Applied System Innovation

21 pages, 3291 KiB

Open AccessArticle

Smart Diet Diary: Real-Time Mobile Application for Food Recognition

by Muhammad Nadeem, Henry Shen, Lincoln Choy and Julien Moussa H. Barakat

Appl. Syst. Innov. 2023, 6(2), 53; https://doi.org/10.3390/asi6020053 - 20 Apr 2023

Cited by 13 | Viewed by 6172

Growing obesity has been a worldwide issue for several decades. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a working adult can be [...] Read more.

Growing obesity has been a worldwide issue for several decades. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a working adult can be difficult. This paper presents the design and development of a smartphone-based diet-tracking application, Smart Diet Diary, to assist obese people as well as patients to manage their dietary intake for a healthier life. The proposed system uses deep learning to recognize a food item and calculate its nutritional value in terms of calorie count. The dataset used comprises 16,000 images of food items belonging to 14 different categories to train a multi-label classifier. We applied a pre-trained faster R-CNN model for classification and achieved an overall accuracy of approximately 80.1% and an average calorie computation within 10% of the real calorie value. Full article

(This article belongs to the Special Issue Machine Learning for Digital Health and Bioinformatics)

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21 pages, 8906 KiB

Open AccessArticle

The Challenge of Digital Transition in Engineering. A Solution Made from a European Collaborative Network of Remote Laboratories Based on Renewable Energies Technology

by Macarena Martínez, Francisca Segura and José Manuel Andújar

Appl. Syst. Innov. 2023, 6(2), 52; https://doi.org/10.3390/asi6020052 - 20 Apr 2023

Cited by 5 | Viewed by 2219

Abstract

Society currently faces two crucial challenges: digital transition and energy transition. Educative innovation plays a key role in this challenging scenario, particularly engineering careers, where laboratory practices are as important as theoretical classes. This paper presents a standardized training platform supported by five [...] Read more.

Society currently faces two crucial challenges: digital transition and energy transition. Educative innovation plays a key role in this challenging scenario, particularly engineering careers, where laboratory practices are as important as theoretical classes. This paper presents a standardized training platform supported by five European universities which include a remote laboratory experience. Each university is responsible for developing a training module under the guidance provided by the responsible entity (University of Huelva, Spain). For this purpose, the University of Huelva has implemented a remote laboratory based on a supercapacitor power bank. The rest of the universities have selected any other renewable source and have replicated the information and communications technology (ICT) infrastructure. The result is a European network materialized on a homogenized platform where teachers and students can find all the teaching materials (theory and practice) to train and to be trained in renewable energy matters in the new digital era. Full article

(This article belongs to the Section Applied Systems on Educational Innovations and Emerging Technologies)

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33 pages, 3908 KiB

Open AccessArticle

Data Verification in the Agent, Combining Blockchain and Quantum Keys by Means of Multiple-Valued Logic

by Alexey Yu. Bykovsky and Nikolay A. Vasiliev

Appl. Syst. Innov. 2023, 6(2), 51; https://doi.org/10.3390/asi6020051 - 6 Apr 2023

Cited by 3 | Viewed by 2124

Abstract

Network control of autonomous robotic devices involves a vast number of secured data coding, verification, and identification procedures to provide reliable work of distant agents. Blockchain scheme provides here the model of the extended linked list for the verification of critical data, approved [...] Read more.

Network control of autonomous robotic devices involves a vast number of secured data coding, verification, and identification procedures to provide reliable work of distant agents. Blockchain scheme provides here the model of the extended linked list for the verification of critical data, approved by quasi-random hash values assigned by external network nodes. And quantum lines are the source of high-quality quasi-random keys used as hash values. Discrete multiple-valued logic in such procedures is a simple and flexible tool to form the logic linked list, combining critical internal parameters of agents with data taken from external nodes. Such combination enlarges the set of possible schemes for data protection from illegal modifications and for data restoration. Full article

(This article belongs to the Special Issue Software Engineering for IoT: Latest Advances and Prospects)

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22 pages, 7223 KiB

Open AccessReview

A Review on Recent Trends and Applications of IoT in Additive Manufacturing

by Bharat Kumar Chigilipalli, Teja Karri, Sathish Naidu Chetti, Girish Bhiogade, Ravi Kumar Kottala and Muralimohan Cheepu

Appl. Syst. Innov. 2023, 6(2), 50; https://doi.org/10.3390/asi6020050 - 6 Apr 2023

Cited by 16 | Viewed by 4338

Abstract

The Internet of Things (IoT) is a new way of communicating that is changing the way things are monitored and controlled from a distance. Gradually, companies want to digitalize their production processes and implement control and monitoring systems on the shop floor. On [...] Read more.

