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Special Issue "Smart Sensor Technologies for IoT"

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

Deadline for manuscript submissions: closed (1 March 2021).

Special Issue Editors

Prof. Dr. Peter Brida
E-Mail Website
Guest Editor
Faculty of Electrical Engineering and Information Technology, University of Zilina, Zilina, Slovakia
Interests: wireless positioning; modular positioning systems; ubiquitous positioning; satellite navigation systems; intelligent transport systems; mobile positioning; pedestrian dead reckoning; wireless communication
Special Issues and Collections in MDPI journals
Prof. Dr. Ondrej Krejcar
E-Mail Website
Guest Editor
Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove, 50003, Czech Republic
Interests: control systems; smart sensors; ubiquitous computing; manufacturing; wireless technology; portable devices; biomedicine; image segmentation and recognition; biometrics; technical cybernetics; ubiquitous computing
Special Issues and Collections in MDPI journals
Prof. Dr. Ali Selamat
E-Mail Website
Guest Editor
Universiti Teknologi Malaysia (UTM), UTM Kuala Lumpur, Malaysia
Interests: cloud based software engineering; software agents; information retrievals; pattern recognition; genetic algorithms; neural networks; soft computing; knowledge management; key performance indicators
Special Issues and Collections in MDPI journals
Prof. Dr. Attila Kertesz
E-Mail Website
Guest Editor
University of Szeged, Szeged, Hungary
Interests: cloud computing; Internet of Things; fog computing

Special Issue Information

Dear Colleagues,

      The recent development in wireless networks and devices leads to novel services that will utilize wireless communication on a new level. It is possible to see a lot of efforts and resources invested to establish new communication networks that will support massive machine to machine communication and Internet of Things (IoT). In these systems, various smart and sensory devices are assumed to be deployed and connected enabling streaming of large amounts of data.

       New trends in mobile services can be represented by smart services, i.e. completely new spectrum of context-aware, personalized, and intelligent services and applications. Variety of existing services already utilize information about the position of the user or mobile device. Position of mobile devices is in a lot of applications achieved thanks to the use of Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, in foreseen IoT applications the use of GNSS chips integrated into all devices might have a negative impact on their battery life. Therefore, alternative solutions for position estimation should be investigated and implemented in IoT applications.

      Additionally, smart mobile sensors and devices could be able to fulfil an astonishingly wide range of demands of users and providers. One of the reasons behind the wireless device development is the ever-growing computing power together with the reduction of energy consumption and improved communication capabilities of devices.

      In order to process a large amount of data from sensors, further investigation of mobile and dynamic cloud computing solutions is also envisioned. Implementation of new services will be with high probability based on the application of cloud services. This, however, produces additional challenges in such areas as management, security, technical solutions, infrastructure modelling, mobile devices support, and many others.

     This special issue is addressed to researchers and engineers in both academia and industry sectors to exchange ideas, share experiences, and report original works about all aspects of the above-stated philosophy.

     We invite investigators to contribute original as well as review articles on research and development in areas of smart sensor technologies and IoT. These include solutions that are designed for the smart mobile devices covered by wireless networks and solutions that are not directly designed for such use but have the potential for it. Potential topics include, but are not limited to:

  • Sensing technologies supporting IoT services
  • Sensors data processing and fusion
  • Sensors data supporting smart devices localization
  • Sensors data retrieval, storage and processing with Cloud and Fog services
  • Context and location-aware applications based IoT
  • An impact of recent advances in wireless technologies on IoT implementation
  • Multimodal sensors enabling smart IoT
  • Smart cities, smart environment and smart grid
  • Mobile services based on sensor technologies and cloud computing
  • Secure sensor and IoT device management using Blockchain techniques

Prof. Peter Brida
Prof. Dr. Ondrej Krejcar
Prof. Dr. Ali Selamat
Prof. Dr. Attila Kertesz
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 papers will be 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. Sensors 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 2200 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
  • IoT
  • wireless communication
  • mobile localization
  • sensors data processing
  • cloud and fog computing

Published Papers (12 papers)

