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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (25 January 2023) | Viewed by 49661

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Prof. Dr. Liang-Bi Chen

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Guest Editor

Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu, Taiwan
Special Issues, Collections and Topics in MDPI journals

Dr. Tian-Hsiang Huang

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Guest Editor

Center for Big Data Research, Kaohsiung Medical University, Kaohsiung, Taiwan
Interests: computational statistics; cloud computing; information retrieval; big data analytics; machine learning; Artificial Intelligence (AI)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editors are inviting submissions to a Special Issue of Applied Sciences on the subject of “Intelligent Systems and Applications of Data Science and Internet of Things Techniques.” Recently, data science (DS) and the Internet of Things (IoT) are primary emerging techniques which are adopted in intelligent systems and applications. Furthermore, thanks to the latest results of research on artificial intelligence (AI), the current systems and applications can count on the intelligence of their operating procedures. In other words, the ongoing development of intelligent systems and applications promotes or improves existing systems and applications by adopting and integrating emerging techniques (such as big data analysis, AI, and IoT). The result is more convenience and benefits for our work and life. This Special Issue will deal with advanced data science, AI, and IoT techniques for intelligent systems and applications. The topics of interest for publication include, but are not limited to:

AIoT-based systems applications;
AIoT-based systems designs;
Artificial intelligence over Internet of Things (AIoT);
Autonomous systems;
Big/smart data analysis and applications;
Computational intelligence;
Deep learning-based intelligent systems;
Edge and fog computing;
Expert systems;
Fuzzy systems;
Healthcare;
Industry 4.0;
Intelligent cyberphysical systems;
Intelligent networking technology;
Intelligent privacy, security, and trust;
Intelligent/smart IoT;
Machine learning-based intelligent systems;

Prof. Dr. Liang-Bi Chen
Dr. Tian-Hsiang Huang
Guest Editors

Manuscript Submission Information

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Published Papers (10 papers)

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Research

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16 pages, 2067 KiB

Open AccessArticle

Lower Bound for Sculpture Garden Problem: Localization of IoT Devices

by Marzieh Eskandari, Bahram Sadeghi Bigham and Mazyar Zahedi-Seresht

Appl. Sci. 2023, 13(4), 2597; https://doi.org/10.3390/app13042597 - 17 Feb 2023

Cited by 1 | Viewed by 1427

Abstract

The purpose of the current study is to investigate a special case of art gallery problem, namely a sculpture garden problem. In this problem, for a given polygon P, the ultimate goal is to place the minimum number of guards (landmarks) to define the interior polygon P by applying a monotone Boolean formula composed of the guards. Using this problem, it can replace the operation-based method with time-consuming, pixel-based algorithms. So, the processing time of some problems in the fields of machine vision, image processing and gamification can be strongly reduced. The problem has also many applications in mobile device localization in the Internet of Things (IoT). An open problem in this regard is the proof of Eppstein’s conjecture, which has remained an open problem since 2007. According to his conjecture, in the worst case,

n - 2

vertex guards are required to describe any n-gon. In this paper, a lower bound is introduced for the special case of this problem (natural vertex guard), which shows that if a polygon can be defined with natural vertex guards, then

n - 2

is a lower bound. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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15 pages, 4693 KiB

Open AccessArticle

Development of a Resource Optimization Platform for Cross-Regional Operation and Maintenance Service for Combine Harvesters

by Weipeng Zhang, Bo Zhao, Liming Zhou, Conghui Qiu, Jizhong Wang, Kang Niu, Hanlu Jiang and Yashuo Li

