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Electronics
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Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems
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Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 10185

Special Issue Editor

Prof. Dr. Soochang Park

E-Mail Website
Guest Editor
Department of Computer Engineering, Chungbuk National University, Chungbuk 28644, Korea
Interests: networking technologies; sensing and data analytics; mobile and internet of things based smart applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a new paradigm to bring active interaction between physical worlds and online cyber systems. A large number of connectable IoT devices have been deployed in areas of our everyday lives, e.g., smart homes, intelligent transportation, and smart factories, to sense ourselves and our surroundings. Online user-related data derived from social network service (SNS) platforms, where individuals and enterprises are connected, have raised awareness that such data acquisition through pervasive IoT devices could be fulfilled more precisely and comprehensively. Nowadays, big data analytics and artificial intelligence (AI) service technologies are being woven into cloud platforms for the online world. These mature AI environments allow AI-aided data analytics and intelligence generation to be readily adapted to a wide variety of smart applications for individuals and enterprises. Therefore, cyber-physical data composition via the IoT paradigm paves the way to understanding user demands appropriately matched to spatial and temporal situations.

However, such IoT nature is composed of mostly untethered devices that have a limited operation lifetime due to their finite power source. Namely, the IoT nature requires periodic battery replacement, which induces increased management cost and such a battery replacement process could be very tedious considering the massive amount of already deployed devices. This shortcoming has been typically amended through the use of energy-efficient communication or hardware architecture, but it is messy due to the huge scale of IoT infrastructures and even this cannot eliminate the problem at its source. For instance, one of the core uses of IoT infrastructures is empowering the cognition of surroundings. There are many fundamental applications, such as position-based marketing, proximity-based interaction, indoor localization, and distance estimation. Hence, the increasing management cost in dealing with the massive number of deployed devices inside a building would lead to reducing the scalability of smart application systems.

This Special Issue will demonstrate how novel interactive electronics technologies and intelligent communication solutions can be designed and exploited for achieving energy-efficient, low-cost but sustainable IoT to tie in with AI algorithms compounded in edge or cloud computing resources. The topics of interest include, but are not limited to:

  • Battery-free hardware and power-optimizing firmware design and modeling;
  • Energy-harvesting technologies for sustainable IoT applications;
  • AI-aided system infrastructure maintenance optimization;
  • AI-aided power management system design;
  • Energy-efficient communication design and modeling for multiscale data acquisition;
  • Adaptive and feasible design and modeling with off-the-shelf device utilization;
  • Infrastructure-less architecture design and modeling for intelligent services;
  • Edge-based AI utilization;
  • Edge–cloud interaction for optimized off-loading;
  • Mobile-assisted environmental sensing and crowdsourcing;
  • Mobile-assisted user activity sensing.

Prof. Dr. Soochang Park
Guest Editor

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. Electronics 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.

Published Papers (5 papers)

