Smart Sensors and Devices: Recent Advances and Applications

A special issue of Applied System Innovation (ISSN 2571-5577). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (11 September 2023) | Viewed by 11187

Special Issue Editor


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Guest Editor
School of Engineering, Macquarie University, Sydney, Australia
Interests: drones; robots; swarm drones; swarm robotics; IoT; smart sensors; mechatronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors play an important role and are the brains and hearts of intelligent systems, such as Unmanned Aerial Vehicles, Autonomous Guided Vehicles, drones and mobile robots. With the development of nanomaterials, advanced signal processing techniques, smart interfacing electronics, low-power embedded processosr, long-range communication technologies and multidisciplinary interactions, more and more smart sensors and devices are proposed and fabricated under increasing demands from homes, the industry, environment and military fields. This Special Issue will report on the development of the above technologies and different applications such as, and not limited to, the following:

  • Smart sensors;
  • Sensing technology;
  • Wireless sensors;
  • Smart devices;
  • IoT sensors and devices;
  • Intelligent processing;
  • Machine learning;
  • Artificaial intelligence;
  • Smart homes;
  • Smart environments;
  • Healthcare;
  • Envioromental monitoring;
  • Industrial applications;

Prof. Dr. Subhas Mukhopadhyay
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. Applied System Innovation 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 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