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Research

Open AccessArticle
Impact of Scene Content on High Resolution Video Quality
Sensors 2021, 21(8), 2872; https://doi.org/10.3390/s21082872 - 19 Apr 2021
Viewed by 383
Abstract
This paper deals with the impact of content on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. The assessment was conducted on eight types of video sequences with diverse content obtained from the SJTU dataset. The sequences were [...] Read more.
This paper deals with the impact of content on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. The assessment was conducted on eight types of video sequences with diverse content obtained from the SJTU dataset. The sequences were encoded at 5 different constant bitrates in two widely video compression standards H.264/AVC and H.265/HEVC at Full HD and Ultra HD resolutions, which means 160 annotated video sequences were created. The length of Group of Pictures (GOP) was set to half the framerate value, as is typical for video intended for transmission over a noisy communication channel. The evaluation was performed in two laboratories: one situated at the University of Zilina, and the second at the VSB—Technical University in Ostrava. The results acquired in both laboratories reached/showed a high correlation. Notwithstanding the fact that the sequences with low Spatial Information (SI) and Temporal Information (TI) values reached better Mean Opinion Score (MOS) score than the sequences with higher SI and TI values, these two parameters are not sufficient for scene description, and this domain should be the subject of further research. The evaluation results led us to the conclusion that it is unnecessary to use the H.265/HEVC codec for compression of Full HD sequences and the compression efficiency of the H.265 codec by the Ultra HD resolution reaches the compression efficiency of both codecs by the Full HD resolution. This paper also includes the recommendations for minimum bitrate thresholds at which the video sequences at both resolutions retain good and fair subjectively perceived quality. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Wi-Fi-Based Location-Independent Human Activity Recognition via Meta Learning
Sensors 2021, 21(8), 2654; https://doi.org/10.3390/s21082654 - 09 Apr 2021
Viewed by 268
Abstract
Wi-Fi-based device-free human activity recognition has recently become a vital underpinning for various emerging applications, ranging from the Internet of Things (IoT) to Human–Computer Interaction (HCI). Although this technology has been successfully demonstrated for location-dependent sensing, it relies on sufficient data samples for [...] Read more.
Wi-Fi-based device-free human activity recognition has recently become a vital underpinning for various emerging applications, ranging from the Internet of Things (IoT) to Human–Computer Interaction (HCI). Although this technology has been successfully demonstrated for location-dependent sensing, it relies on sufficient data samples for large-scale sensing, which is enormously labor-intensive and time-consuming. However, in real-world applications, location-independent sensing is crucial and indispensable. Therefore, how to alleviate adverse effects on recognition accuracy caused by location variations with the limited dataset is still an open question. To address this concern, we present a location-independent human activity recognition system based on Wi-Fi named WiLiMetaSensing. Specifically, we first leverage a Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) feature representation method to focus on location-independent characteristics. Then, in order to well transfer the model across different positions with limited data samples, a metric learning-based activity recognition method is proposed. Consequently, not only the generalization ability but also the transferable capability of the model would be significantly promoted. To fully validate the feasibility of the presented approach, extensive experiments have been conducted in an office with 24 testing locations. The evaluation results demonstrate that our method can achieve more than 90% in location-independent human activity recognition accuracy. More importantly, it can adapt well to the data samples with a small number of subcarriers and a low sampling rate. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Algorithm for Dynamic Fingerprinting Radio Map Creation Using IMU Measurements
Sensors 2021, 21(7), 2283; https://doi.org/10.3390/s21072283 - 24 Mar 2021
Viewed by 336
Abstract
While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide access to accurate position estimates. Indoor positioning systems can be based on many technologies; [...] Read more.
