Comparative Performance Analysis of Wireless RSSI in Wireless Sensor Networks Motes in Tropical Mixed-crop Precision Farm

Harun, A.; Ramli, Mohammad Fadzli; Kamarudin, Kamarulzaman; Ndzi, David; Shakaff, Ali Yeon Md; Zakaria, A.; Jaafar, Mohd Saleh

doi:10.1109/isms.2012.57

Cited by 19 publications

(8 citation statements)

References 14 publications

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“…The results obtained for RSSI and packet loss are similar in different distances ranging up to 500 m. However, beyond the 500 m, XBPS2 module provides an acceptable performance for packet transmission, similar to the results obtained by Harun et al 21 where an XBee Pro module is compared to other technologies and obtained the best performance. This clearly reflects the greater transmission power provided by this module.…”

Section: Resultssupporting

confidence: 85%

“…In the literature, 19,20 similar experiments were carried out using an analysis of propagation behavior of the RF signal (ZigBee for the second case) modules in a real environment through RSSI measurements at different distances. There are also studies on the use of WSN in the environment to improve the production of mixed crops with precision farming variables, 21,22 or systems for measuring climate variables such as temperature, humidity, rainfall, solar radiation, wind speed, and direction. 22,23 Materials and methods…”

Section: Similar Workmentioning

confidence: 99%

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Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

Cama-Pinto

Piñeres-Espitia

Caicedo-Ortiz

et al. 2017

International Journal of Distributed Sensor Networks

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Today, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with ''log-normal shadowing'' and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an ''Arduino Mega'' board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios.

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Section: Resultssupporting

confidence: 85%

Section: Similar Workmentioning

confidence: 99%

Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

Cama-Pinto

Piñeres-Espitia

Caicedo-Ortiz

et al. 2017

International Journal of Distributed Sensor Networks

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“…There is an extensive literature on path loss models for forests and agricultural environments. It is claimed that log-distance path loss model provides a good fit to the measured path loss in vegetated environments [16], [17], [18],…”

Section: B a Representative Path Loss Model For Orchard Environmentsmentioning

confidence: 99%

RSSI-Based Distributed Self-Localization for Wireless Sensor Networks Used in Precision Agriculture

Abouzar

Michelson

Hamdi

2016

IEEE Trans. Wireless Commun.

135

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Node localization algorithms that can be easily integrated into deployed wireless sensor networks (WSNs) and which run seamlessly with proprietary lower layer communication protocols running on off-the-shelf modules can help operators of large farms and orchards avoid the difficulty, cost and/or time involved with manual or satellite-based node localization techniques. Even though the state-of-the-art node localization algorithms can achieve low error rates using distributed techniques such as belief propagation (BP), they are not well suited to WSNs deployed for precision agriculture applications with large number of nodes, few number of landmarks and lack real time update capability. The algorithm proposed here is designed for applications such as pest control and irrigation in large farms and orchards where greater power efficiency and scalability are required but location accuracy requirements are less demanding. Our algorithm uses received signal strength indicator (RSSI) values to estimate the distribution of distance between nodes then updates the location probability mass function (pmf) of nodes in a distributed manner.At every time step, the most recently communicated path loss samples and location prior pmf received from neighbouring nodes is sufficient for nodes with unknown location to update their location pmf. This renders the algorithm recursive, hence results in lower computational complexity at each time step. We propose a particular realization of the method in which only one node multicasts at each time step and neighbouring nodes update their location pmf conditioned on all communicated samples over previous time steps. This is highly compatible with realistic WSN deployments, e.g., ZigBee which are based upon the ad hoc on-demand distance vector (AODV) where nodes flood route request (RREQ) and route reply (RREP) packets. Further, beacon signals transmitted during the network formation and routing table formulation stage can provide the RSSI information required by the localization algorithm. Index TermsWireless sensor networks, distributed localization, range-based localization algorithms, path loss measurements, information aggregation, precision agriculture September 9, 2015 DRAFT 2

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“…An experiment involving video streaming over a wireless channel in the presence of fading caused by the physical environment was also reported [23] [24]. The study records a very poorly received video quality when streaming video file wirelessly across an agricultural area [25]. Besides foliage and vegetation, weather condition can as well affect the wireless signal quality.…”

Section: Introductionmentioning

confidence: 95%

Measurements of Mobile Signal Received Power Level at Ringlet, Cameron Highland, Malaysia

Suliman

Hashim²,

Ismail

et al. 2018

IJET

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Tenaga Nasional, the electric utility company in Peninsular Malaysia have been installing electronic meters that can establish wireless connectivity over the mobile phone network since 2005. Several locations including Ringlet, Cameron Highland have been pointed out as having difficulties in establishing a stable connection to the national main server. Empirical investigations had been carried out to determine the availability of service coverage and the associated signal received power levels at the said location. The findings are reported in this article. The outcomes from the measurement campaign were used to deduce the likely solution that is capable of establishing a more reliable link. Field trials involving installations of high-gain antennas and signal boosters as potential solutions were also carried out at selected sites within the district. It is the objective of the study to develop a total solution that can ultimately address the communication issue.

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Comparative Performance Analysis of Wireless RSSI in Wireless Sensor Networks Motes in Tropical Mixed-crop Precision Farm

Cited by 19 publications

References 14 publications

Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

RSSI-Based Distributed Self-Localization for Wireless Sensor Networks Used in Precision Agriculture

Measurements of Mobile Signal Received Power Level at Ringlet, Cameron Highland, Malaysia

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