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Networked Intelligent Systems for a Sustainable Future

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 28859

Special Issue Editors

School of Engineering and Technology, College of Information and Communication Technology, Central Queensland University, Melbourne, VIC-3000, Australia
Interests: security of networked systems; networked ubiquitous devices; distributed systems; smart farming; smart sprinkler system for parks; smart city for sustainable environment; renewable forecasting

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Guest Editor
School of Cyber Engineering, Xidian University, Xi’an 710071, China
Interests: resource allocation and system design for edge computing; vehicular networks; blockchain

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Guest Editor

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Guest Editor
School of Information Technology, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC 3220, Australia
Interests: 5G mobile communication for intellegent applications; artificial intellegence for data hungry smart application; cloud IoT applications; networked unmanned aerial vehicles for fault detection
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Guest Editor
School of Information Technology, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, Victoria, VIC 3220, Australia
Interests: Internet of Things; cyber security; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The future sustainability of the world depends on the development of technologies to address issues that may threaten stability. Due to recent advancements in Internet of Things (IoT) technologies, artificial intelligence, fog, and cloud computing, we have a great opportunity to prepare ourselves for a smarter world that can better handle upcoming challenges. IoT-enabling technologies such as sensors, actuators, controllers, and gateways can efficiently network among themselves to read, store, and process contextual information which is crucial for smart citizens and smart infrastructure to prepare a smarter world to adapt to upcoming and unforeseen challenges. Fog computing and blockchain technologies reduce dependency on a centralized backhaul system for a sustainable smarter echo system. Advancements in communication technologies, such as 5G, NBIoT, and LPWAN, and distributed computing, such as cloud computing, make it possible to create seamless connectivity and computing for smarter decisions based on contextual information. Faster and efficient artificial intelligent algorithms are developed to process big data collected in edge, in transit, and in central storage points for smarter decisions to create smart rural and urban developments for smarter sustainable movement to protect our future.

This Special Issue will focus on networked and intelligent technologies that are influencing smarter developments towards a long-term sustainable world. Existing work has mainly focused on the development of better technologies and techniques in specific silos but widely missed the opportunity to integrate developments from multiple silos to address issues that are complex but critical to address for balanced ecosystems that can handle unforeseen challenges. This Special Issue encourages the submission of high-quality research papers on interdisciplinary research towards smarter technologies, system, techniques, and hypotheses towards a sustainable future. The main topics of this SPECIAL ISSUE include but are not limited to the following:

  • IoT for sustainable critical infrastructure;
  • Intelligent and adaptive computing for sustainable energy, water, and transportation networks;
  • Renewable energy for sustainable buildings and grids;
  • Intelligent network analysis toward a sustainable world;
  • Blockchain for decentralized systems for sustainable application, system and infrastructure;
  • Secure communication protocols to protect critical infrastructure;
  • Smart governance;
  • Secure and sustainable smart cities;
  • Big data vs. sustainable development;
  • Intelligent, smart and distributed systems for remote sustainability;
  • Intelligent system to handle health crisis;
  • Teaching and learning innovation to complement networked intelligent systems.

Dr. Biplob Ray
Prof. Dr. Tom Hao Luan
Prof. Dr. Jemal H. Abawajy
Dr. Morshed U. Chowdhury
Dr. Adnan Anwar
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. Sustainability 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 2400 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

  • Sustainable computing
  • Sustainable infrastructures
  • Blockchain
  • Smart infrastructure
  • Smart systems
  • Digital twin
  • Big data
  • Smart health
  • Smart education

Published Papers (4 papers)

