Overhead Interspersing of Redundancy Bits Reduction Algorithm by Enhanced Error Detection Correction Code

Tolentino, Lean Karlo S.; Valenzuela, Ira C.; Juan, Ronnie O. Serfa

doi:10.25103/jestr.122.05

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…Work [6] continued the study of codes that have the properties of detecting and correcting errors. An algorithm for reducing the number of redundant bits when constructing an extended error detection and correction code is proposed.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

Sokolovskyi,

Zharikov,

Telenyk

2024

EEJET

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The object of the study is the IOT system for monitoring the state of objects. The problem being solved is the development of an innovative method of detecting and correcting data transmission errors in the networks of Internet of Things systems. The essence of the results is that a method of detecting and correcting multiple transmission errors during byte-by-byte transmission of a block of information has been developed. The method is distinguished by an original coding scheme, which involves the calculation of control bits, as well as the shuffling of block bits by performing bit shift operations. The peculiarity of the method is that any bit can be distorted when transmitting a code word, but it belongs to different code combinations of the Hamming code. This allows multiple data transmission errors to be detected and corrected during decoding, and multiple errors of different bytes belonging to the same block can be corrected. Simple algorithms for encoding and decoding procedures have been developed, and programs for information block encoding procedures and decoding procedures with error detection and correction have been developed. A software model of the data transmission channel was also developed with the possibility of introducing multiple errors when simulating the data transmission process. All programs are developed in Python, although other languages are possible. An experiment was conducted using the developed software model of the data transmission channel. The efficiency of the developed method has been experimentally confirmed and it has been proven that its use increases the immunity of the data transmission channel. This is due to the fact that the developed method allows detecting and correcting all code word transmission errors with a multiplicity from 1 to 8, which was confirmed experimentally. The main field of use of the developed method is considered to be IoT system networks. First of all, systems for monitoring the state of objects

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

Sokolovskyi,

Zharikov,

Telenyk

2024

EEJET

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“…Renewable energy aims to be a reliable power supply, offering fuel diversification, maintaining energy security, minimizing the risk of fuel spills, and lowering the demand for imported fuels. Nowadays, there are numerous domains of application that utilize renewable energy sources, such as medical [1], driverless cars [2], and wireless wearables [3]. As a renewable energy source, solar energy produces solar power, converted into electricity-i.e., solar cells, also called photovoltaic cells that convert sunlight into electricity [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

et al. 2021

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Infrared thermography is the science of measuring the infrared energy emitted by an object, translating it to apparent temperature variance, and displaying the result as an infrared image. Significantly, acquiring thermal images delivers distinctive levels of temperature differences in solar panels that correspond to their health status, which is beneficial for the early detection of defects. The proposed algorithm aims to analyze the thermal solar panel images. The acquired thermal solar panel images were segmented into solar cell sizes to provide more detailed information by region or cell area instead of the entire solar panel. This paper uses both the image histogram information and its corresponding cumulative distribution function (CDF), useful for image analysis. The acquired thermal solar panel images are enhanced using grayscale, histogram equalization, and adaptive histogram equalization to represent a domain that is easier to analyze. The experimental results reveal that the extraction results of thermal images provide better histogram and CDF features. Furthermore, the proposed scheme includes the convolutional neural network (CNN) for classifying the enhanced images, which shows that a 97% accuracy of classification was achieved. The proposed scheme could promote different thermal image applications—for example, non-physical visual recognition and fault detection analysis.

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A 100-MHz 3.352-mW 8-bit shift register using low-power DETFF using 90-nm CMOS process

Wang

Tolentino

Ekkurthi

et al. 2022

International Journal of Electronics Letters

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Overhead Interspersing of Redundancy Bits Reduction Algorithm by Enhanced Error Detection Correction Code

Cited by 6 publications

References 14 publications

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

Importance of Image Enhancement and CDF for Fault Assessment of Photovoltaic Module Using IR Thermal Image

A 100-MHz 3.352-mW 8-bit shift register using low-power DETFF using 90-nm CMOS process

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