Appl. Sci. 2022, 12(19), 9873; https://doi.org/10.3390/app12199873 - 30 Sep 2022

Cited by 2 | Viewed by 1862

Abstract

In view of the centralized operation, high failure rate and large number of harvesters involved in the cross-regional operation of combine harvesters, which has led to a surge in maintenance service demand and a lack of effective maintenance service systems, in order to be able to quickly solve problems arising from failures during the process of cross-regional operation, an operation and maintenance (O&M) service platform for the cross-regional operation of combine harvesters was designed in this research on the basis of data resources, supported by the computing power of a big data platform and centered on an artificial intelligence algorithm. Meeting the demand for maintenance service during cross-regional operation, we built a system platform integrating service order management, maintenance service activity management, and maintenance service resource management, and a technical algorithm for operation and maintenance service resource allocation and service path optimization was developed in order to achieve service function modularization and intelligent monitoring, while early warning and display were realized using multi-dimensional platforms such as a PC, a control screen, and a mobile App. This platform was able to solve problems arising when harvesters break down, maintenance service can be carried out quickly when traditional resource information is blocked and the demand for the service is difficult to meet. The reduction in cost and the increased efficiency for agricultural machinery enterprises was also achieved, while the problem of ensuring continued service was systematically solved during the process of cross-regional operation. Finally, the performance of the software architecture and the effect of path optimization were verified. The results showed that the platform system developed using the three-layer C/S architecture offered more stable characteristics, and the path optimization in the platform system was better able to reduce the maintenance time and distance, thus making it possible to realize the dynamic on-demand configuration and scheduling management of cross-region job service resources. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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12 pages, 2045 KiB

Open AccessArticle

Deep Recurrent Neural Network Assisted Stress Detection System for Working Professionals

by Sameer Dev Sharma, Sonal Sharma, Rajesh Singh, Anita Gehlot, Neeraj Priyadarshi and Bhekisipho Twala

Appl. Sci. 2022, 12(17), 8678; https://doi.org/10.3390/app12178678 - 30 Aug 2022

Cited by 7 | Viewed by 2070

Abstract

Predicting the stress levels of working professionals is one of the most time-consuming and difficult research topics of current day. As a result, estimating working professionals’ stress levels is critical in order to assist them in growing and developing professionally. Numerous machine learning and deep learning algorithms have been developed for this purpose in previous papers. They do, however, have some disadvantages, including increased design complexity, a high rate of misclassification, a high rate of errors, and decreased efficiency. To address these concerns, the purpose of this research is to forecast the stress levels of working professionals using a sophisticated deep learning model called the Deep Recurrent Neural Network (DRNN). The model proposed here comprises dataset preparation, feature extraction, optimal feature selection, and classification using DRNNs. Preprocessing the original dataset removes duplicate attributes and fills in missing values. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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14 pages, 5908 KiB

Open AccessArticle

A Smartphone-Based Mobility Assistant Using Depth Imaging for Visually Impaired and Blind

by Aaron Raymond See, Bien Grenier Sasing and Welsey Daniel Advincula

Appl. Sci. 2022, 12(6), 2802; https://doi.org/10.3390/app12062802 - 9 Mar 2022

Cited by 27 | Viewed by 6050

Abstract

The means of assisting visually impaired and blind (VIB) people when travelling usually relies on other people. Assistive devices have been developed to assist in blind navigation, but many technologies require users to purchase more devices and they lack flexibility, thus making it inconvenient for VIB users. In this research, we made use of a mobile phone with a depth camera function for obstacle avoidance and object recognition. It includes a mobile application that is controlled using simple voice and gesture controls to assist in navigation. The proposed system gathers depth values from 23 coordinate points that are analyzed to determine whether an obstacle is present in the head area, torso area, or ground area, or is a full body obstacle. In order to provide a reliable warning system, the research detects outdoor objects within a distance of 1.6 m. Subsequently, the object detection function includes a unique interactable feature that enables interaction with the user and the device in finding indoor objects by providing an audio and vibration feedback, and users were able to locate their desired objects more than 80% of the time. In conclusion, a flexible and portable system was developed using a depth camera-enabled mobile phone for use in obstacle detection without the need to purchase additional hardware devices. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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18 pages, 700 KiB

Open AccessArticle

Password-Guessing Attack-Aware Authentication Scheme Based on Chinese Remainder Theorem for 5G-Enabled Vehicular Networks

by Mahmood A. Al-Shareeda, Mohammed Anbar, Selvakumar Manickam and Iznan H. Hasbullah

Appl. Sci. 2022, 12(3), 1383; https://doi.org/10.3390/app12031383 - 27 Jan 2022

Cited by 29 | Viewed by 3492

Abstract

The new fifth-generation (5G) cellular networks dramatically improve the speed of message transmissions. Most existing authentication schemes that secure 5G communication rely heavily on the vehicle’s tamper-proof device (TPD) and roadside units (RSUs) to store the system’s master key. However, it only takes a single compromised TPD to render the whole system insecure. We propose a password-guessing attack-aware authentication scheme based on the Chinese Remainder Theorem (CRT) to secure inter-vehicle communication on 5G-enabled vehicular networks to address this issue. The trusted authorities (TAs) in the proposed scheme generate and broadcast new group keys to the vehicles assisted by CRT. Moreover, since the system’s master key does not need to be preloaded, the proposed scheme only requires realistic TPDs. The proposed scheme overcomes password-guessing attacks and guarantees top-level security for entire 5G-enabled vehicular networks. The security analysis indicates that the proposed scheme is secure against adaptive chosen-message attacks under the random oracle model and meets the security requirements of a 5G-enabled vehicular network. Since cryptographic operations based on elliptic curve cryptography are employed, the performance evaluation shows that the proposed scheme outperforms the eight existing schemes in terms of computation and communication costs. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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23 pages, 4874 KiB