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Research

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18 pages, 5137 KiB  
Article
Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond
by Amlan Haque, Nahina Islam, Nahidul Hoque Samrat, Shuvashis Dey and Biplob Ray
Sustainability 2021, 13(8), 4511; https://doi.org/10.3390/su13084511 - 19 Apr 2021
Cited by 18 | Viewed by 6264
Abstract
Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending [...] Read more.
Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending the role of responsible leadership, this paper proposes an AI and IoT based smart farming system in Bangladesh. With a comprehensive literature review, this paper counsels the need to go beyond the simple application of traditional farming and irrigation practices and recommends implementing smart farming enabling responsible leadership to uphold sustainable agriculture. It contributes to the current literature of smart farming in several ways. First, this paper helps to understand the prospect and challenges of both AI and IoT and the requirement of smart farming in a nonwestern context. Second, it clarifies the interventions of responsible leadership into Bangladesh’s agriculture sector and justifies the demand for sustainable smart farming. Third, this paper is a step forward to explore future empirical studies for the effective and efficient use of AI and IoT to adopt smart farming. Finally, this paper will help policymakers to take responsible initiatives to plan and apply smart farming in a developing economy like Bangladesh. Full article
(This article belongs to the Special Issue Networked Intelligent Systems for a Sustainable Future)
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25 pages, 7366 KiB  
Article
A Secured Privacy-Preserving Multi-Level Blockchain Framework for Cluster Based VANET
by A. F. M. Suaib Akhter, Mohiuddin Ahmed, A. F. M. Shahen Shah, Adnan Anwar and Ahmet Zengin
Sustainability 2021, 13(1), 400; https://doi.org/10.3390/su13010400 - 4 Jan 2021
Cited by 39 | Viewed by 4797
Abstract
Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The [...] Read more.
Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The paper thoroughly explains the formation of the authentication centers, vehicles registration, and key generation processes. In the proposed architecture, a global authentication center (GAC) is responsible for storing all vehicle information, while Local Authentication Center (LAC) maintains a blockchain to enable quick handover between internal clusters of vehicle. We also propose a modified control packet format of IEEE 802.11 standards to remove the shortcomings of the traditional MAC protocols. Moreover, cluster formation, membership and cluster-head selection, and merging and leaving processes are implemented while considering the safety and non-safety message transmission to increase the performance. All blockchain communication is performed using high speed 5G internet while encrypted information is transmitted while using the RSA-1024 digital signature algorithm for improved security, integrity, and confidentiality. Our proof-of-concept implements the authentication schema while considering multiple virtual machines. With detailed experiments, we show that the proposed method is more efficient in terms of time and storage when compared to the existing methods. Besides, numerical analysis shows that the proposed transmission protocols outperform traditional MAC and benchmark methods in terms of throughput, delay, and packet dropping rate. Full article
(This article belongs to the Special Issue Networked Intelligent Systems for a Sustainable Future)
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17 pages, 374 KiB  
Article
Robustness Evaluations of Sustainable Machine Learning Models against Data Poisoning Attacks in the Internet of Things
by Corey Dunn, Nour Moustafa and Benjamin Turnbull
Sustainability 2020, 12(16), 6434; https://doi.org/10.3390/su12166434 - 10 Aug 2020
Cited by 38 | Viewed by 5233
Abstract
With the increasing popularity of the Internet of Things (IoT) platforms, the cyber security of these platforms is a highly active area of research. One key technology underpinning smart IoT systems is machine learning, which classifies and predicts events from large-scale data in [...] Read more.
With the increasing popularity of the Internet of Things (IoT) platforms, the cyber security of these platforms is a highly active area of research. One key technology underpinning smart IoT systems is machine learning, which classifies and predicts events from large-scale data in IoT networks. Machine learning is susceptible to cyber attacks, particularly data poisoning attacks that inject false data when training machine learning models. Data poisoning attacks degrade the performances of machine learning models. It is an ongoing research challenge to develop trustworthy machine learning models resilient and sustainable against data poisoning attacks in IoT networks. We studied the effects of data poisoning attacks on machine learning models, including the gradient boosting machine, random forest, naive Bayes, and feed-forward deep learning, to determine the levels to which the models should be trusted and said to be reliable in real-world IoT settings. In the training phase, a label modification function is developed to manipulate legitimate input classes. The function is employed at data poisoning rates of 5%, 10%, 20%, and 30% that allow the comparison of the poisoned models and display their performance degradations. The machine learning models have been evaluated using the ToN_IoT and UNSW NB-15 datasets, as they include a wide variety of recent legitimate and attack vectors. The experimental results revealed that the models’ performances will be degraded, in terms of accuracy and detection rates, if the number of the trained normal observations is not significantly larger than the poisoned data. At the rate of data poisoning of 30% or greater on input data, machine learning performances are significantly degraded. Full article
(This article belongs to the Special Issue Networked Intelligent Systems for a Sustainable Future)
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Review

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20 pages, 1865 KiB  
Review
A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming
by Nahina Islam, Md Mamunur Rashid, Faezeh Pasandideh, Biplob Ray, Steven Moore and Rajan Kadel
Sustainability 2021, 13(4), 1821; https://doi.org/10.3390/su13041821 - 8 Feb 2021
Cited by 123 | Viewed by 11133
Abstract
To reach the goal of sustainable agriculture, smart farming is taking advantage of the Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms are designed to be run by interconnected devices and vehicles. Some enormous potentials can be achieved [...] Read more.
To reach the goal of sustainable agriculture, smart farming is taking advantage of the Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms are designed to be run by interconnected devices and vehicles. Some enormous potentials can be achieved by the integration of different IoT technologies to achieve automated operations with minimum supervision. This paper outlines some major applications of IoT and UAV in smart farming, explores the communication technologies, network functionalities and connectivity requirements for Smart farming. The connectivity limitations of smart agriculture and it’s solutions are analysed with two case studies. In case study-1, we propose and evaluate meshed Long Range Wide Area Network (LoRaWAN) gateways to address connectivity limitations of Smart Farming. While in case study-2, we explore satellite communication systems to provide connectivity to smart farms in remote areas of Australia. Finally, we conclude the paper by identifying future research challenges on this topic and outlining directions to address those challenges. Full article
(This article belongs to the Special Issue Networked Intelligent Systems for a Sustainable Future)
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