The Internet of Things (IoT) is a new way of communicating that is changing the way things are monitored and controlled from a distance. Gradually, companies want to digitalize their production processes and implement control and monitoring systems on the shop floor. On the basis of the Industry 4.0 concept, internet features and database services have been incorporated into processes in order to reinvent manufacturing. This study proposes a proof-of-concept system for the management of additive manufacturing (AM) machines, where an internet integration of beacon technology in the manufacturing environment enables the rapid and intuitive interchange of production data retrieved from machines with mobile devices in various applications. Even though AM technologies can be used to customize the final product, they cannot be used to make a lot of 3D-printed jobs at once for commercial usage. Therefore, this research-based study aims to understand IoT technologies to improve the understanding and reliability of AM processes and 3D print smart materials in large quantities for manufacturers around the world. This study demonstrates the significance of the successful use of internet-based technologies in AM by examining its practical consequences in various fields. This paper gives an overview of IoT-based remote monitoring and control systems that could solve problems in AM, particularly in digital twin, human augmentation (HA), 3D bioprinters, 3D scanners, input parameters optimization, and electronics fields. IoT in AM makes production processes more efficient, reduces waste, and meets customer needs. Full article

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26 pages, 8953 KiB

Open AccessArticle

Evolution of the Human Role in Manufacturing Systems: On the Route from Digitalization and Cybernation to Cognitization

by Elvis Hozdić and Igor Makovec

Appl. Syst. Innov. 2023, 6(2), 49; https://doi.org/10.3390/asi6020049 - 3 Apr 2023

Cited by 7 | Viewed by 3689

Abstract

Modern society is living at a time of revolutionary changes in all areas of human life. For example, the field of industrial manufacturing has greatly influenced the role of human beings during the past 30 years. Modern manufacturing systems are in a phase [...] Read more.

Modern society is living at a time of revolutionary changes in all areas of human life. For example, the field of industrial manufacturing has greatly influenced the role of human beings during the past 30 years. Modern manufacturing systems are in a phase of transition, in accordance with the concept of the fourth industrial revolution (Industry 4.0). A new manufacturing paradigm based on the principles of Industry 4.0 is presented by Smart Manufacturing Systems (SMS). A basic building block of SMS is cyber-physical production systems (CPPS), which together with innovative-management principles of emergence, self-organization, learning, open innovation, collaboration and the networking of people and organizations are the key principles of Industry 4.0. The three key enablers of Industry 4.0, i.e., the connectivity, the digitization and the cybernation of work processes in manufacturing systems, have paved the way for a new industrial revolution, i.e., Industry 5.0 concept that is bringing about a new paradigm in the field of manufacturing systems, the so-called Adaptive Cognitive Manufacturing Systems (ACMS). A fundamental building block of ACMS is the new generation of manufacturing systems called Cognitive Cyber-Physical Production Systems (C-CPPS), which are based on CPPS concepts and incorporate cognitive technologies and artificial intelligence. This paper presents the revolutionary development of manufacturing and manufacturing systems through the industrial revolutions and the evolution of the role of humans in manufacturing systems towards Industry 5.0. Full article

(This article belongs to the Special Issue Towards the Innovations and Smart Factories)

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22 pages, 948 KiB

Open AccessReview

Comparing the Evolutionary Trajectories of Industry 4.0 and 5.0: A Management Fashion Perspective

by Dag Øivind Madsen and Kåre Slåtten

Appl. Syst. Innov. 2023, 6(2), 48; https://doi.org/10.3390/asi6020048 - 30 Mar 2023

Cited by 7 | Viewed by 3561

Abstract

The concept of Industry 4.0 has received enormous levels of attention since it was introduced in 2011 and continues to be a dominant management trend. However, during the last few years, Industry 5.0 has emerged as an alternative visionary management concept. Although Industry [...] Read more.

