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Smart, Autonomous and Evolved Technologies in Internet of Things
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Smart, Autonomous and Evolved Technologies in Internet of Things

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 9447

Special Issue Editor

Dr. Tuan Nguyen Gia

E-Mail Website
Guest Editor
Silo AI, Fredrikinkatu 57 C, 00100 Helsinki, Finland
Interests: edge/fog computing; Blockchain; drones; e-health, co-robot; autonomous vehicles; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things can be defined as a virtual platform where virtual and physical objects are interconnected and communicate with each other. In the last decade, IoT, consisting of advanced technologies from sensing, communicating, and big data to cloud computing, has been ubiquitously used in many areas and applications such as smart homes, health monitoring, and smart grids. IoT helps to significantly improve quality of service and thus reduce costs, increase productivity, and improve real-time reaction time in unexpected situations. However, IoT-based systems still have challenges. For instance, many IoT systems are not smart enough to deal with abnormal situations—e.g., when a connection between a gateway and cloud servers is intermittent, quality of service is significantly reduced. Additionally, when a large volume of data is collected and transmitted over a network, bandwidth may be overloaded, causing delays in transmission. In another example, when one of the components of an IoT system (e.g., sensor node or gateway) fails, the service can be interrupted. Therefore, there is a need for evolved and smart methods, architectures, systems or technologies that can help to overcome these challenges. This Special Issue addresses all the essential aspects that are required to make this happen. Authors are invited to submit high-quality papers on (but not limited to) the following topics:

  • New paradigms, concepts, and architectures;
  • Smart sensor networks and smart computing;
  • Fog and Edge computing in IoT;
  • Middleware, architectures, and protocols for smart/autonomous IoT systems;
  • Smart sensors for IoT monitoring systems;
  • Smart computational offloading methods/decisions in IoT systems;
  • Advanced task migration in future IoT systems;
  • Artificial intelligence at the edge of the network;
  • Smart and autonomous IoT monitoring and controlling systems;
  • Advanced decision making methods at Edge/Fog computing;
  • Smart resource allocation methods in IoT systems;
  • Date processing and data fusion for smart/autonomous IoT systems;
  • Big data, machine learning, AI, and analytics for IoT systems;
  • Application, prototypes, and testbed for smart/autonomous IoT systems;
  • Smart methods for improving fault tolerance and reliability in fog computing and IoT;
  • Experiences from real-world experiments and deployments of smart/autonomous IoT systems;
  • Performance analysis and optimization of smart/autonomous IoT systems;
  • Security and privacy issues in smart/autonomous IoT systems;
  • 5G for smart/autonomous IoT systems;
  • LPWAN for smart/autonomous IoT systems (Sigfox, LoRa, NB-FI, etc.).

Dr. Tuan Nguyen Gia
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. Sensors 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 2600 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

