Smart Sensor Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 30629

Special Issue Editors


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Guest Editor
School of Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: smart sensors; sensing technology; WSN; IoT; ICT; smart grid; energy harvesting
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Life Sciences, University Technology Sydney, Building 7 (CB07), 638 Jones Street, Broadway Ultimo, NSW 2007, Australia
Interests: sensors; chemical synthesis; chemistry; organic synthesis; health science; phytochrome; molecular synthesis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors play a significant role in our everyday life. it is of paramount importance to know our surroundings. The monitoring of surroundings is done with the help of smart, accurate, and reliable sensors. The configuration of smart sensors in the form of a network can measure and collect data from the environment, weather, traffic congestion, air and water pollution, health parameters, human activities and so on. Data collected through sensors enhance our lives and our connections to each other and with our environment, allow real-time monitoring of many phenomena around us, and provide information about the quality of products and services to increase knowledge of the physical and chemical world. The measured data is processed and transmitted via wireless or wired communication technologies to a central station for further processing of data to take corrective and decisive actions.

The advancement in high-quality materials, fabrication technologies, electronics, embedded controllers, and technology for communication as well as the progress towards a better informed, knowledge-based society increase the demand for small size, affordable smart sensors that can provide accurate and reliable data recording, processing, storing, and communication.

This Special Issue solicits the submission of high-quality and unpublished papers as well as extended papers from the 13th International Conference on Sensing Technology to be held during December 2 to 4, 2019 in Sydney, Australia that aim to solve open technical problems and challenges typical of smart sensors and sensor networks. The main aim is to integrate novel approaches efficiently, focusing on the performance evaluation and the comparison with existing solutions. Both theoretical and experimental studies for typical smart sensors and sensor networks including all recent communication methodologies including LoRaWan, LTE, and 5G are encouraged. Furthermore, high-quality review and survey papers are also welcome. Submitted papers from ICST 2019 should be extended to the size of regular research or review articles, with at least a 50% extension of new results.

Paper addressing, but not limited to, the following topics will be considered for publication:

  • Smart sensors
  • Wireless sensor networks
  • Internet of things
  • Communication technologies, BT, WiFi, ZigBee, LoRaWAN, and so on
  • Smart sensors for home automation and smart home
  • Wireless sensors networks for smart homes
  • Internet of things-enabled home automation
  • Green communications for smart homes
  • Energy management systems and networks for smart homes
  • Smart environment monitoring and control
  • Smart management of home appliances

Prof. Dr. Subhas Mukhopadhyay
Dr. Krishanthi P. Jayasundera
Guest Editors

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. Electronics 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 2400 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

  • Smart sensors
  • Sensor networks
  • WSN and IoT
  • IoT-enabled sensors
  • Eldercare
  • Healthcare
  • Human activity recognition
  • Home automation
  • Green communications
  • Security and privacy
  • Artificial intelligence
  • WSN for smart homes
  • IoT-enabled homes

Published Papers (7 papers)