The concept of Industry 4.0 has received enormous levels of attention since it was introduced in 2011 and continues to be a dominant management trend. However, during the last few years, Industry 5.0 has emerged as an alternative visionary management concept. Although Industry 5.0 builds on and is related to its predecessor, it provides a different vision of the future of industry. Therefore, the aim of this paper is to carry out an in-depth examination of these two related management concepts, using management fashion theory as an interpretive framework and lens. Viewing Industry 4.0 and 5.0 from this vantage point involves analyzing and tracing the involvement activities of the suppliers of the two concepts as well as gauging the concepts’ demand-side impact. Generally, the comparative analysis of the cases of Industry 4.0 and 5.0 indicates that, while the growth and popularity of Industry 4.0 appear to have plateaued, it remains at a high level. Although Industry 5.0 is growing in popularity and is gaining followers and supporters, it is still a much more marginal concept and movement. This study contributes to the management fashion literature by showing how two highly related but competing management concept movements coevolve. Furthermore, the two cases provide novel insights into the trajectories and lifecycles of fashionable management concepts, in particular, the early phase where actors are actively attempting to generate credibility and legitimacy and drum up support and enthusiasm for their preferred ideas. Full article

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12 pages, 1761 KiB

Open AccessTutorial

The Project-Based Learning Study of Insurance Information Courses to Simulate the Application of Online Analytical Processing

by Yung-Cheng Liao and Mei-Su Chen

Appl. Syst. Innov. 2023, 6(2), 47; https://doi.org/10.3390/asi6020047 - 29 Mar 2023

Cited by 2 | Viewed by 1881

Abstract

The use of data warehouses combined with online analytical processing (OLAP) platforms has become popular in Taiwan’s insurance market. However, most schools do not have an insurance data warehouse and OLAP platform for student learning in Taiwan. The researched courses are insurance information [...] Read more.

The use of data warehouses combined with online analytical processing (OLAP) platforms has become popular in Taiwan’s insurance market. However, most schools do not have an insurance data warehouse and OLAP platform for student learning in Taiwan. The researched courses are insurance information system courses for two university classes. Based on the teacher’s experience and innovativeness, those courses are integrated using the guided project-based learning approach. Students need to build a customer micro-database, analyze customer figures through pivot analysis charts, and plan marketing campaigns. The study finds a project-based learning approach is helpful to enhance students’ OLAP analysis abilities. Secondly, the research finds that the flexibility for students to choose the topic of their project is one of the key success factors. Thirdly, the evaluation share of the student’s learning scores is important for the completion of the project. Fourthly, the courses are accompanied with satisfaction questionnaires to monitor the learning results and analyze the learning satisfaction for students among course A, course B, and the college average. Those students in the two classes both have higher satisfaction scores than the college average, but there are still differences between the classes after the t-test. Full article

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18 pages, 4167 KiB

Open AccessArticle

IoT-Aware Architecture to Guarantee Safety of Maintenance Operators in Industrial Plants

by Teodoro Montanaro, Ilaria Sergi, Ilaria Stefanizzi, Luca Landi, Luciano Di Donato and Luigi Patrono

Appl. Syst. Innov. 2023, 6(2), 46; https://doi.org/10.3390/asi6020046 - 28 Mar 2023

Cited by 3 | Viewed by 2492

Abstract

One of the most important factors that influence people’s daily lives and their well-being at work is the so-called “worker safety”. Different literature works demonstrated the positive effects on worker mood and well-being brought by the awareness of being in a safe environment [...] Read more.

One of the most important factors that influence people’s daily lives and their well-being at work is the so-called “worker safety”. Different literature works demonstrated the positive effects on worker mood and well-being brought by the awareness of being in a safe environment and, consequently, less prone to accidents. Every working environment should guarantee safety protection to employees and operators both in normal operations and extraordinary duties (e.g., maintenance operations), however, the industrial domain is the one that is more exposed to risks for workers. Different technologies already accomplished such requirements in “normal” operations, nonetheless, the literature still lacks solutions to also monitor and guide operators during exceptional and dangerous operations (e.g., maintenance). The combination of IoT and Industry 4.0 can guide the research toward the resolution of the maintenance-related exposed problems. This paper proposes an IoT-aware architecture for the industrial domain to support maintenance operators. It was designed to guide them step by step while real-time monitoring plant, machinery, and other employees working in the same area. During the maintenance procedure, the operator is guided in the proper execution of every single step required by maintenance and an autonomous IoT system monitors the status of the different parts of the plants and machinery to, then, authorize and show, the next steps foreseen in the maintenance process. To test the feasibility and usefulness of the proposed system, a prototype was developed and functionally tested through the exploitation of a machinery simulator and a real lathe machine. Full article

