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Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022

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

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 13510

Special Issue Editor

Dr. Rafal Scherer

E-Mail Website
Guest Editor
Associate Professor, Institute of Computational Intelligence, Częstochowa University Of Technology, 42-201 Czestochowa, Poland
Interests: neural networks; computer vision; cybersecurity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Machine learning and computational intelligence methods, especially deep learning, can be used to create smart sensors that can perform testing, classification, or prediction. The whole menagerie of sensors, including inductive proximity sensors, photoelectric retroreflective sensors, ultrasonic sensors, and others, can be beneficial to all areas—from Industry 4.0 through cars to smart offices, homes, or hospitals. Synergistic hyperconnectivity brought by the emergence of the IoT will increase the applicability of such intelligent sensors. This Special Issue is addressed to all soft computing methods enabling in-sensor, edge, and similar computing for machine vision, data acquisition, or diagnostics. The methods covered will include deep learning, fuzzy logic, evolutionary methods, and various data mining techniques.

Dr. Rafal Scherer
Guest Editor

Manuscript Submission Information

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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.

Keywords

  • sensor networks
  • smart/intelligent sensors
  • sensor devices
  • sensor technology and application
  • sensing principles
  • Internet of Things
  • fuzzy logic
  • data mining
  • data fusion and deep learning in sensor systems

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Related Special Issue

Published Papers (5 papers)

