Smart Trash Bin Model Design and Future for Smart City

Choi, Jaehyeon; Seo, Kyungryong

doi:10.3390/app11114810

Cited by 18 publications

(4 citation statements)

References 24 publications

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“…• Smart trash bin Smart trash bins have been developed with the help of the recent available digital technologies especially IoT and its associated cloud computing and data analytics. The main functions which are currently developed and incorporated in smart bin technologies are summarized in Figure 11.18 (Angin et al, 2018;Balamurugan et al, 2017;Huh et al, 2021;Kumar et al, 2017;Noiki et al, 2021;Sohail et al, 2019;Wahab et al, 2014). Three most notable features of smart bins are waste monitoring, communication and waste segregation (Soni & Kandasamy, 2018).…”

Section: • Processes and Service Layermentioning

confidence: 99%

Marine Plastics Abatement

2023

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Marine Plastics Abatement Volume 2 focusses on abatement strategies and up-to-date technological innovations against marine plastic pollution such as resource recovery, plastics-to-values, co-processing, dumpsite recovery, etc. With an understanding of technological solutions and proper management practices, this volume suggests ways to develop businesses from plastic wastes with several cases from developed and developing countries. Furthermore, business case studies are presented along with recent scientific information, and practical exercises together with discussions on future trends such as introduction of biodegradable, or decomposable plastics; product designs for recycling/upcycling; etc. ISBN: 9781789063431 (print) ISBN: 9781789063448 (eBook) ISBN: 9781789063448 (ePUB)

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Section: • Processes and Service Layermentioning

confidence: 99%

Marine Plastics Abatement

2023

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“…The technology and environment applied to waste management can be different, therefore it is necessary to choose a type of waste detection technology that can facilitate its implementation. The IoT-based sensor workflow shown in Figure 15 is modified from (Huh et al, 2021) and (Zohari and Zulkefle, 2020) including getting waste data, measuring weight, and determining the type of waste.…”

Section: Developed Wsn Architecturementioning

confidence: 99%

Integrated Waste Management System with IOT-Based Centralized Control towards a Smart Eco Campus-Telkom University

Permana

Raharjo

2023

IJEEP

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Telkom University is a private university in Indonesia that has implemented an eco-campus or green campus program. The Greenmetric Program is one part of Telkom University's strategic planning in realizing a campus that cares and has an environmental culture by managing the environment in a systematic and sustainable manner. One of the programs is to reduce waste production. Therefore, it is necessary to conduct research related to optimizing waste management by implementing Onsite Waste Treatment Technology-Integrated-Independent-Environmentally Friendly (TOSS-TMRL). TOSS-TMRL Management System with Centralized Control Based on the Internet of Things (IoT) Towards a Smart ECO Campus to be completed on the spot. This will reduce pollution, operational costs, and waste management investment and can even function as Living Labs for environmental-based courses. In addition, optimization is also one of the efforts to realize a smart eco campus towards the best-ranking Green Metric Telkom University. Wireless communication technology is very efficient, effective, and easy to use. One of the applications can be applied to determine the condition of environmental cleanliness in a campus area by integrating microcontroller technology and detection devices (sensors, QR codes, AR/imaging, and CCTV) with Wireless Sensor Networks (WSN) and IoT applications as tools to increase awareness of the importance of sorting waste so that the cleanliness of the campus area can be maintained. In this study, a system and network architecture design were carried out based on the number of sensor nodes, the number of recycle bins, the number of garbage transportation equipment, the number of buildings, the number of areas, and the ability of Data Transfer Nodes (DTN) to provide information to the server taken from the recycle bin of each room/building, business areas, SME facilities, canteens, and dormitories or local areas. With this system, it is hoped that there will be no accumulation of garbage and allow users/garbage managers to interact with the system through a web browser and android application.

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“…Not experimenting with better CNN architectures and the lack of sufficient training data are the evident drawbacks. Similarly, in the study of Huh et al (2021) , the incoming trash is classified into one of following categories of recyclable waste: paper, glass, plastic, vinyl and can. The process begins with the capture of an image of the trash and then label recognition; if the label is not recognized, it is fed into spectroscopic and image classification algorithms for identifying the class it belongs to.…”

Section: Waste Classificationmentioning

confidence: 99%

Technical solutions for waste classification and management: A mini-review

Shreya

Katyal

et al. 2022

Waste Manag Res

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The massive growth of population coupled with urbanization over the years has created a significant challenge of increase in waste generation. India has achieved massive developmental growth in economic and social areas but still lacks a proper waste management system. The lack of knowledge about segregation of waste into different categories and proper disposal techniques in a country like India with an accelerated population growth is a critical issue. Since trash has different disposal techniques, according to its type, segregating waste through an automated process at the point of collection will streamline the process and result in effective waste management and utilization. The mini-review article evaluates the recent literature on technologies used for municipal waste segregation and management, with the motive of providing critical information for advancement in current research. This article reviews the use of various convolutional neural network architectures for waste classification and describes in detail as to why image processing methods are preferred over sensors for segregation into respective categories. It is also important to have an efficient waste monitoring and management system for proper disposal. A comprehensive mini-review was undertaken to understand internet of things-based models proposing efficient waste handling, from the perspective of reduced costs, collection time and optimized routes. The proposed systems were compared and evaluated based on the sensors used monitoring, microcontrollers and communication protocols such as Long Range, Global System for Mobile Communication, Zigbee and Wi-Fi, which are employed for the secure and efficient data transmission.

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Smart Trash Bin Model Design and Future for Smart City

Cited by 18 publications

References 24 publications

Marine Plastics Abatement

Marine Plastics Abatement

Integrated Waste Management System with IOT-Based Centralized Control towards a Smart Eco Campus-Telkom University

Technical solutions for waste classification and management: A mini-review

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