(This article belongs to the Special Issue Software Engineering for IoT: Latest Advances and Prospects)

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22 pages, 4226 KiB

Open AccessArticle

Analyzing the Feasibility of Integrating Urban Sustainability Assessment Indicators with City Information Modelling (CIM)

by Adriana Salles, Maryam Salati and Luís Bragança

Appl. Syst. Innov. 2023, 6(2), 45; https://doi.org/10.3390/asi6020045 - 27 Mar 2023

Cited by 3 | Viewed by 2307

Abstract

Sustainability assessment methods have gained the attention between urban planners and policymakers since they promote a comprehensive view of the cities. Intelligent solutions, enabled by advances in information technologies, can accelerate progress in achieving sustainability goals. In this context, City Information Modelling (CIM) [...] Read more.

Sustainability assessment methods have gained the attention between urban planners and policymakers since they promote a comprehensive view of the cities. Intelligent solutions, enabled by advances in information technologies, can accelerate progress in achieving sustainability goals. In this context, City Information Modelling (CIM) emerges as a tool to facilitate urban sustainability assessment implementation. Accordingly, the main question aimed to address in this article is whether conventional sustainability assessment tools can be adapted to the CIM framework. In this regard, this study extracts the most consensual list of indicators from four sustainability assessment methods: BREEAM-C, LEED-ND, SNTool, and SBTool^PT Urban, to identify a clear set of key sustainability priorities. The selected sustainability assessment methods are pioneering and often used for performance assessment at the urban scale. Furthermore, the indicators extracted from the assessment methods are measurable and can present accurate results. The study analyses the potential of the selected indicators to be calculated in CIM. The final product of the article is identifying the indicators that are adaptable to be used in the CIM approach. Full article

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16 pages, 8511 KiB

Open AccessArticle

Experimental Interpretation of the Provisions of EN 13796-3 for Fatigue Testing of Cableway Gondolas

by Arkadiusz Bednarz, Krzysztof Bieniek, Radosław Kołodziejczyk, Zygmunt Szczerba, Piotr Krauz, Monika Lubas and Kamil Szczerba

Appl. Syst. Innov. 2023, 6(2), 44; https://doi.org/10.3390/asi6020044 - 26 Mar 2023

Viewed by 1748

Abstract

This article presents an experimental approach to fatigue testing of cableway gondolas, carried out in accordance with the EN 13796-3 standard. Due to the limitations of the aforementioned regulations and the lack of clarity in their content, when designing and conducting fatigue tests [...] Read more.

This article presents an experimental approach to fatigue testing of cableway gondolas, carried out in accordance with the EN 13796-3 standard. Due to the limitations of the aforementioned regulations and the lack of clarity in their content, when designing and conducting fatigue tests of gondolas, there is a need to find solutions that meet the normative requirements, while ensuring the cost-effectiveness of the tests. The work presents the method of loading, receiving the degrees of freedom, the methodology of gondola strength verification and additional suggestions allowing for the satisfactory preparation of a plan of fatigue tests and their implementation. The paper shows problems and ways to solve it, what may occur during cableway gondolas fatigue test design. In addition, the work contains an extensive description and methodology for conducting research verifying the elastic and permanent deformation of the structure, using digital image correlation (DIC). The results obtained by using this method make it possible to unambiguously determine the degree of structure deformation while maintaining high accuracy and repeatability of measurements at many points of the structure. Following the presented tests, it was possible to correctly carry out fatigue tests of the nacelle in a satisfactory time (about 8 weeks), perform 5 million load cycles and verify the integrity of the structure. The presented results show the effectiveness of the adopted design assumptions and indicate the process that guarantees the correctness of the conducted fatigue tests. The prepared study may be the basis for further full-scale fatigue tests. The research object is a 6-seater gondola designed by TRANSSYSTEM S.A. Full article

(This article belongs to the Section Industrial and Manufacturing Engineering)

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17 pages, 7762 KiB

Open AccessArticle

Performance Analysis of a Zero-Energy Building Using Photovoltaics and Hydrogen Storage

by Evangelos Bellos, Panagiotis Lykas and Christos Tzivanidis

Appl. Syst. Innov. 2023, 6(2), 43; https://doi.org/10.3390/asi6020043 - 20 Mar 2023

Cited by 7 | Viewed by 2455

Abstract

The exploitation of renewable energy sources in the building sector is a challenging aspect of achieving sustainability. The incorporation of a proper storage unit is a vital issue for managing properly renewable electricity production and so to avoid the use of grid electricity. [...] Read more.