While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide access to accurate position estimates. Indoor positioning systems can be based on many technologies; however, radio networks and more precisely Wi-Fi networks seem to attract the attention of a majority of the research teams. The most widely used localization approach used in Wi-Fi-based systems is based on fingerprinting framework. Fingerprinting algorithms, however, require a radio map for position estimation. This paper will describe a solution for dynamic radio map creation, which is aimed to reduce the time required to build a radio map. The proposed solution is using measurements from IMUs (Inertial Measurement Units), which are processed with a particle filter dead reckoning algorithm. Reference points (RPs) generated by the implemented dead reckoning algorithm are then processed by the proposed reference point merging algorithm, in order to optimize the radio map size and merge similar RPs. The proposed solution was tested in a real-world environment and evaluated by the implementation of deterministic fingerprinting positioning algorithms, and the achieved results were compared with results achieved with a static radio map. The achieved results presented in the paper show that positioning algorithms achieved similar accuracy even with a dynamic map with a low density of reference points. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
A Portable Electromagnetic System Based on mm-Wave Radars and GNSS-RTK Solutions for 3D Scanning of Large Material Piles
Sensors 2021, 21(3), 757; https://doi.org/10.3390/s21030757 - 23 Jan 2021
Viewed by 420
Abstract
In this paper, a portable three-dimensional (3D) scanning system for the accurate characterization of large raw material (e.g., cereal grain, coal, etc.) stockpiles is presented. The system comprises an array of high resolution millimeter-wave radars and a cm-level accuracy positioning system to accurately [...] Read more.
In this paper, a portable three-dimensional (3D) scanning system for the accurate characterization of large raw material (e.g., cereal grain, coal, etc.) stockpiles is presented. The system comprises an array of high resolution millimeter-wave radars and a cm-level accuracy positioning system to accurately characterize large stockpiles by means of a high-resolution 3D map, making it suitable for automation purposes. A control unit manages the data received by the sensors, which are sent to a computer system for processing. As a proof of concept, the entire sensor system is evaluated in a real environment for electromagnetically scan a scaled stockpile of coal, used in the industry for handling raw materials. In addition, a highly efficient processing adaptive algorithm that may reconstruct the scanned structure in real-time has been introduced, enabling continuous dynamic updating of the information. Results are compared with those from a photogrammetry-like technique, revealing an excellent agreement. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSN
Sensors 2021, 21(2), 627; https://doi.org/10.3390/s21020627 - 18 Jan 2021
Cited by 4 | Viewed by 532
Abstract
Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol [...] Read more.
Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
WON-OCDMA System Based on MW-ZCC Codes for Applications in Optical Wireless Sensor Networks
Sensors 2021, 21(2), 539; https://doi.org/10.3390/s21020539 - 13 Jan 2021
Viewed by 441
Abstract
The growing demand for extensive and reliable structural health monitoring resulted in the development of advanced optical sensing systems (OSS) that in conjunction with wireless optical networks (WON) are capable of extending the reach of optical sensing to places where fibre provision is [...] Read more.
The growing demand for extensive and reliable structural health monitoring resulted in the development of advanced optical sensing systems (OSS) that in conjunction with wireless optical networks (WON) are capable of extending the reach of optical sensing to places where fibre provision is not feasible. To support this effort, the paper proposes a new type of a variable weight code called multiweight zero cross-correlation (MW-ZCC) code for its application in wireless optical networks based optical code division multiple access (WON-OCDMA). The code provides improved quality of service (QoS) and better support for simultaneous transmission of video surveillance, comms and sensor data by reducing the impact of multiple access interference (MAI). The MW-ZCC code’s power of two code-weight properties provide enhanced support for the needed service differentiation provisioning. The performance of this novel code has been studied by simulations. This investigation revealed that for a minimum allowable bit error rate of 103, 109 and 1012 when supporting triple-play services (sensing, datacomms and video surveillance, respectively), the proposed WON-OCDMA using MW-ZCC codes could support up to 32 simultaneous services over transmission distances up to 32 km in the presence of moderate atmospheric turbulence. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
BLE-Based Indoor Tracking System with Overlapping-Resistant IoT Solution for Tourism Applications
Sensors 2021, 21(2), 329; https://doi.org/10.3390/s21020329 - 06 Jan 2021
Viewed by 441
Abstract
In this paper, an overlapping-resistant Internet of Things (IoT) solution for a Bluetooth Low Energy (BLE)-based indoor tracking system (BLE-ITS) is presented. The BLE-ITS is a promising, inexpensive alternative to the well-known GPS. It can be used in human traffic analysis, such as [...] Read more.
