Realistic propagation effects on wireless sensor networks for landslide management

Shutimarrungson, Nattakarn; Wuttidittachotti, Pongpisit

doi:10.1186/s13638-019-1412-6

Cited by 11 publications

(9 citation statements)

References 21 publications

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“…When you must check the actual system performance in a series of ways using different parameters and are cost-effective and hardworking the process of simulation will be followed. Simulations are the replications of realism for exploring the model, it offers to arrange and format the algorithm properties (Shutimarrungson & Wuttidittachotti, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…According to researchers in (Shutimarrungson & Wuttidittachotti, 2019) investigated the result of two non-fading models of propagation named free space and two ray ground model, by the key features and outcomes of the ad-hoc routing schemes like DSR, AODV and Location-Aware Routing scheme in terms of average throughput, delay, and routing overhead. The authors observed that the act and efficiency of the LAR1 routing protocol is top, and the performance of DSR protocol is worst as radio verity increase.…”

Section: Related Literaturementioning

confidence: 99%

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Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets

Hussain

Ali

et al. 2020

ADCAIJ

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Mobile Ad-hoc Network (MANET) is the most emerging and fast-expanding technology in the last two decades. One of the major issues and challenging areas in MANET is the process of routing due to dynamic topologies and high mobility of mobile nodes. The efficiency and accuracy of a protocol depend on many parameters in these networks. In addition to other parameters node velocity and propagation models are among them. Calculating signal strength at the receiver is the responsibility of a propagation model while the mobility of nodes is responsible for the topology of the network. A huge amount of loss in performance is occurred due to the variation of signal strength at the receiver and obstacles between transmissions. In this paper,it has been analyzed to check the impact of different propagation models on the performance of Optimized Link State Routing (OLSR) in Sparse and Dense scenarios in MANET. The simulation has been carried out in NS-2 by using performance metrics as average packet drop average latency and average Throughput. The results predicted that propagation models and mobility have a strong impact on the performance of OLSR in considered scenarios.

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Section: Methodsmentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets

Hussain

Ali

et al. 2020

ADCAIJ

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“…30 Experimental studies have shown that in areas with multipath loss, path loss includes log-normal distribution and shadowing effects. 9…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…These are generally animal behavior monitoring, industrial detection, health monitoring, consumption, and military applications. [1][2][3][4][5][6][7][8][9][10][11] Besides these applications, this technology is also commonly used for precision agriculture applications in the various vegetation environments such as fruit orchard. [5][6][7] The usage of wireless sensor networks (WSN) has become significant with the aim of monitoring and management, especially in vegetative environments.…”

Section: Introductionmentioning

confidence: 99%

A new empirical propagation model depending on volumetric density in citrus orchards for wireless sensor network applications at sub‐6 GHz frequency region

Doğan¹

2021

Int J RF Microw Comput Aided Eng

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The accuracy of the path loss models directly affects the performance of the wireless sensor networks (WSN) and the efficiency of coverage planning. In this article, as a novelty, new empirical path loss models with foliage depth are proposed at two different 5G frequencies (3.5 and 4.2 GHz) based on volumetric density rate (v) of the trees in citrus orchards for WSN. In order to generate/verify empirical models, measurements are performed at different locations with similar environment characteristics. First, the measurements are compared with commonly used empirical models such as LITU-R, FITU-R, Cost 235, and log-normal, and they are found to be compatible with these models. Second, empirical path loss model is generated based on these measurements. Accordingly, for 3.5 and 4.2 GHz, the coefficient of determination (R 2 ) values are 0.966 and 0.965, respectively. Thirdly, based on the proposed model, it is determined that increasing the v value by 30% increased path loss by 20 dB. Finally, the performance of the proposed models is compared with four different empiric models for calculated v as 0.571. Additionally, the 3.08 and 3.46 root mean square error values of the proposed models are considerably better than those of other models.

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“…Some studies measure the size of foliage depth and create a model with location-based image processing [22]. In MED models such as Weissberger, ITU Recommendation (ITU-R), LITU-R, FITU-R, and COST235 [23][24][25][26][27][28][29], the path loss changes as an exponential function of frequency and distance. It should be noted that these five models are made in areas with foliage depths <1 km.…”

Section: Fundamentals Of Foliage Path Loss Modelsmentioning

confidence: 99%

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

Genç

2020

Int. J. Microw. Wireless Technol.

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In this paper, a new empirical path loss model based on frequency, distance, and volumetric occupancy rate is generated at the 3.5 and 4.2 GHz in the scope of 5G frequency bands. This study aims to determine the effect of the volumetric occupancy rate on path loss depending on the foliage density of the trees in the pine forest area. Using 4.2 GHz and the effect of the volumetric occupancy rate contributes to the literature in terms of novelty. Both the reference measurements to generate a model and verification measurements to verify the proposed models are conducted in three different regions of the forest area with double ridged horn antennas. These regions of the artificial forest area consist of regularly sorted and identical pine trees. Root mean square error (RMSE) and R-squared values are calculated to evaluate the performance of the proposed model. For 3.5 and 4.2 GHz, while the RMSEs are 3.983 and 3.883, the values of R-squared are 0.967 and 0.963, respectively. Additionally, the results are compared with four path loss models which are commonly used in the forest area. The proposed one has the best performance among the other models with values 3.98 and 3.88 dB for 3.5 and 4.2 GHz.

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Realistic propagation effects on wireless sensor networks for landslide management

Cited by 11 publications

References 21 publications

Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets

Impact of Sparse and Dense Deployment of Nodes Under Different Propagation Models in Manets

A new empirical propagation model depending on volumetric density in citrus orchards for wireless sensor network applications at sub‐6 GHz frequency region

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

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