14 pages, 3107 KiB  
Article
Evaluation of Functionality of Warning System in Smart Protective Clothing for Firefighters
by Anna Dąbrowska, Grażyna Bartkowiak and Rafał Kotas
Sensors 2021, 21(5), 1767; https://doi.org/10.3390/s21051767 - 4 Mar 2021
Cited by 10 | Viewed by 3585
Abstract
Recent achievements in the field of miniaturization of electronics have led to a significant interest in its application into the protective clothing for firefighters in order to improve their safety and health. However, up to now there are not any requirements and standardized [...] Read more.
Recent achievements in the field of miniaturization of electronics have led to a significant interest in its application into the protective clothing for firefighters in order to improve their safety and health. However, up to now there are not any requirements and standardized test methods enabling confirmation of safety of use and functionality of these systems in work environment. In the paper, an importance of evaluation of such smart wearable system in predicted utility conditions is highlighted. Three variants of the specially developed personal warning systems (PWSs) for integration with either health status or environmental sensors to be used in smart protective clothing for firefighters are presented, i.e., with LCD display, LED diodes and vibrating element. For the purpose of evaluation a new testing methodology was developed. The PWSs were evaluated on a basis of perception of warning signals by firefighters in simulated utility conditions including temperature, light, noise, fog and performed activities. In the case of marching, even 75% of signals generated by PWS with LCD display were not received. Physical activity did not influence on functionality of PWS with vibrating element. For the PWS with LED diodes, the signal was received statistically significantly quicker than in the case of other PWS and the mean value of voice response time was below 3 s. Full article
(This article belongs to the Special Issue Smart, Autonomous and Evolved Technologies in Internet of Things)
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19 pages, 3811 KiB  
Article
Fisheye-Based Smart Control System for Autonomous UAV Operation
by Donggeun Oh and Junghee Han
Sensors 2020, 20(24), 7321; https://doi.org/10.3390/s20247321 - 20 Dec 2020
Cited by 6 | Viewed by 2643
Abstract
Recently, as UAVs (unmanned aerial vehicles) have become smaller and higher-performance, they play a very important role in the Internet of Things (IoT). Especially, UAVs are currently used not only in military fields but also in various private sectors such as IT, agriculture, [...] Read more.
Recently, as UAVs (unmanned aerial vehicles) have become smaller and higher-performance, they play a very important role in the Internet of Things (IoT). Especially, UAVs are currently used not only in military fields but also in various private sectors such as IT, agriculture, logistics, construction, etc. The range is further expected to increase. Drone-related techniques need to evolve along with this change. In particular, there is a need for the development of an autonomous system in which a drone can determine and accomplish its mission even in the absence of remote control from a GCS (Ground Control Station). Responding to such requirements, there have been various studies and algorithms developed for autonomous flight systems. Especially, many ML-based (Machine-Learning-based) methods have been proposed for autonomous path finding. Unlike other studies, the proposed mechanism could enable autonomous drone path finding over a large target area without size limitations, one of the challenges of ML-based autonomous flight or driving in the real world. Specifically, we devised Multi-Layer HVIN (Hierarchical VIN) methods that increase the area applicable to autonomous flight by overlaying multiple layers. To further improve this, we developed Fisheye HVIN, which applied an adaptive map compression ratio according to the drone’s location. We also built an autonomous flight training and verification platform. Through the proposed simulation platform, it is possible to train ML-based path planning algorithms in a realistic environment that takes into account the physical characteristics of UAV movements. Full article
(This article belongs to the Special Issue Smart, Autonomous and Evolved Technologies in Internet of Things)
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17 pages, 958 KiB  
Article
User Experience Sensor for Man–Machine Interaction Modeled as an Analogy to the Tower of Hanoi
by Arkadiusz Gardecki, Michal Podpora, Ryszard Beniak, Bartlomiej Klin and Sławomir Pochwała
Sensors 2020, 20(15), 4074; https://doi.org/10.3390/s20154074 - 22 Jul 2020
Cited by 1 | Viewed by 2588
Abstract
This paper presents a novel user experience optimization concept and method, named User Experience Sensor, applied within the Hybrid Intelligence System (HINT). The HINT system, defined as a combination of an extensive AI system and the possibility of attaching a human expert, is [...] Read more.
This paper presents a novel user experience optimization concept and method, named User Experience Sensor, applied within the Hybrid Intelligence System (HINT). The HINT system, defined as a combination of an extensive AI system and the possibility of attaching a human expert, is designed to be used by relational agents, which may have a physical form, such as a robot, a kiosk, be embodied in an avatar, or may also exist as only software. The proposed method focuses on automatic process evaluation as a common sensor for optimization of the user experience for every process stage and the indicator for human-expert automatic session activation. This functionality is realized by the User Experience Sensor, which constitutes one of main elements of the self-optimizing interaction system. The authors present the optimization mechanism of the HINT system as an analogy to the process of building a Tower of Hanoi. The proposed sensor evaluates the user experience and measures the user/employee efficiency at every stage of a given process, offering the user to choose other forms of information, interaction, or expert support. The designed HINT system is able to learn and self-optimize, making the entire process more intuitive and easy for each and every user individually. The HINT system with the proposed sensor, implemented in a window assembly facility, successfully reduced assembly time, increased employees’ satisfaction, and assembly quality. The proposed approach can be implemented in numerous man–machine interaction applications. Full article
(This article belongs to the Special Issue Smart, Autonomous and Evolved Technologies in Internet of Things)
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