The exploitation of renewable energy sources in the building sector is a challenging aspect of achieving sustainability. The incorporation of a proper storage unit is a vital issue for managing properly renewable electricity production and so to avoid the use of grid electricity. The present investigation examines a zero-energy residential building that uses photovoltaics for covering all its energy needs (heating, cooling, domestic hot water, and appliances-lighting needs). The building uses a reversible heat pump and an electrical heater, so there is not any need for fuel. The novel aspect of the present analysis lies in the utilization of hydrogen as the storage technology in a power-to-hydrogen-to-power design. The residual electricity production from the photovoltaics feeds an electrolyzer for hydrogen production which is stored in the proper tank under high pressure. When there is a need for electricity, and the photovoltaics are not enough, the hydrogen is used in a fuel cell for producing the needed electricity. The present work examines a building of 400 m² floor area in Athens with total yearly electrical demand of 23,656 kWh. It was found that the use of 203 m² of photovoltaics with a hydrogen storage capacity of 34 m³ can make the building autonomous for the year period. Full article

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13 pages, 1813 KiB

Open AccessArticle

Could the ‘Spinner Innovation’ and ‘Triple Helix’ Models Improve System Innovation?

by Ronnie Figueiredo, Mohammad Soliman, Alamir N. Al-Alawi and Tarek Fatnassi

Appl. Syst. Innov. 2023, 6(2), 42; https://doi.org/10.3390/asi6020042 - 16 Mar 2023

Cited by 3 | Viewed by 4349

Abstract

Although several prior studies have outlined and examined models associated with knowledge and innovation in different fields, the literature lacks any solid insights combining the Triple Helix model and the Spinner Innovation model and ascertaining their relevance to innovation. This article correspondingly presents [...] Read more.

Although several prior studies have outlined and examined models associated with knowledge and innovation in different fields, the literature lacks any solid insights combining the Triple Helix model and the Spinner Innovation model and ascertaining their relevance to innovation. This article correspondingly presents an unprecedented alternative based on two innovation models, analyzing and structuring a process to innovate in different economic sectors. In doing so, this paper seeks to explore how this integration between Spinner Innovation and Triple Helix models could have a significant influence to improve system innovation. We collected data from the Scopus database spanning the period between 2012 and 2021 to study the integration of the models. The analysis identifies how these models differ but are nevertheless of complementary importance for developing regional and national economies through combining the “helices”, the “fidgets” and the framework integrating both models and their components to system innovation. Full article

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11 pages, 12103 KiB

Open AccessArticle

Power Curve Modeling of Wind Turbines through Clustering-Based Outlier Elimination

by Chunhyun Paik, Yongjoo Chung and Young Jin Kim

Appl. Syst. Innov. 2023, 6(2), 41; https://doi.org/10.3390/asi6020041 - 15 Mar 2023

Cited by 4 | Viewed by 2685

Abstract

The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and [...] Read more.

The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and thus the power curve estimation necessitates the detection and proper treatment of outliers. This study proposes a novel procedure for outlier detection and elimination for estimating power curves of wind farms by employing clustering algorithms of vector quantization and density-based spatial clustering of applications with noise. Testing different parametric models of power output curve, the proposed methodology is demonstrated for obtaining power curves of individual wind turbines in a Korean wind farm. It is asserted that the outlier elimination procedure for power curve modeling outlined in this study can be highly efficient at the presence of noises. Full article

(This article belongs to the Special Issue Wind Energy and Wind Turbine System)

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11 pages, 366 KiB

Open AccessCommunication

Assessing the Risk of Spreading COVID-19 in the Room Utilizing Low-Cost Monitoring System

by Marek Bujňák, Rastislav Pirník, Pavol Kuchár and Karol Rástočný

Appl. Syst. Innov. 2023, 6(2), 40; https://doi.org/10.3390/asi6020040 - 14 Mar 2023

Cited by 1 | Viewed by 1739

Abstract

High hygiene standards were established during the COVID-19 epidemic, and their adherence was closely monitored. They included the need to regularly wash one’s hands and the requirement to cover person’s upper airways or keep at least a two-meter space between individuals. The ITS [...] Read more.