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Research

16 pages, 7011 KiB  
Article
Online Store Aesthetics Impact Efficacy of Product Recommendations and Highlighting
by Piotr Sulikowski, Michał Kucznerowicz, Iwona Bąk, Andrzej Romanowski and Tomasz Zdziebko
Sensors 2022, 22(23), 9186; https://doi.org/10.3390/s22239186 - 26 Nov 2022
Cited by 11 | Viewed by 2730
Abstract
Owing to high competition in e-commerce, customers may prefer sites that ensure that good user experience (UX) and website aesthetics are one of its qualities. The method of presenting items seems crucial for gaining and maintaining user attention. We conducted a task-based user [...] Read more.
Owing to high competition in e-commerce, customers may prefer sites that ensure that good user experience (UX) and website aesthetics are one of its qualities. The method of presenting items seems crucial for gaining and maintaining user attention. We conducted a task-based user eye-tracking study with n = 30 participants to examine two variants of an online fashion store: one based on aesthetic rules and one defying them. The following aspects of item presentation were considered: height and width the ratio of product photos, website colors, rounded borders, text visibility, spacing between elements, and smooth animation. We investigated their relationship to user attention by analyzing gaze fixation, tracking user interest, and conducting a supplementary survey. Experimental results showed that owing to following the rules of aesthetics in interface design in the presented fashion shopping scenario, elements such as the recommendation area and product highlights had a significant positive impact on customer attention. Full article
(This article belongs to the Special Issue Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022)
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13 pages, 2563 KiB  
Article
Attempts to Attract Eyesight in E-Commerce May Have Negative Effects
by Piotr Sulikowski, Konrad Ryczko, Iwona Bąk, Soojeong Yoo and Tomasz Zdziebko
Sensors 2022, 22(22), 8597; https://doi.org/10.3390/s22228597 - 8 Nov 2022
Cited by 4 | Viewed by 1855
Abstract
E-commerce shop owners often want to attract user attention to a specific product to enhance the chances of sales, to cross-sell, or up-sell. The way of presenting a recommended item is as important as the recommendation algorithms are to gain that attention. In [...] Read more.
E-commerce shop owners often want to attract user attention to a specific product to enhance the chances of sales, to cross-sell, or up-sell. The way of presenting a recommended item is as important as the recommendation algorithms are to gain that attention. In this study, we examined the following types of highlights: background, shadow, animation, and border, as well as the position of the item in a 5 × 2 grid in a furniture online store, and their relationships with user fixations and user interest. We wanted to verify the effects highlighting had on attracting user attention. Various levels of intensity were considered for each highlight: low, medium, and strong. Methods used for data collection were both implicit and explicit: eye tracking, tracking cart’s contents, and a supplementary survey. Experimental results showed that a low-intensity background highlight should be the first-choice solution to best attract user attention in the presented shopping scenario, resulting in the best fixation times and most users’ selections. However, in the case of the highest-intensity animations, highlighting seemed to have negative effects; despite successful attempts to attract eyesight and a long fixation time, users did not add the highlighted products to cart. Full article
(This article belongs to the Special Issue Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022)
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15 pages, 5709 KiB  
Article
Development and Validation of an Algorithm for the Digitization of ECG Paper Images
by Vincenzo Randazzo, Edoardo Puleo, Annunziata Paviglianiti, Alberto Vallan and Eros Pasero
Sensors 2022, 22(19), 7138; https://doi.org/10.3390/s22197138 - 21 Sep 2022
Cited by 11 | Viewed by 3428
Abstract
The electrocardiogram (ECG) signal describes the heart’s electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is [...] Read more.
The electrocardiogram (ECG) signal describes the heart’s electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is twofold: firstly, all medical applications can be easily implemented with an engineering approach if the ECGs are treated as signals; secondly, paper ECGs can deteriorate over time, therefore a correct evaluation of the patient’s clinical evolution is not always guaranteed. The goal of this paper is the realization of an automatic conversion algorithm from paper-based ECGs (images) to digital ECG signals. The algorithm involves a digitization process tested on an image set of 16 subjects, also with pathologies. The quantitative analysis of the digitization method is carried out by evaluating the repeatability and reproducibility of the algorithm. The digitization accuracy is evaluated both on the entire signal and on six ECG time parameters (R-R peak distance, QRS complex duration, QT interval, PQ interval, P-wave duration, and heart rate). Results demonstrate the algorithm efficiency has an average Pearson correlation coefficient of 0.94 and measurement errors of the ECG time parameters are always less than 1 mm. Due to the promising experimental results, the algorithm could be embedded into a graphical interface, becoming a measurement and collection tool for cardiologists. Full article
(This article belongs to the Special Issue Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022)
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29 pages, 14054 KiB  
Article
Containerized Architecture Performance Analysis for IoT Framework Based on Enhanced Fire Prevention Case Study: Rwanda
by Eric Hitimana, Gaurav Bajpai, Richard Musabe, Louis Sibomana and Kayavizhi Jayavel
Sensors 2022, 22(17), 6462; https://doi.org/10.3390/s22176462 - 27 Aug 2022
Cited by 2 | Viewed by 2673
Abstract
Nowadays, building infrastructures are pushed to become smarter in response to desires for the environmental comforts of living. Enhanced safety upgrades have begun taking advantage of new, evolving technologies. Normally, buildings are configured to respond to the safety concerns of the occupants. However, [...] Read more.
Nowadays, building infrastructures are pushed to become smarter in response to desires for the environmental comforts of living. Enhanced safety upgrades have begun taking advantage of new, evolving technologies. Normally, buildings are configured to respond to the safety concerns of the occupants. However, advanced Internet of Things (IoT) techniques, in combination with edge computing with lightweight virtualization technology, is being used to improve users’ comfort in their homes. It improves resource management and service isolation without affecting the deployment of heterogeneous hardware. In this research, a containerized architectural framework for support of multiple concurrent deployed IoT applications for smart buildings was proposed. The prototype developed used sensor networks as well as containerized microservices, centrally featuring the DevOps paradigm. The research proposed an occupant counting algorithm used to check occupants in and out. The proposed framework was tested in different academic buildings for data acquisition over three months. Different deployment architectures were tested to ensure the best cases based on efficiency and resource utilization. The acquired data was used for prediction purposes to aid occupant prediction for safety measures as considered by policymakers. Full article
(This article belongs to the Special Issue Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022)
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18 pages, 5304 KiB  
Article
Use of Polar Heliostats to Improve Levels of Natural Lighting inside Buildings with Little Access to Sunlight
by Luis Manuel Fernández-Ahumada, Maximiliano Osuna-Mérida, Jesús López-Sánchez, Francisco Javier Gómez-Uceda, Rafael López-Luque and Marta Varo-Martínez
Sensors 2022, 22(16), 5996; https://doi.org/10.3390/s22165996 - 11 Aug 2022
Cited by 3 | Viewed by 2119
Abstract
The growing need to increase environmental and energy sustainability in buildings (housing, offices, warehouses, etc.) requires the use of solar radiation as a renewable source of energy that can help to lower carbon footprint, making buildings more efficient and thereby contributing to a [...] Read more.
The growing need to increase environmental and energy sustainability in buildings (housing, offices, warehouses, etc.) requires the use of solar radiation as a renewable source of energy that can help to lower carbon footprint, making buildings more efficient and thereby contributing to a more sustainable planet, while enhancing the health and wellbeing of its occupants. One of the technologies deployed in the use of solar energy in buildings is heliostats. In this context, this paper presents an analysis of the performance of a heliostat illuminator to improve illumination in a classroom at the Campus of Rabanales of the University of Cordoba (Spain). A design of a system in charge of monitoring and measuring daylighting variables using Arduino hardware technology and free software is shown. This equipment develops the communications, programming and collection of lighting data. In parallel, installation of an artificial lighting system complementary to the natural lighting system is implemented. Finally, an analysis of the impact of the proposed solution on the improvement of energy efficiency is presented. Specifically, it is estimated that up to 64% of savings in artificial lighting can be achieved in spaces with heliostatic illuminators compared to those without them. Full article
(This article belongs to the Special Issue Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment 2022)
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