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Research

18 pages, 4815 KiB  
Article
Potential of Pressure Sensor Based Mass Estimation Methods for Electric Buses
by Utz Spaeth, Heiko Fechtner, Michele Weisbach and Benedikt Schmuelling
Electronics 2020, 9(5), 711; https://doi.org/10.3390/electronics9050711 - 26 Apr 2020
Cited by 5 | Viewed by 2968
Abstract
One approach to improve the economic efficiency of trolleybuses in the so-called BOB Project in the German town of Solingen is to use them as mobile energy storages in a smart grid. To achieve this, reliable information on available energy is essential, which [...] Read more.
One approach to improve the economic efficiency of trolleybuses in the so-called BOB Project in the German town of Solingen is to use them as mobile energy storages in a smart grid. To achieve this, reliable information on available energy is essential, which in turn needs to be derived from a precise range calculator. As shown in this article, vehicle mass is a strong influencing factor, especially in urban traffic. Depending on passenger volume, the total mass and range of the bus varies by about 30 percent. The currently available mass on the bus fluctuates by more than 2 tons for constant payloads, and there is no proven solution for a more accurate mass estimation for buses in public passenger transportation. Therefore, this article presents a viable methodology to detect changes in payload, using high precision pressure sensors on the bus’s tires and air suspensions. These mass inducted pressure changes are extracted from the measurement data, using a filter to be later converted back into the corresponding masses. As the article will show, both approaches have their respective advantages and disadvantages, but have high potential and should therefore be investigated further. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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24 pages, 7901 KiB  
Article
An Integrated Toolbox for the Engagement of Citizens in the Monitoring of Water Ecosystems
by Maria Krommyda, Anastasios Rigos, Spyridon-Nektarios Bolierakis, Theodoros Theodoropoulos, Stefano Tamascelli, Luca Simeone, Evangelos Sdongos and Angelos Amditis
Electronics 2020, 9(4), 671; https://doi.org/10.3390/electronics9040671 - 20 Apr 2020
Cited by 4 | Viewed by 2636
Abstract
The monitoring of water ecosystems requires consistent and accurate sensor measurements, usually provided from traditional in-situ environmental monitoring systems. Such infrastructure, however, is expensive, hard to maintain and available only in limited areas that had been affected by extreme phenomena and require continuous [...] Read more.
The monitoring of water ecosystems requires consistent and accurate sensor measurements, usually provided from traditional in-situ environmental monitoring systems. Such infrastructure, however, is expensive, hard to maintain and available only in limited areas that had been affected by extreme phenomena and require continuous monitoring. Due to climate change, the monitoring of larger areas and extended water ecosystems is imperative, raising the question of whether this monitoring can be disengaged from the in-situ monitoring systems. Due to climate change and extreme weather phenomena, more citizens are affected by environmental issues and become aware of the need to contribute to their monitoring. As a result, they are willing to offer their time to support the collection of scientific data. Collecting such data from volunteers, with no technical knowledge and while using low-cost equipment such as smart phones and portable sensors, raises the question of data quality and consistency. We present here a novel integrated toolbox that can support the organization of crowd-sourcing activities, ensure the engagement of the participants, the data collection in a consistent way, enforce extensive data quality controls and provide to local authorities and scientists access to the collected information in a uniform way, through widely accepted standards. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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15 pages, 1207 KiB  
Article
Detecting Sensor Faults, Anomalies and Outliers in the Internet of Things: A Survey on the Challenges and Solutions
by Anuroop Gaddam, Tim Wilkin, Maia Angelova and Jyotheesh Gaddam
Electronics 2020, 9(3), 511; https://doi.org/10.3390/electronics9030511 - 20 Mar 2020
Cited by 98 | Viewed by 8537
Abstract
The Internet of Things (IoT) has gained significant recognition to become a novel sensing paradigm to interact with the physical world in this Industry 4.0 era. The IoTs are being used in many diverse applications that are part of our life and is [...] Read more.
The Internet of Things (IoT) has gained significant recognition to become a novel sensing paradigm to interact with the physical world in this Industry 4.0 era. The IoTs are being used in many diverse applications that are part of our life and is growing to become the global digital nervous systems. It is quite evident that in the near future, hundreds of millions of individuals and businesses with billions will have smart-sensors and advanced communication technology, and these things will expand the boundaries of current systems. This will result in a potential change in the way we work, learn, innovate, live and entertain. The heterogeneous smart sensors within the Internet of Things are indispensable parts, which capture the raw data from the physical world by being the first port of contact. Often the sensors within the IoT are deployed or installed in harsh environments. This inevitably means that the sensors are prone to failure, malfunction, rapid attrition, malicious attacks, theft and tampering. All of these conditions cause the sensors within the IoT to produce unusual and erroneous readings, often known as outliers. Much of the current research has been done in developing the sensor outlier and fault detection models exclusively for the Wireless Sensor Networks (WSN), and adequate research has not been done so far in the context of the IoT. Wireless sensor network’s operational framework differ greatly when compared to IoT’s operational framework, using some of the existing models developed for WSN cannot be used on IoT’s for detecting outliers and faults. Sensor faults and outlier detection is very crucial in the IoT to detect the high probability of erroneous reading or data corruption, thereby ensuring the quality of the data collected by sensors. The data collected by sensors are initially pre-processed to be transformed into information and when Artificially Intelligent (AI), Machine Learning (ML) models are further used by the IoT, the information is further processed into applications and processes. Any faulty, erroneous, corrupted sensor readings corrupt the trained models, which thereby produces abnormal processes or outliers that are significantly distinct from the normal behavioural processes of a system. In this paper, we present a comprehensive review of the detecting sensor faults, anomalies, outliers in the Internet of Things and the challenges. A comprehensive guideline to select an adequate outlier detection model for the sensors in the IoT context for various applications is discussed. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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21 pages, 8014 KiB  
