Read Range Optimization of Low Frequency RFID System in Hostile Environmental Conditions by Using RSM Approach

Abstract

RFID system plays a major role in asset tracking but its performance may get challenged when it has to work in extreme atmospheric conditions. RFID system can play an important role in military or defense purpose to track the land mines, military containers etc. Keeping these things in mind, this research work was carried out for the military areas which are situated in arid and semiarid regions. In this research work, experimental investigation, statistical analysis and optimization of the low frequency RFID system read range has been carried out with respect to four major input parameters i.e. varying sandy soil grain sizes (0.45 mm, 0.78 mm, 1.18 mm, 1.6 mm and 2 mm) which is present in between RFID reader and tag, temperature (15 °C to 50 °C), humidity (35 %RH to 70 %RH) and sandy soil layer thickness (0 mm to 90 mm). Here the optimization is being done by using response surface methodology (RSM). From the investigations and optimization it was found that maximum value of read range which the LF RFID system can attain is 118.14 mm for the optimum combination of input variables i.e. temperature, soil layer thickness, relative humidity and soil grain size were found to be 25.606 °C, 0 mm, 35 % and 2 mm respectively.

DDNet- A Deep Learning Approach to Detect Driver Distraction and Drowsiness

“…The study was conducted for the safety of highway maintenance personnel in order to prevent mishaps or a hazard in the direct emergency lane of the highway by implementing a danger sensor device known as the Signal Warning Detector (SWAD) was used by Hassan, Suhaimi, et al 30) . Although RFID systems play an important role in asset tracking, their performance may be hampered when they are required to work in adverse weather conditions Choudhary, Shilpa, et al 31) . To determine system parameters for simulation purpose, time series based on neural networks was used by Dief, Tarek N., and Shigeo Yoshida 32) .…”

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“…In the result they found that temperature is inversely proportional to the signal strength, atmospheric pressure has a negative impact on the signal and also as there is an increase in the humidity it leads to the decrease of signal strength for a network propagation shows long distance co-channel interference as there is a change in weather condition [25]. Choudhary et al [26,27] in their work they optimized the output parameters using response surface methodology and error between the experimental and optimized results were found to be within 5%. Apart from this, RSM is a commonly used technique to solve many industrial challenges.…”

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“…Ryan Imansyah 23) studied Impact of Internet Penetration for different wireless communication technologies on the economic growth of Indonesia. Dwivedi et al 24) , Sharma et al 25) and Choudhary et al 26) suggested that RSM technology can be used as a multi-objective optimization tool. Karthik Vasudeva et al 27) investigated the V2I connectivity performance of LTE deployments in rural, semi-urban and urban scenarios using extensive drive-test measurement campaign.…”