IoT-Enabled Waste Management in Smart Cities

A special issue of Smart Cities (ISSN 2624-6511). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 16926

Special Issue Editors


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Guest Editor
DigiT.DSS.Lab, Department of Business Administration, University of West Attica, Athens, 122 23, Greece
Department of Infocommunication Technologies, ITMO University, St. Petersurg, 197101, Russia
Interests: Internet of Things (IoT); artificial intelligence; robotics; waste management; context-aware systems; Smart Cities

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Guest Editor
School of Engineering Technology, Purdue University, West Lafayette, IN-47907, USA
Department of ECE, Vignan’s Foundation for Sciecne, Technology and Research, 522213, India
Interests: IoT; sensor networks; waste management; remote monitoring; Smart Cities

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Guest Editor
School of Information Technology, Deakin University, Burwood, VIC 3125, Australia
Interests: IoT; context-awareness; smart cities; waste management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, 97187, Sweden
Interests: IoT; IoT security; wireless access networks; Smart Cities

Special Issue Information

Dear Colleagues,

The current Special Issue covers research advances in IoT-enabled waste management in Smart Cities. Context-awareness is a service as well as an enabling technology for waste management in Smart Cities. Predictive analytics are based on machine learning and pervasive data science modeling for efficient waste disposal. Research in artificial intelligence, remote monitoring, autonomous systems and robotics is used for effective waste collection. Methods and algorithms combine sensors, sensor networks, wireless access networks, actuators, and IoT platforms. IoT security technologies are used to provide a secure environment for further waste processing. Inference models assist stakeholders and third parties for efficient dynamic scheduling and routing to support waste disposal and further recycling of organic waste. Sustainable waste management solutions are a prerequisite for a green ecosystem within Smart Cities. Research on integrated systems for waste management that adopt one or more of the above described research areas will be accepted to this Special Issue. We invite original research papers, review articles, and short communications. Topics of interest include, but are not limited to, the following research areas:

  • IoT sensors, sensor networks and actuators for waste management;
  • Sensor networks, context-awareness, wireless access networks and IoT security;
  • Pervasive data architecture for decision making;
  • Machine learning and inference models;
  • Artificial intelligence and multi agent modeling;
  • Reinforcement learning;
  • Robotics for waste collection and further processing;
  • Remote monitoring and autonomous systems;
  • Waste management as a service;
  • Context-aware systems for waste management
  • Sustainable solutions for Smart Cities;
  • Green and secure ecosystems for Smart Cities.

Dr. Theodoros Anagnostopoulos
Dr. S.R. Jino Ramson
Prof. Arkady Zaslavsky
Prof. Christer Åhlund
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Smart Cities is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart Cities;
  • waste management;
  • IoT;
  • wireless sensor networks;
  • IoT security;
  • pervasive data architecture;
  • decision making;
  • machine learning;
  • artificial intelligence;
  • reinforcement learning;
  • robotics;
  • autonomous systems;
  • remote monitoring;
  • context-aware inference models;
  • sustainable solution;
  • green and secure ecosystem

Published Papers (1 paper)

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14 pages, 2615 KiB  
Article
IoT-Enabled Solid Waste Management in Smart Cities
by S. Vishnu, S. R. Jino Ramson, Samson Senith, Theodoros Anagnostopoulos, Adnan M. Abu-Mahfouz, Xiaozhe Fan, S. Srinivasan and A. Alfred Kirubaraj
Smart Cities 2021, 4(3), 1004-1017; https://doi.org/10.3390/smartcities4030053 - 14 Jul 2021
Cited by 59 | Viewed by 15729
Abstract
The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact [...] Read more.
The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society’s health and the environment. The traditional waste management process begins with waste created by city residents and disposed of in garbage bins at the source. Municipal department trucks collect garbage and move it to recycling centers on a fixed schedule. Municipalities and waste management companies fail to keep up with outdoor containers, making it impossible to determine when to clean them or when they are full. This work proposes an IoT-enabled solid waste management system for smart cities to overcome the limitations of the traditional waste management systems. The proposed architecture consists of two types of end sensor nodes: PBLMU (Public Bin Level Monitoring Unit) and HBLMU (Home Bin Level Monitoring Unit), which are used to track bins in public and residential areas, respectively. The PBLMUs and HBLMUs measure the unfilled level of the trash bin and its location data, process it, and transmit it to a central monitoring station for storage and analysis. An intelligent Graphical User Interface (GUI) enables the waste collection authority to view and evaluate the unfilled status of each trash bin. To validate the proposed system architecture, the following significant experiments were conducted: (a) Eight trash bins were equipped with PBLMUs and connected to a LoRaWAN network and another eight trash bins were equipped with HBLMUs and connected to a Wi-Fi network. The trash bins were filled with wastes at different levels and the corresponding unfilled levels of every trash bin were monitored through the intelligent GUI. (b) An experimental setup was arranged to measure the sleep current and active current contributions of a PBLMU to estimate its average current consumption. (c) The life expectancy of a PBLMU was estimated as approximately 70 days under hypothetical conditions. Full article
(This article belongs to the Special Issue IoT-Enabled Waste Management in Smart Cities)
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