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Research

14 pages, 2481 KiB  
Article
AI-Aided Individual Emergency Detection System in Edge-Internet of Things Environments
by Taehun Yang, Sang-Hoon Lee and Soochang Park
Electronics 2021, 10(19), 2374; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10192374 - 28 Sep 2021
Cited by 4 | Viewed by 1951
Abstract
Recently, many disasters have occurred in indoor places. In order to rescue or detect victims within disaster scenes, vital information regarding their existence and location is needed. To provide such information, some studies simply employ indoor positioning systems to identify each mobile device [...] Read more.
Recently, many disasters have occurred in indoor places. In order to rescue or detect victims within disaster scenes, vital information regarding their existence and location is needed. To provide such information, some studies simply employ indoor positioning systems to identify each mobile device of victims. However, their schemes may be unreliable, since people sometimes drop their mobile devices or put them on a desk. In other words, their methods may find a mobile device, not a victim. To solve this problem, this paper proposes a novel individual monitoring system based on edge intelligence. The proposed system monitors coexisting states with a user and a smart mobile device through a user state detection mechanism, which could allow tracking through the monitoring of continuous user state switching. Then, a fine-grained localization scheme is employed to perceive the precise location of a user who is with a mobile device. Hence, the proposed system is developed as a proof-of-concept relying on off-the-shelf WiFi devices and reusing pervasive signals. The smart mobile devices of users interact with hierarchical edge computing resources to quickly and safely collect and manage sensing data of user behaviors with encryption by cipher-block chaining, and user behaviors are analyzed via the ensemble paradigm of three machine learning technologies. The proposed system shows 98.82% prevision for user activity recognition, and 96.5% accuracy for user localization accuracy is achieved. Full article
(This article belongs to the Special Issue Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems)
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14 pages, 2064 KiB  
Article
D-PARK: User-Centric Smart Parking System over BLE-Beacon Based Internet of Things
by Soochang Park
Electronics 2021, 10(5), 541; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10050541 - 25 Feb 2021
Cited by 8 | Viewed by 2462
Abstract
Our daily life services are quickly becoming smarter with intelligence and information through artificial intelligence (AI) and Big Data technologies. Parking services are one of the most frequently used in our daily life-cycle. This parking application could be classified into several features according [...] Read more.
Our daily life services are quickly becoming smarter with intelligence and information through artificial intelligence (AI) and Big Data technologies. Parking services are one of the most frequently used in our daily life-cycle. This parking application could be classified into several features according to demands and properties, such as parking capacity balancing on a city-level view, parking fee maximization for achieving the service provider demand, empty parking spot notification within a parking lot, etc. This paper concentrates on parking space detection and alert to users. Most smart services rely on smart mobile derives of users such as smartphones and smartwatches. The proposed novel mechanism for smart parking is based on a smart device to gather mobile sensing data such as users’ activity and position data. Acquired mobile data are analyzed via machine learning technologies to provide dedicated parking services per user. Based on real testbed setups on campus and the proof-of-concept implementation, the proposed localization can achieve accuracy of a parking spot scale (2m-second guess 95%); moreover, it shows a much lower service operation period of 6.8 times (34s) than the legacy approach (230s). Full article
(This article belongs to the Special Issue Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems)
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13 pages, 747 KiB  
Article
Large-Scale Object Monitoring in Internet-of-Things: Energy-Efficient Perspectives
by Yongbin Yim, Euisin Lee and Seungmin Oh
Electronics 2021, 10(4), 461; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10040461 - 13 Feb 2021
Cited by 1 | Viewed by 1427
Abstract
Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic [...] Read more.
Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed. Full article
(This article belongs to the Special Issue Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems)
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11 pages, 681 KiB  
Article
Mobile-Based Sensing Scheme to Minimize Battery Power Consumption for Urban Monitoring Systems
by Sang-Hoon Lee, Taehun Yang and Tae-Sung Kim
Electronics 2021, 10(2), 198; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10020198 - 16 Jan 2021
Cited by 2 | Viewed by 1596
Abstract
In urban monitoring systems, mobile sensing is imperative to acquire data from sensors and relay them to a cloud server. Mobile devices can be used anytime and anywhere, enabling communication with pervasive sensing in various conditions to obtain the data. Reliable data acquisition [...] Read more.
In urban monitoring systems, mobile sensing is imperative to acquire data from sensors and relay them to a cloud server. Mobile devices can be used anytime and anywhere, enabling communication with pervasive sensing in various conditions to obtain the data. Reliable data acquisition has been required in urban monitoring systems from the macroscale to the microscale. However, a broadcast method for the data acquisition process may lead to the increased battery power consumption of mobile devices. Managing the battery power consumption of mobile devices is essential for reliable data acquisition. In this paper, we propose an urban monitoring system with an optimization algorithm in which a cloud server broadcasts a communication request that includes battery power consumption and the data acquisition quantity of mobile devices. Game theoretic optimization is formulated with a decision process. We derive a best response and Nash equilibrium for mobile communication with sensors and a cloud server. Evaluation results demonstrate that the proposed system can guarantee a low battery power consumption, as well as acquire the desired data quantity. Full article
(This article belongs to the Special Issue Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems)
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14 pages, 3676 KiB  
Article
Integrated Management Strategy with Feasible Smartness over Heterogeneous IoT Environments
by Taehun Yang and Jinsoo Han
Electronics 2021, 10(2), 149; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10020149 - 12 Jan 2021
Cited by 2 | Viewed by 1829
Abstract
Recently, Internet of Things (IoT) applications have been increasingly deployed in smart domains, such as homes, buildings, and so on. A wide variety of smart devices and solutions bring improved lifestyles. However, current provider-oriented and individual application deployment leads to the separation of [...] Read more.
Recently, Internet of Things (IoT) applications have been increasingly deployed in smart domains, such as homes, buildings, and so on. A wide variety of smart devices and solutions bring improved lifestyles. However, current provider-oriented and individual application deployment leads to the separation of a smart domain into respective regions by providers and applications. Such heterogeneous environments hinder unified operation and the utilization of smart IoT applications. Therefore, this Article firstly addresses analyses on conventional smart domain technologies—smart home, smart building, etc.— and deployment in the real world with heterogeneous IoT technologies; then, a novel smart domain strategy for inter-cloud and inter-service operability and mobile-user-attached interactivity is proposed. Performance is compared in terms of user experience and service availability. Finally, numeric analyses are provided to prove the proposed strategy, and the proof-of-concept is presented to show feasibility and performances. Full article
(This article belongs to the Special Issue Green Internet-of-Thing Design and Modeling in AI and 5G Ecosystems)
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