Environmental Monitoring with Distributed Mesh Networks: An Overview and Practical Implementation Perspective for Urban Scenario

Ometov, Aleksandr; Bezzateev, Sergey; Voloshina, Natalia; Mašek, Pavel; Komarov, Mikhail

doi:10.3390/s19245548

Cited by 10 publications

(12 citation statements)

References 59 publications

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“…The dramatically booming requirement of wireless sensor networks (WSN) demand more sensor nodes with sensing ability for different applications, such as ecological monitoring, health surveillance, and traffic control [ 1 , 2 , 3 , 4 ]. To ensure the stability of a reception link from plenty of the sensor nodes, high-performance antennas with high gains, orthogonal polarizations, and omnidirectional coverage are required in sink nodes.…”

Section: Introductionmentioning

confidence: 99%

High-Gain Omnidirectional Dual-Polarized Antenna for Sink Nodes in Wireless Sensor Networks

Zhang

2022

Sensors

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In wireless sensor networks (WSN), a sink node receives signals from a large number of sensor nodes. Hence, the sink nodes are required to integrate compact antennas with high performances, such as high gain, dual polarizations, and omnidirectional radiation. In this paper, a high-gain omnidirectional dual-polarized (HGODP) antenna with a slot-cavity structure is proposed for WSN. The proposed antenna integrates dual omnidirectional antennas with orthogonal polarizations, i.e., a thin open-ended cavity for horizontal polarization and four folded slots for vertical polarization. Due to the orthogonal operating modes of the dual polarizations, the antenna configuration is constructed within a compact volume, but with an independent design. A prototype of the proposed antenna is fabricated and measured within a ruler-like profile. The experimental results show that the realized gains are higher than 6.5 dBi and are achieved for both dual polarizations in 2.37~2.54 GHz. With the merits of high gain, high isolation, and omnidirectional radiation, the proposed compact antenna exhibits promising usage for sink nodes in WSN.

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Section: Introductionmentioning

confidence: 99%

High-Gain Omnidirectional Dual-Polarized Antenna for Sink Nodes in Wireless Sensor Networks

Zhang

2022

Sensors

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“…These techniques can be very accurate but require the use of bulky, power-hungry, and expensive instruments [ 19 , 20 ]. Thus, these approaches do not provide a scalable solution for monitoring with enough spatial resolution air pollution events related to automotive combustion or burning fuels for cooking in urban scenarios [ 20 , 21 , 22 , 23 ]. Furthermore, these technologies demand trained personnel to operate with complex equipment and, obviously, they cannot be implemented in portable, low-cost, and low-power devices.…”

Section: Introductionmentioning

confidence: 99%

“…In the last few years, several authors have reported the use of Wireless Sensor Networks (WSNs) for air quality monitoring systems [ 20 , 22 ]. In that sense, some decision-making systems have been designed using both Local Area Networks (LANs) for the monitoring of local air quality or generating an alarm while under a gas pollution event [ 35 , 36 ] and Wide Area Networks (WANs) for remote control and monitoring [ 37 , 38 , 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…In that sense, some decision-making systems have been designed using both Local Area Networks (LANs) for the monitoring of local air quality or generating an alarm while under a gas pollution event [ 35 , 36 ] and Wide Area Networks (WANs) for remote control and monitoring [ 37 , 38 , 39 ]. Many WSNs have been deployed to cover a broad range of applications such as precision agriculture [ 40 , 41 , 42 ], healthcare [ 43 , 44 , 45 ], military industry [ 46 , 47 , 48 ], and air quality monitoring [ 22 , 24 , 25 ]. The application fields for WSNs are becoming wider every day.…”

Section: Introductionmentioning

confidence: 99%

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LoRa Sensor Network Development for Air Quality Monitoring or Detecting Gas Leakage Events

González

Casanova-Cháfer

Romero

et al. 2020

Sensors

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During the few last years, indoor and outdoor Air Quality Monitoring (AQM) has gained a lot of interest among the scientific community due to its direct relation with human health. The Internet of Things (IoT) and, especially, Wireless Sensor Networks (WSN) have given rise to the development of wireless AQM portable systems. This paper presents the development of a LoRa (short for long-range) based sensor network for AQM and gas leakage events detection. The combination of both a commercial gas sensor and a resistance measurement channel for graphene chemoresistive sensors allows both the calculation of an Air Quality Index based on the concentration of reducing species such as volatile organic compounds (VOCs) and CO, and it also makes possible the detection of NO2, which is an important air pollutant. The graphene sensor tested with the LoRa nodes developed allows the detection of NO2 pollution in just 5 min as well as enables monitoring sudden changes in the background level of this pollutant in the atmosphere. The capability of the system of detecting both reducing and oxidizing pollutant agents, alongside its low-cost, low-power, and real-time monitoring features, makes this a solution suitable to be used in wireless AQM and early warning systems.

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“…In IIoT, a large number of sensors are used to periodically detect changes in machine health, manufacturing process, industrial environment, etc. [5][6][7][8][9][10]. Hence, a huge amount of data is collected from the sensors used in IIoT.…”

Section: Introductionmentioning

confidence: 99%

Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things

Kwon

Kim

2020

Symmetry

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This paper presents a failure prediction model using iterative feature selection, which aims to accurately predict the failure occurrences in industrial Internet of Things (IIoT) environments. In general, vast amounts of data are collected from various sensors in an IIoT environment, and they are analyzed to prevent failures by predicting their occurrence. However, the collected data may include data irrelevant to failures and thereby decrease the prediction accuracy. To address this problem, we propose a failure prediction model using iterative feature selection. To build the model, the relevancy between each feature (i.e., each sensor) and the failure was analyzed using the random forest algorithm, to obtain the importance of the features. Then, feature selection and model building were conducted iteratively. In each iteration, a new feature was selected considering the importance and added to the selected feature set. The failure prediction model was built for each iteration via the support vector machine (SVM). Finally, the failure prediction model having the highest prediction accuracy was selected. The experimental implementation was conducted using open-source R. The results showed that the proposed failure prediction model achieved high prediction accuracy.

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Environmental Monitoring with Distributed Mesh Networks: An Overview and Practical Implementation Perspective for Urban Scenario

Cited by 10 publications

References 59 publications

High-Gain Omnidirectional Dual-Polarized Antenna for Sink Nodes in Wireless Sensor Networks

High-Gain Omnidirectional Dual-Polarized Antenna for Sink Nodes in Wireless Sensor Networks

LoRa Sensor Network Development for Air Quality Monitoring or Detecting Gas Leakage Events

Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things

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