In this paper, an overlapping-resistant Internet of Things (IoT) solution for a Bluetooth Low Energy (BLE)-based indoor tracking system (BLE-ITS) is presented. The BLE-ITS is a promising, inexpensive alternative to the well-known GPS. It can be used in human traffic analysis, such as indoor tourist facilities. Tourists or other customers are tagged by a unique MAC address assigned to a simple and energy-saving BLE beacon emitter. Their location is determined by a distributed and scalable network of popular Raspberry Pi microcomputers equipped with BLE and WiFi/Ethernet modules. Only simple triggered messages in the form of login records (LRs) are sent to a server, where the so-called path vectors (PVs) and interest profile (IPr) are set. The authors implemented the prototype and demonstrated its usefulness in a controlled environment. As it is shown in the paper, the solution is highly overlap-resistant and mitigates the so-called multilocation problem. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Which Digital-Output MEMS Magnetometer Meets the Requirements of Modern Road Traffic Survey?
Sensors 2021, 21(1), 266; https://doi.org/10.3390/s21010266 - 03 Jan 2021
Viewed by 532
Abstract
Present systems for road traffic surveillance largely utilize MEMS magnetometers for the purpose of vehicle detection and classification. Magnetoresistive sensing or LR oscillation circuitry are technologies providing the sensors with the competitive advantage which lies in the energy efficiency and low price. There [...] Read more.
Present systems for road traffic surveillance largely utilize MEMS magnetometers for the purpose of vehicle detection and classification. Magnetoresistive sensing or LR oscillation circuitry are technologies providing the sensors with the competitive advantage which lies in the energy efficiency and low price. There are several chip suppliers on the market who specialize in the development of these sensors. The aim of this paper is to compare available sensors from the viewpoint of their suitability for traffic measurements. A summary of the achieved results is given in the form of the score for each sensor. The introduced sensor chart should provide the audience with knowledge about pros and cons of sensors, especially if intended for the purposes of road traffic surveillance. The authors in this research focused on the specific situation of road traffic monitoring with magnetometers placed at the roadside. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
A Smart IoT System for Detecting the Position of a Lying Person Using a Novel Textile Pressure Sensor
Sensors 2021, 21(1), 206; https://doi.org/10.3390/s21010206 - 31 Dec 2020
Viewed by 684
Abstract
Bedsores are one of the severe problems which could affect a long-term lying subject in the hospitals or the hospice. To prevent lying bedsores, we present a smart Internet of Things (IoT) system for detecting the position of a lying person using novel [...] Read more.
Bedsores are one of the severe problems which could affect a long-term lying subject in the hospitals or the hospice. To prevent lying bedsores, we present a smart Internet of Things (IoT) system for detecting the position of a lying person using novel textile pressure sensors. To build such a system, it is necessary to use different technologies and techniques. We used sixty-four of our novel textile pressure sensors based on electrically conductive yarn and the Velostat to collect the information about the pressure distribution of the lying person. Using Message Queuing Telemetry Transport (MQTT) protocol and Arduino-based hardware, we send measured data to the server. On the server side, there is a Node-RED application responsible for data collection, evaluation, and provisioning. We are using a neural network to classify the subject lying posture on the separate device because of the computation complexity. We created the challenging dataset from the observation of twenty-one people in four lying positions. We achieved a best classification precision of 92% for fourth class (right side posture type). On the other hand, the best recall (91%) for first class (supine posture type) was obtained. The best F1 score (84%) was achieved for first class (supine posture type). After the classification, we send the information to the staff desktop application. The application reminds employees when it is necessary to change the lying position of individual subjects and thus prevent bedsores. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Multilayered Network Model for Mobile Network Infrastructure Disruption
Sensors 2020, 20(19), 5491; https://doi.org/10.3390/s20195491 - 25 Sep 2020
Viewed by 560
Abstract
In this paper, the novel study of the multilayered network model for the disrupted infrastructure of the 5G mobile network is introduced. The aim of this study is to present the new way of incorporating different types of networks, such as Wireless Sensor [...] Read more.