12 pages, 2095 KiB  
Communication
Suitability of Low-Cost Sensors for Submicron Aerosol Particle Measurement
by Daniel Stoll, Maximilian Kerner, Simon Paas and Sergiy Antonyuk
Appl. Syst. Innov. 2023, 6(4), 69; https://doi.org/10.3390/asi6040069 - 8 Aug 2023
Viewed by 1253
Abstract
The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement monitoring of the [...] Read more.
The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement monitoring of the anthropogenic aerosol spreading is necessary. For indoor aerosol measurements usually standard lab equipment is used. However, these devices are time-consuming, expensive and unwieldy. The idea is to replace this standard laboratory equipment with low-cost sensors widely used for monitoring fine dust (particulate matter—PM). Due to the low acquisition costs, many sensors can be used to determine the aerosol load, even in large rooms. Thus, the aim of this work is to verify the measurement capability of low-cost sensors. For this purpose, two different models of low-cost sensors are compared with established laboratory measuring instruments. The study was performed with artificially prepared NaCl aerosols with a well-defined size and morphology. In addition, the influence of the relative humidity, which can vary significantly indoors, on the measurement capability of the low-cost sensors is investigated. For this purpose, a heating stage was developed and tested. The results show a discrepancy in measurement capability between low-cost sensors and laboratory measuring instruments. This difference can be attributed to the partially different measuring method, as well as the different measuring particle size ranges. The determined measurement accuracy is nevertheless good, considering the compactness and the acquisition price of the low-cost sensors. Full article
(This article belongs to the Special Issue Smart Sensors and Devices: Recent Advances and Applications)
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25 pages, 11927 KiB  
Article
A GRASS GIS Scripting Framework for Monitoring Changes in the Ephemeral Salt Lakes of Chotts Melrhir and Merouane, Algeria
by Polina Lemenkova
Appl. Syst. Innov. 2023, 6(4), 61; https://doi.org/10.3390/asi6040061 - 25 Jun 2023
Cited by 5 | Viewed by 1904
Abstract
Automated classification of satellite images is a challenging task that enables the use of remote sensing data for environmental modeling of Earth’s landscapes. In this document, we implement a GRASS GIS-based framework for discriminating land cover types to identify changes in the endorheic [...] Read more.
Automated classification of satellite images is a challenging task that enables the use of remote sensing data for environmental modeling of Earth’s landscapes. In this document, we implement a GRASS GIS-based framework for discriminating land cover types to identify changes in the endorheic basins of the ephemeral salt lakes Chott Melrhir and Chott Merouane, Algeria; we employ embedded algorithms for image processing. This study presents a dataset of the nine Landsat 8–9 OLI/TIRS satellite images obtained from the USGS for a 9-year period, from 2014 to 2022. The images were analyzed to detect changes in water levels in ephemeral lakes that experience temporal fluctuations; these lakes are dry most of the time and are fed with water during rainy periods. The unsupervised classification of images was performed using GRASS GIS algorithms through several modules: ‘i.cluster’ was used to generate image classes; ‘i.maxlik’ was used for classification using the maximal likelihood discriminant analysis, and auxiliary modules, such as ‘i.group’, ‘r.support’, ‘r.import’, etc., were used. This document includes technical descriptions of the scripts used for image processing with detailed comments on the functionalities of the GRASS GIS modules. The results include the identified variations in the ephemeral salt lakes within the Algerian part of the Sahara over a 9-year period (2014–2022), using a time series of Landsat OLI/TIRS multispectral images that were classified using GRASS GIS. The main strengths of the GRASS GIS framework are the high speed, accuracy, and effectiveness of the programming codes for image processing in environmental monitoring. The presented GitHub repository, which contains scripts used for the satellite image analysis, serves as a reference for the interpretation of remote sensing data for the environmental monitoring of arid and semi-arid areas of Africa. Full article
(This article belongs to the Special Issue Smart Sensors and Devices: Recent Advances and Applications)
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29 pages, 14521 KiB  
Article
Using Low-Cost Radar Sensors and Action Cameras to Measure Inter-Vehicle Distances in Real-World Truck Platooning
by Markus Metallinos Log, Thomas Thoresen, Maren H. R. Eitrheim, Tomas Levin and Trude Tørset
Appl. Syst. Innov. 2023, 6(3), 55; https://doi.org/10.3390/asi6030055 - 6 May 2023
Cited by 1 | Viewed by 2971
Abstract
Many modern vehicles collect inter-vehicle distance data from radar sensors as input to driver assistance systems. However, vehicle manufacturers often use proprietary algorithms to conceal the collected data, making them inaccessible to external individuals, such as researchers. Aftermarket sensors may circumvent this issue. [...] Read more.
Many modern vehicles collect inter-vehicle distance data from radar sensors as input to driver assistance systems. However, vehicle manufacturers often use proprietary algorithms to conceal the collected data, making them inaccessible to external individuals, such as researchers. Aftermarket sensors may circumvent this issue. This study investigated the use of low-cost radar sensors to determine inter-vehicle distances during real-world semi-automated truck platooning on two-way, two-lane rural roads. Radar data from the two follower trucks in a three-truck platoon were collected, synchronized and filtered. The sensors measured distance, relative velocity and signal-to-noise ratio. Dashboard camera footage was collected, coded and synchronized to the radar data, providing context about the driving situation, such as oncoming trucks, roundabouts and tunnels. The sensors had different configuration parameters, suggested by the supplier, to avoid signal interference. With parameters as chosen, sensor ranges, inferred from maximum distance measurements, were approximately 74 and 71 m. These values were almost on par with theoretical calculations. The sensors captured the preceding truck for 83–85% of the time where they had the preceding truck within range, and 95–96% of the time in tunnels. While roundabouts are problematic, the sensors are feasible for collecting inter-vehicle distance data during truck platooning. Full article
(This article belongs to the Special Issue Smart Sensors and Devices: Recent Advances and Applications)
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11 pages, 366 KiB  
Communication
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 1505
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, CO2, 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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31 pages, 17192 KiB  
Article
Smart Sensors System Based on Smartphones and Methodology for 3D Modelling in Shallow Water Scenarios
by Gabriele Vozza, Domenica Costantino, Massimiliano Pepe and Vincenzo Saverio Alfio
Appl. Syst. Innov. 2023, 6(1), 28; https://doi.org/10.3390/asi6010028 - 10 Feb 2023
Cited by 1 | Viewed by 2429
Abstract
The aim of the paper was the implementation of low-cost smart sensors for the collection of bathymetric data in shallow water and the development of a 3D modelling methodology for the reconstruction of natural and artificial aquatic scenarios. To achieve the aim, a [...] Read more.
The aim of the paper was the implementation of low-cost smart sensors for the collection of bathymetric data in shallow water and the development of a 3D modelling methodology for the reconstruction of natural and artificial aquatic scenarios. To achieve the aim, a system called GNSS > Sonar > Phone System (G > S > P Sys) was implemented to synchronise sonar sensors (Deeper Smart Sonars CHIRP+ and Pro+ 2) with an external GNSS receiver (SimpleRTK2B) via smartphone. The bathymetric data collection performances of the G > S > P Sys and the Deeper Smart Sonars were studied through specific tests. Finally, a data-driven method based on a machine learning approach to mapping was developed for the 3D modelling of the bathymetric data produced by the G > S > P Sys. The developed 3D modelling method proved to be flexible, easily implementable and capable of producing models of natural surfaces and submerged artificial structures with centimetre accuracy and precision. Full article
(This article belongs to the Special Issue Smart Sensors and Devices: Recent Advances and Applications)
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