An efficient waste management technique with IoT based smart garbage system

Karthik, M.; Sreevidya, L.; Devi, R. Nithya; Thangaraj, Marimuthu; hemalatha, Gaddam; Yamini, R

doi:10.1016/j.matpr.2021.07.179

Cited by 30 publications

(7 citation statements)

References 12 publications

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“…Dalam penelitian ini menggunakan mikrokontroler Raspberry Pi 3B+ dan menggunakan kamera untuk pemilahan. Penelitian [12] mengembangkan tempat sampah yang dapat mengetahui tingkat kepenuhan pada tempat sampah dengan menggunakan sensor ultrasonik dan diintegrasikan ke web server sehingga petugas akan mendapatkan notifikasi saat sampah sudah penuh. Penelitian [13] mengembangkan tempat sampah bergerak mengikuti jalur hitam, dan ketika berhenti, tutup tempat sampah akan terbuka dengan menggunakan servo SG90.…”

Section: Gambar 1 Capaian Kinerja Tempat Sampahunclassified

Rancang Bangun Alat Mobile Smart Trash Bin Menggunakan Raspberry Pi

Hermawan,

Kurniawan,

Hanafi

et al. 2023

JKT

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Standar hidup masyarakat semakin meningkat dengan adanya perkembangan ekonomi global, sehingga produksi sampah domestik menjadi semakin meningkat dari tahun ke tahun. Namun dalam pengolahan sampah masih terdapat masalah dimana masih tercampurnya sampah berbahaya sehingga dapat menyebabkan penyebaran covid saat ini. Saat ini tren mulai bergeser ke perangkat pintar yang menggunakan Internet of Things untuk mengatasi masalah umum seperti masalah pengolahan sampah. Dalam penelitian ini diusulkan sebuah mobile smart trash bin yang dapat mengurangi interaksi secara langsung karena memiliki fitur buka tutup otomatis, dapat memilah sampah menjadi berbahaya dan tidak berbahaya, dapat mengirimkan data berat sampah, dan dapat dikendalikan dari jarak jauh dengan dilengkapi livestream video. Sistem yang dikembangkan diuji dengan metode pengujian fungsionalitas, pengujian performa, dan pengujian konektifitas. Pengujian fungsionalitas memberikan hasil bahwa keseluruhan sistem dapat bekerja. Pengujian performa pada sensor ultrasonik memberikan hasil tingkat keakurasian sebesar 97,18%, servo motor MG995 berada di angka 100%, sensor berat memiliki tingkat keakurasian 98,65%, dan penggunaan baterai dalam keadaan bersiap dapat bekerja selama 13 Jam 3 Menit 40 Detik dan dalam keadaan bekerja dapat bekerja selama 1 Jam 56 Menit 42 Detik. Pengujian konektivitas dari rata-rata delay kontrol robot ketika diberikan perintah adalah 103,4ms, dan delay pada pengiriman data berat sampah adalah 112,8ms.

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Section: Gambar 1 Capaian Kinerja Tempat Sampahunclassified

Rancang Bangun Alat Mobile Smart Trash Bin Menggunakan Raspberry Pi

Hermawan,

Kurniawan,

Hanafi

et al. 2023

JKT

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“…PIC controller is a cost efficient, easy to use microcontroller that has an EEPROM chip to retain information. It can be used as the main component that collects data from the ultrasonic sensor about the level of trash in the bin and sends it to a web browser for visualization with the help of an ESP8266 module ( Karthik et al, 2021 ).…”

Section: Waste Monitoringmentioning

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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“…The United Nations highlights waste management as essential for public health and environmental protection [2]. Several studies [3]- [6] underscore the urgency of addressing pollution and its adverse impacts, emphasising the necessity for innovative waste disposal and efficient management strategies.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Trash Level Detection for Sustainable Urban Waste Management

Enache,

Banica,

Bogdan

2024

The Scientific Bulletin of Electrical Engineering Faculty

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This paper introduces an advanced trash bin fill ratio detection system, addressing the challenges of municipal solid waste management. Utilising the ESP32 CAM module, the system captures and transmits bin images via the ESP MESH protocol, enhancing waste management efficiency. The hardware relies on sustainable energy sources, including a photovoltaic cell and LiPo battery, ensuring continuous operation. On the software front, a client-server architecture is employed. The client-side captures images, while the server-side processes these images using a Python script and SQL database to determine bin fill levels. This innovative approach offers a scalable, cost-effective solution for improving urban waste collection and management.

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An efficient waste management technique with IoT based smart garbage system

Cited by 30 publications

References 12 publications

Rancang Bangun Alat Mobile Smart Trash Bin Menggunakan Raspberry Pi

Rancang Bangun Alat Mobile Smart Trash Bin Menggunakan Raspberry Pi

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

Intelligent Trash Level Detection for Sustainable Urban Waste Management

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