High hygiene standards were established during the COVID-19 epidemic, and their adherence was closely monitored. They included the need to regularly wash one’s hands and the requirement to cover person’s upper airways or keep at least a two-meter space between individuals. The ITS (Information Technology Systems) community made a big contribution to this by developing methods and applications for the ongoing observation of people and the environment. Our major objective was to create a low-cost, straightforward system for tracking and assessing the danger of spreading COVID-19 in a space.The proposed system collects data from various low-cost environmental sensors such as temperature, humidity, CO

_{2}

, the number of people, the dynamics of speech, and the cleanliness of the environment with a significant connection to elements of wearable electronics and then evaluate the level of contamination and possible risks and, in the event of a high level of risk, alerts the person to take actions that can reduce or eliminate favourable conditions for the spread of the virus. The system was created at the Laboratory of industrial control systems of the University of Žilina, Slovakia. The experiment demonstrates the ability and feasibility to control the number of people in a space depending on particular symptoms like fever, coughing, and hand hygiene. On the other hand, the laboratory’s temperature, humidity, and air quality should be controlled to reduce the spread of illness. Full article

(This article belongs to the Special Issue Smart Sensors and Devices: Recent Advances and Applications)

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3 pages, 209 KiB

Open AccessEditorial

New Innovation, Sustainability, and Resilience Challenges in the X.0 Era

by Maryam Gallab and Mario Di Nardo

Appl. Syst. Innov. 2023, 6(2), 39; https://doi.org/10.3390/asi6020039 - 13 Mar 2023

Cited by 4 | Viewed by 1728

Abstract

Facing a constantly evolving industry and customers that are becoming more fastidious, companies are seeking to adapt their manufacturing methods to meet market demands [...] Full article

(This article belongs to the Special Issue New Challenges of Innovation, Sustainability, Resilience in X.0 Era)

33 pages, 9776 KiB

Open AccessArticle

e-Archeo: A Pilot National Project to Valorize Italian Archaeological Parks through Digital and Virtual Reality Technologies

by Eva Pietroni, Sofia Menconero, Carolina Botti and Francesca Ghedini

Appl. Syst. Innov. 2023, 6(2), 38; https://doi.org/10.3390/asi6020038 - 9 Mar 2023

Cited by 4 | Viewed by 2933

Abstract

Commissioned to ALES spa by the Ministry of Culture (MiC), the e-Archeo project was born with the intention of enhancing and promoting knowledge of some Italian archaeological sites with a considerable narrative potential that has not yet been fully expressed. The main principle [...] Read more.

Commissioned to ALES spa by the Ministry of Culture (MiC), the e-Archeo project was born with the intention of enhancing and promoting knowledge of some Italian archaeological sites with a considerable narrative potential that has not yet been fully expressed. The main principle that guided the choice of the sites and the contents was of illustrating the various cultures and types of settlements present in the Italian territory. Eight sites were chosen, spread across the national territory from north to south, founded by Etruscans, Greeks, Phoenicians, natives and Romans. e-Archeo has developed multimedia, integrated and multi-channel solutions for various uses and types of audiences, adopting both scientific and narrative and emotional languages. Particular attention was paid to multimedia accessibility, technological sustainability and open science. The e-Archeo project was born from a strong synergy between public entities, research bodies and private industries thanks to the collaboration of MiC and ALES with the CNR ISPC, 10 Italian Universities, 12 Creative Industries and the Italian National Television (RAI). This exceptional and unusual condition made it possible to realise all the project’s high-quality contents and several outputs in only one and a half years. Full article

(This article belongs to the Special Issue Advanced Virtual Reality Technologies and Their Applications)

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11 pages, 1536 KiB

Open AccessArticle

QACM: Quality Aware Crowd Sensing in Mobile Computing

by B. M. Thippeswamy, Mohamed Ghouse, Shanawaz Ahmed Jafarabad, Murtuza Ahamed Khan Mohammed, Ketema Adere, Prabhu Prasad B. M. and Pavan Kumar B. N.

Appl. Syst. Innov. 2023, 6(2), 37; https://doi.org/10.3390/asi6020037 - 8 Mar 2023

Viewed by 2157

Abstract

Mobile computing is one of the significant opportunities that can be used for various practical applications in numerous fields in real life. Due to inherent characteristics of ubiquitous computing, devices can gather numerous types of data that led to innovative applications in many [...] Read more.