Article
A Telespirometer for the Developing World
by Graham Brooker
Electronics 2020, 9(2), 275; https://doi.org/10.3390/electronics9020275 - 06 Feb 2020
Cited by 1 | Viewed by 2673
Abstract
There are numerous examples in which the introduction of expensive medical equipment into the developing world fail for lack of a basic understanding of the device operation, lack of spare parts and poor maintenance. This paper describes the development of a Fleisch pneumotachograph [...] Read more.
There are numerous examples in which the introduction of expensive medical equipment into the developing world fail for lack of a basic understanding of the device operation, lack of spare parts and poor maintenance. This paper describes the development of a Fleisch pneumotachograph and cellphone based telespirometer that can easily be built from “junk box” medical and electronic components available in the developing world. This approach should introduce a sense of local ownership to the project as well as encouraging participation by the local electronics repair industry. Experimental results confirm that the forced expiratory flow data are reliably modulated onto an audio signal and transmitted by cellphone to a base station for examination by a district nurse or doctor. Flow measurement and data transmission accuracies are sufficiently good for remote diagnoses of chronic obstructive pulmonary disease. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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17 pages, 2044 KiB  
Article
Transducer Electronic Data Sheets: Anywhere, Anytime, Anyway
by Vítor Viegas, Octavian Postolache and J.M. Dias Pereira
Electronics 2019, 8(11), 1345; https://doi.org/10.3390/electronics8111345 - 14 Nov 2019
Cited by 5 | Viewed by 3995
Abstract
Transducer electronic data sheets (TEDS) are a key element of smart transducers because they support core features such as plug and play, self-calibration, and self-diagnostics. The ISO/IEC/IEEE 21451-4 standard defines templates to describe the most common types of transducers and suggests the use [...] Read more.
Transducer electronic data sheets (TEDS) are a key element of smart transducers because they support core features such as plug and play, self-calibration, and self-diagnostics. The ISO/IEC/IEEE 21451-4 standard defines templates to describe the most common types of transducers and suggests the use of one-wire memories to store the corresponding data. In this paper we explore new ways to store and access TEDS tables, including near field communication (NFC) tags and QR codes. We also present a mobile TEDS parser, compatible with Android, that is capable of reading TEDS data from all supported mediums (one-wire memories, NFC tags, and QR codes) and decoding them as human-readable text. The idea is to make TEDS available in the easiest way possible. We also underline the need to extend the 21451-4 standard by adding support for frequency–time sensors. A new TEDS template is proposed, and filling examples are presented. The main novelties of the paper are (i) the proposal of new ways to store 21451-4 TEDS tables using NFC tags and QR codes; (ii) the release of new tools to access TEDS tables including a mobile parser; and (iii) the definition of a new TEDS template for frequency–time sensors. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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24 pages, 6177 KiB  
Article
SARM: Salah Activities Recognition Model Based on Smartphone
by Nafees Ahmad, Lansheng Han, Khalid Iqbal, Rashid Ahmad, Muhammad Adil Abid and Naeem Iqbal
Electronics 2019, 8(8), 881; https://doi.org/10.3390/electronics8080881 - 08 Aug 2019
Cited by 20 | Viewed by 5782
Abstract
Alzheimer’s is a chronic neurodegenerative disease that frequently occurs in many people today. It has a major effect on the routine activities of affected people. Previous advancement in smartphone sensors technology enables us to help people suffering from Alzheimer’s. For people in the [...] Read more.
Alzheimer’s is a chronic neurodegenerative disease that frequently occurs in many people today. It has a major effect on the routine activities of affected people. Previous advancement in smartphone sensors technology enables us to help people suffering from Alzheimer’s. For people in the Muslim community, where it is mandatory to offer prayers five times a day, it may mean that they are struggling in their daily life prayers due to Alzheimer’s or lack of concentration. To deal with such a problem, automated mobile sensor-based activity recognition applications can be supportive to design accurate and precise solutions with an objective to direct the Namazi (worshipper). In this paper, a Salah activities recognition model (SARM) using a mobile sensor is proposed with the aim to recognize specific activities, such as Al-Qayam (standing), Ruku (standing to bowing), and Sujud (standing to prostration). This model entails the collection of data, selection and placement of sensor, data preprocessing, segmentation, feature extraction, and classification. The proposed model will provide a stepping edge to develop an application for observing prayer. For these activities’ recognition, data sets were collected from ten subjects, and six different features sets were used to get improved results. Extensive experiments were performed to test and validate the model features to train random forest (RF), K-nearest neighbor (KNN), naive Bayes (NB), and decision tree (DT). The predicted average accuracy of RF, KNN, NB, and DT was 97%, 94%, 71.6%, and 95% respectively. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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15 pages, 2800 KiB  
Article
Dynamic Stress Measurement with Sensor Data Compensation
by Jingjing Gu, Zhiteng Dong, Cai Zhang, Xiaojiang Du and Mohsen Guizani
Electronics 2019, 8(8), 859; https://doi.org/10.3390/electronics8080859 - 02 Aug 2019
Cited by 2 | Viewed by 3226
Abstract
Applying parachutes-deployed Wireless Sensor Network (WSN) in monitoring the high-altitude space is a promising solution for its effectiveness and cost. However, both the high deviation of data and the rapid change of various environment factors (air pressure, temperature, wind speed, etc.) pose a [...] Read more.
Applying parachutes-deployed Wireless Sensor Network (WSN) in monitoring the high-altitude space is a promising solution for its effectiveness and cost. However, both the high deviation of data and the rapid change of various environment factors (air pressure, temperature, wind speed, etc.) pose a great challenge. To this end, we solve this challenge with data compensation in dynamic stress measurements of parachutes during the working stage. Specifically, we construct a data compensation model to correct the deviation based on neural network by taking into account a variety of environmental parameters, and name it as Data Compensation based on Back Propagation Neural Network (DC-BPNN). Then, for improving the speed and accuracy of training the DC-BPNN, we propose a novel Adaptive Artificial Bee Colony (AABC) algorithm. We also address its stability of solution by deriving a stability bound. Finally, to verify the real performance, we conduct a set of real implemented experiments of airdropped WSN. Full article
(This article belongs to the Special Issue Smart Sensor Networks)
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