Open AccessArticle

An Internet of Things (IoT)-Based Master-Slave Regionalized Intelligent LED-Light-Controlling System

by Chun-Te Lee, Liang-Bi Chen, Huan-Mei Chu, Che-Jen Hsieh and Wei-Chieh Liang

Appl. Sci. 2022, 12(1), 420; https://doi.org/10.3390/app12010420 - 2 Jan 2022

Cited by 8 | Viewed by 4160

Abstract

Reducing residential and industrial electricity consumption has been a goal of governments around the world. Lighting sources account for a large portion of the whole energy/power consumption. Unfortunately, most of the existing installed lighting systems are ancient and have poor energy efficiency. Today, many manufacturers have introduced light-controlling systems into the current market. However, existing light controlling systems may not be successfully applied to buildings, streets, and industrial buildings due to high costs and difficult installation and maintenance. To combat this issue, this article presents an easy-to-install, low-cost, Master-Slave intelligent LED light-controlling system based on Internet of Things (IoT) techniques. The benefit of using the proposed system is that the brightness of the LED lights in the same zone can be changed simultaneously to save in energy consumption. Furthermore, the parameters of the LED lights can be directly set. Moreover, the related data are collected and uploaded to a cloud platform. In this article, we use 15 W T8 LED tubes (non-induction lamps) as a case study. When the proposed system is installed in a zone with few people, the energy-saving rate is as high as 90%. Furthermore, when 12 people pass by a zone within one hour, its energy-saving rate can reach 81%. Therefore, the advantages of using the proposed system include: (1) the original lamp holder can be retained; (2) no wiring is required; and (3) no server is set up. Moreover, the goal of energy saving can also be achieved. As a result, the proposed system changes the full-dark mode of the available sensor lamp to the low power low-light mode for standby. Further, it makes the sensor lamps in the same zone brighten or low-light way simultaneously, which can quickly complete large-scale energy-saving and convenient control functions of intelligent LED lighting controlling system. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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22 pages, 52944 KiB

Open AccessArticle

The Wearable Physical Fitness Training Device Based on Fuzzy Theory

by Yu-Xiang Zhao, Zheng-Xian Lu, Yi-Zeng Hsieh, Shih-Syun Lin and Pei-Ying Chiang

Appl. Sci. 2021, 11(21), 9976; https://doi.org/10.3390/app11219976 - 25 Oct 2021

Cited by 3 | Viewed by 2617

Abstract

Mobile Edge Computing and Communication (MECC) can be deployed in close proximity with sensing devices and act as middleware between cloud and local networks. The health and fitness movement has become extremely popular recently. Endurance activities, such as marathons, triathlons, and cycling have also grown in popularity. However, with more people participating in these activities, more accidents and injuries occur—ranging from heat stroke, to heart attacks, shock, or hypoxia. All physical training activities include a risk of injury and accidents. Therefore, any research that offers a means of reducing injury risk will significantly contribute to the personal fitness field. Moreover, with the growing popularity of wearable devices and the rise of the MECC, the development and application of wearable devices that can connect to the MECC has become widespread, producing many new innovations. Although many wearable devices, such as wrist straps and smart watches, are available and able to detect individual physiological data, they cannot monitor the human body in a state of motion. Therefore, this study proposes a set of monitoring parameters for a novel wearable device connected to the MECC based on fitness management to assist fitness trainers in effective prompted strength training, and to offer timely warnings in the event of an injury risk. The data collected by the monitoring device using fuzzy theory include risk factor, body temperature, heart rate, and blood oxygen concentration. The proposed system can display in real-time the current physiological state of a wearer/user. The introduction of this device will hopefully enable trainers to immediately and effectively control and monitor the intensity of a training session, while increasing training safety, and offer crucial and immediate diagnostic information so that the correct treatment can be applied without delay in the event of injury. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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15 pages, 3459 KiB

