT data traceability in the post-public health crisis era

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