Mobile computing is one of the significant opportunities that can be used for various practical applications in numerous fields in real life. Due to inherent characteristics of ubiquitous computing, devices can gather numerous types of data that led to innovative applications in many fields with a unique emerging prototype known as Crowd sensing. Here, the involvement of people is one of the important features and their mobility provides an exclusive opportunity to collect and transmit the data over a substantial geographical area. Thus, we put forward novel idea about Quality of Information (QOI) with unique parameters with opportunistic uniqueness of people’s mobility in terms of sensing and transmission. Additionally, we propose some of the viable improved ideas about the competent opportunistic data collection through efficient techniques. This work also considered some of the open issues mentioned by previous related works. Full article

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19 pages, 3913 KiB

Open AccessArticle

Human-Centric Aggregation via Ordered Weighted Aggregation for Ranked Recommendation in Recommender Systems

by Shahab Saquib Sohail, Asfia Aziz, Rashid Ali, Syed Hamid Hasan, Dag Øivind Madsen and M. Afshar Alam

Appl. Syst. Innov. 2023, 6(2), 36; https://doi.org/10.3390/asi6020036 - 6 Mar 2023

Viewed by 2078

Abstract

In this paper, we propose an approach to recommender systems that incorporates human-centric aggregation via Ordered Weighted Aggregation (OWA) to prioritize the suggestions of expert rankers over the usual recommendations. We advocate for ranked recommendations where rankers are assigned weights based on their [...] Read more.

In this paper, we propose an approach to recommender systems that incorporates human-centric aggregation via Ordered Weighted Aggregation (OWA) to prioritize the suggestions of expert rankers over the usual recommendations. We advocate for ranked recommendations where rankers are assigned weights based on their ranking position. Our approach recommends books to university students using linguistic data summaries and the OWA technique. We assign higher weights to the highest-ranked university to improve recommendation quality. Our approach is evaluated on eight parameters and outperforms traditional recommender systems. We claim that our approach saves storage space and solves the cold start problem by not requiring prior user preferences. Our proposed scheme can be applied to decision-making problems, especially in the context of recommender systems, and offers a new direction for human-specific task aggregation in recommendation research. Full article

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18 pages, 6629 KiB

Open AccessArticle

Gesture-to-Text Translation Using SURF for Indian Sign Language

by Kaustubh Mani Tripathi, Pooja Kamat, Shruti Patil, Ruchi Jayaswal, Swati Ahirrao and Ketan Kotecha

Appl. Syst. Innov. 2023, 6(2), 35; https://doi.org/10.3390/asi6020035 - 2 Mar 2023

Cited by 3 | Viewed by 6778

Abstract

This research paper focuses on developing an effective gesture-to-text translation system using state-of-the-art computer vision techniques. The existing research on sign language translation has yet to utilize skin masking, edge detection, and feature extraction techniques to their full potential. Therefore, this study employs [...] Read more.

This research paper focuses on developing an effective gesture-to-text translation system using state-of-the-art computer vision techniques. The existing research on sign language translation has yet to utilize skin masking, edge detection, and feature extraction techniques to their full potential. Therefore, this study employs the speeded-up robust features (SURF) model for feature extraction, which is resistant to variations such as rotation, perspective scaling, and occlusion. The proposed system utilizes a bag of visual words (BoVW) model for gesture-to-text conversion. The study uses a dataset of 42,000 photographs consisting of alphabets (A–Z) and numbers (1–9), divided into 35 classes with 1200 shots per class. The pre-processing phase includes skin masking, where the RGB color space is converted to the HSV color space, and Canny edge detection is used for sharp edge detection. The SURF elements are grouped and converted to a visual language using the K-means mini-batch clustering technique. The proposed system’s performance is evaluated using several machine learning algorithms such as naïve Bayes, logistic regression, K nearest neighbors, support vector machine, and convolutional neural network. All the algorithms benefited from SURF, and the system’s accuracy is promising, ranging from 79% to 92%. This research study not only presents the development of an effective gesture-to-text translation system but also highlights the importance of using skin masking, edge detection, and feature extraction techniques to their full potential in sign language translation. The proposed system aims to bridge the communication gap between individuals who cannot speak and those who cannot understand Indian Sign Language (ISL). Full article

(This article belongs to the Section Artificial Intelligence)

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15 pages, 5888 KiB

Open AccessArticle

Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control

by Ayad Q. Al-Dujaili, Amjad J. Humaidi, Ziyad T. Allawi and Musaab E. Sadiq

Appl. Syst. Innov. 2023, 6(2), 34; https://doi.org/10.3390/asi6020034 - 28 Feb 2023

Cited by 17 | Viewed by 2194

Abstract

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based [...] Read more.