Open AccessArticle

Creating Tactile Educational Materials for the Visually Impaired and Blind Students Using AI Cloud Computing

by Aaron Raymond See and Welsey Daniel Advincula

Appl. Sci. 2021, 11(16), 7552; https://doi.org/10.3390/app11167552 - 17 Aug 2021

Cited by 7 | Viewed by 8205

Abstract

There are 24.5 million visually impaired and blind (VIB) students who have limited access to educational materials due to cost or availability. Although advancement in technology is prevalent, providing individualized learning using technology remains a challenge without the proper tools or experience. The TacPic system was developed as an online platform to create tactile educational materials (TEM) based on the image inputs of users who do not have prior experience in tactile photo development or 3D printing. The TacPic system allows the users to simply upload images to a website and uses AI cloud computing on the Amazon Web Services platform. First, it segments and labels the images. Then, the text label is converted into braille words. Subsequently, surface rendering and consolidation of the image and text is performed, before it is converted into a single file that is ready for 3D printing. Currently, the types of TEM that can be created are tactile flashcards, tactile maps, and tactile peg puzzles, which can be developed within a few hours. This is in contrast to a development period of weeks using traditional methods. Furthermore, the tactile educational materials were tested by two VIB teachers and six VIB students. It was found that those who are congenitally blind need more time to identify the object and rely more on the braille labels compared to students who became blind at a later age. Teachers also suggested producing TEM that use simpler images, and TEM that are suitable for both sighted and VIB students. In conclusion, the researchers successfully developed a platform that allows more educators or parents to develop personalized and individualized TEM. In the future, further optimization of the algorithms to improve segmentation and the inclusion of other features, such as color, could be undertaken. Finally, new printing materials and methods are needed to improve printing efficiency. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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19 pages, 1286 KiB

Open AccessArticle

Exploring the Relationship between Internal Information Security, Response Cost, and Security Intention in Container Shipping

by Hsin-Wei Wang, Szu-Yu Kuo and Liang-Bi Chen

Appl. Sci. 2021, 11(6), 2609; https://doi.org/10.3390/app11062609 - 15 Mar 2021

Cited by 6 | Viewed by 2709

Abstract

This study empirically investigates the influence of information security marketing and response cost on employees’ information security intention in the container shipping industry. Survey data were collected from 285 respondents in Taiwan. Exploratory factor analysis was employed to identify all the measures to be summarized in a relative set. Confirmatory factor analysis was utilized to ensure every measure’s construct’s convergent and discriminant validity. Structural equation modeling was carried out to the proposed model in this article. The results indicate that organizational information security marketing has a positive impact on information security intention. Furthermore, this study conducted hierarchical regression to examine the moderating effects of information security awareness and information security climate. In particular, information security awareness significantly influenced the relationships between organizational information security marketing, response cost, and information security intention. Moreover, information security climate moderated the relationship between response cost and information security intention. This article concludes by discussing these theoretical and practical findings and implications. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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Review

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17 pages, 788 KiB

Open AccessReview

Touch, Texture and Haptic Feedback: A Review on How We Feel the World around Us

by Aaron Raymond See, Jose Antonio G. Choco and Kohila Chandramohan

Appl. Sci. 2022, 12(9), 4686; https://doi.org/10.3390/app12094686 - 6 May 2022

Cited by 29 | Viewed by 14466

Abstract

Touch is one most of the important aspects of human life. Nearly all interactions, when broken down, involve touch in one form or another. Recent advances in technology, particularly in the field of virtual reality, have led to increasing interest in the research of haptics. However, accurately capturing touch is still one of most difficult engineering challenges currently being faced. Recent advances in technology such as those found in microcontrollers which allow the creation of smaller sensors and feedback devices may provide the solution. Beyond capturing and measuring touch, replicating touch is also another unique challenge due to the complexity and sensitivity of the human skin. The development of flexible, soft-wearable devices, however, has allowed for the creating of feedback systems that conform to the human form factor with minimal loss of accuracy, thus presenting possible solutions and opportunities. Thus, in this review, the researchers aim to showcase the technologies currently being used in haptic feedback, and their strengths and limitations. Full article

(This article belongs to the Special Issue Intelligent Systems and Applications of Data Science and Internet of Things Techniques Ⅱ)

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