In this paper, the novel study of the multilayered network model for the disrupted infrastructure of the 5G mobile network is introduced. The aim of this study is to present the new way of incorporating different types of networks, such as Wireless Sensor Networks (WSN), Mobile Ad-Hoc Networks (MANET), and DRONET Networks into one fully functional multilayered network. The proposed multilayered network model also presents the resilient way to deal with infrastructure disruption due to different reasons, such as disaster scenarios or malicious actions. In the near future, new network technologies of 5G networks and the phenomenon known as the Internet of Things (IoT) will empower the functionality of different types of networks and interconnects them into one complex network. The proposed concept is oriented on resilient, smart city applications such as public safety and health and it is able to provide critical communication when fixed network infrastructure is destroyed by deploying smart sensors and unmanned aerial vehicles. The provided simulations shows that the proposed multilayered network concept is able to perform better than traditional WSN network in term of delivery time, average number of hops and data rate speed, when disruption scenario occurs. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
A New Bit Repair Fast Reroute Mechanism for Smart Sensors IoT Network Infrastructure
Sensors 2020, 20(18), 5230; https://doi.org/10.3390/s20185230 - 14 Sep 2020
Cited by 1 | Viewed by 618
Abstract
Today’s IP networks are experiencing a high increase in used and connected Internet of Things (IoT) devices and related deployed critical services. This puts increased demands on the reliability of underlayer transport networks. Therefore, modern networks must meet specific qualitative and quantitative parameters [...] Read more.
Today’s IP networks are experiencing a high increase in used and connected Internet of Things (IoT) devices and related deployed critical services. This puts increased demands on the reliability of underlayer transport networks. Therefore, modern networks must meet specific qualitative and quantitative parameters to satisfy customer service demands in line with the most common requirements of network fault tolerance and minimal packet loss. After a router or link failure within the transport network, the network convergence process begins. This process can take an unpredictable amount of time, usually depending on the size, the design of the network and the routing protocol used. Several solutions have been developed to address these issues, where one of which is the group of so-called Fast ReRoute (FRR) mechanisms. A general feature of these mechanisms is the fact that the resilience to network connectivity failures is addressed by calculating a pre-prepared alternative path. The path serves as a backup in the event of a network failure. This paper presents a new Bit Repair (B-REP) FRR mechanism that uses a special BIER header field (Bit-String) to explicitly indicate an alternative path used to route the packet. B-REP calculates an alternative path in advance as a majority of existing FRR solutions. The advantage of B-REP is the ability to define an alternative hop-by-hop path with full repair coverage throughout the network, where, unlike other solutions, we propose the use of a standardized solution for this purpose. The area of the B-REP application is communication networks working on the principle of packet switching, which use some link-state routing protocol. Therefore, B-REP can be successfully used in the IoT solutions especially in the field of ensuring communication from sensors in order to guarantee a minimum packet loss during data transmission. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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Open AccessArticle
Enhanced Multicast Repair Fast Reroute Mechanism for Smart Sensors IoT and Network Infrastructure
Sensors 2020, 20(12), 3428; https://doi.org/10.3390/s20123428 - 17 Jun 2020
Cited by 4 | Viewed by 996
Abstract
The sprawling nature of Internet of Things (IoT) sensors require the comprehensive management and reliability of the entire network. Modern Internet Protocol (IP) networks demand specific qualitative and quantitative parameters that need to be met. One of these requirements is the minimal packet [...] Read more.
The sprawling nature of Internet of Things (IoT) sensors require the comprehensive management and reliability of the entire network. Modern Internet Protocol (IP) networks demand specific qualitative and quantitative parameters that need to be met. One of these requirements is the minimal packet loss in the network. After a node or link failure within the network, the process of network convergence will begin. This process may take an unpredictable time, mostly depending on the size and the structure of the affected network segment and the routing protocol used within the network. The categories of proposed solutions for these problems are known as Fast ReRoute (FRR) mechanisms. The majority of current Fast ReRoute mechanisms use precomputation of alternative backup paths in advance. This paper presents an Enhanced Multicast Repair (EM-REP) FRR mechanism that uses multicast technology to create an alternate backup path and does not require pre-calculation. This principle creates a unique reactive behavior in the Fast ReRoute area. The enhanced M-REP FRR mechanism can find an alternative path in the event of multiple links or nodes failing at different times and places in the network. This unique behavior can be applied in the IoT sensors area, especially in network architecture that guarantees reliability of data transfer. Full article
(This article belongs to the Special Issue Smart Sensor Technologies for IoT)
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