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulated on the basis of earthquake acceleration data recorded from the El Centro Imperial Valley Earthquake. The effectiveness of the adaptive synergetic control was verified and assessed via numerical simulation, and a comparison study was conducted between the adaptive and classical versions of synergetic control (SC). The vibration suppression index was used to evaluate both controllers. The numerical simulation showed the capability of the proposed adaptive controller to stabilize and to suppress the vibration of a building subjected to earthquake. In addition, the adaptive controller successfully kept the estimated viscosity and stiffness coefficients bounded. Full article

(This article belongs to the Section Control and Systems Engineering)

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19 pages, 8985 KiB

Open AccessArticle

Optimization of Small Horizontal Axis Wind Turbines Based on Aerodynamic, Steady-State, and Dynamic Analyses

by Khalil Deghoum, Mohammed Taher Gherbi, Hakim S. Sultan, Adnan N. Jameel Al-Tamimi, Azher M. Abed, Oday Ibraheem Abdullah, Hamza Mechakra and Ali Boukhari

Appl. Syst. Innov. 2023, 6(2), 33; https://doi.org/10.3390/asi6020033 - 24 Feb 2023

Cited by 6 | Viewed by 3179

Abstract

In this article, the model of a 5 kW small wind turbine blade is developed and improved. Emphasis has been placed on improving the blade’s efficiency and aerodynamics and selecting the most optimal material for the wind blade. The QBlade software was used [...] Read more.

In this article, the model of a 5 kW small wind turbine blade is developed and improved. Emphasis has been placed on improving the blade’s efficiency and aerodynamics and selecting the most optimal material for the wind blade. The QBlade software was used to enhance the chord and twist. Also, a new finite element model was developed using the ANSYS software to analyze the structure and modal problems of the wind blade. The results presented the wind blade’s von Mises stresses and deformations using three different materials (Carbon/epoxy, E-Glass/epoxy, and braided composite). The modal analysis results presented the natural frequencies and mode shapes for each material. It was found, based on the results, that the maximum deflections of E-glass, braided composite and carbon fiber were 46.46 mm, 33.54 mm, and 18.29 mm, respectively. Full article

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26 pages, 4740 KiB

Open AccessArticle

A Distinctive Explainable Machine Learning Framework for Detection of Polycystic Ovary Syndrome

by Varada Vivek Khanna, Krishnaraj Chadaga, Niranajana Sampathila, Srikanth Prabhu, Venkatesh Bhandage and Govardhan K. Hegde

Appl. Syst. Innov. 2023, 6(2), 32; https://doi.org/10.3390/asi6020032 - 23 Feb 2023

Cited by 38 | Viewed by 8125

Abstract

Polycystic Ovary Syndrome (PCOS) is a complex disorder predominantly defined by biochemical hyperandrogenism, oligomenorrhea, anovulation, and in some cases, the presence of ovarian microcysts. This endocrinopathy inhibits ovarian follicle development causing symptoms like obesity, acne, infertility, and hirsutism. Artificial Intelligence (AI) has revolutionized [...] Read more.

Polycystic Ovary Syndrome (PCOS) is a complex disorder predominantly defined by biochemical hyperandrogenism, oligomenorrhea, anovulation, and in some cases, the presence of ovarian microcysts. This endocrinopathy inhibits ovarian follicle development causing symptoms like obesity, acne, infertility, and hirsutism. Artificial Intelligence (AI) has revolutionized healthcare, contributing remarkably to science and engineering domains. Therefore, we have demonstrated an AI approach using heterogeneous Machine Learning (ML) and Deep Learning (DL) classifiers to predict PCOS among fertile patients. We used an Open-source dataset of 541 patients from Kerala, India. Among all the classifiers, the final multi-stack of ML models performed best with accuracy, precision, recall, and F1-score of 98%, 97%, 98%, and 98%. Explainable AI (XAI) techniques make model predictions understandable, interpretable, and trustworthy. Hence, we have utilized XAI techniques such as SHAP (SHapley Additive Values), LIME (Local Interpretable Model Explainer), ELI5, Qlattice, and feature importance with Random Forest for explaining tree-based classifiers. The motivation of this study is to accurately detect PCOS in patients while simultaneously proposing an automated screening architecture with explainable machine learning tools to assist medical professionals in decision-making. Full article

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Appl. Syst. Innov., Volume 6, Issue 2 (April 2023) – 22 articles

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