Papers by Kiran Kumar Gopathoti
This study explores the integration of logistic regression with Internet of Things (IoT) technolo... more This study explores the integration of logistic regression with Internet of Things (IoT) technology to optimize water management in agriculture. Efficient irrigation systems are vital for boosting crop yields while preserving water resources, which is becoming more important due to the growing demand for food and the challenges caused by climate change. The suggested method makes use of Internet of Things (IoT) sensors to gather weather predictions, soil moisture levels, humidity, and temperature readings in real time. In order to determine how much water crops will use, this data is utilized to train a logistic regression model. Supervised learning is made possible by generating labelled data through the analysis of expert knowledge and past irrigation practices. The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score. Once validated, the logistic regression model is deployed within the IoT system to provide real-time predictions of crop water requirements. Through automation and data-driven decisionmaking, farmers can optimize irrigation schedules, minimize water wastage, and enhance crop productivity.
International Journal of Scientific Methods in Intelligence Engineering Networks
Agriculture and related industries employ approximately seventieth of India’s labour force, while... more Agriculture and related industries employ approximately seventieth of India’s labour force, while agriculture contributes approximately seventeen percent of India’s gross domestic product (GDP). In addition to the production of food, revenue, and jobs, the agricultural sector is responsible for the production of a diverse range of other goods and services. In addition to the provision of necessary primary resources, this is another purpose served by it. However, many of the practices that are used in current crop farming can trace their roots back several hundred years earlier. When trying to forecast which crops will flourish in different climates, Indian farmers still have a difficult time because there is not enough information available. The purpose of this research is to provide a summary of the numerous and varied strategies that AI has been suggested using to boost agricultural production in various regions of the world. The overall notion that directs the use of these strate...
International Journal of Scientific Methods in Engineering and Management
Nowadays, power consumption is one of the primary considerations in the design of VLSI (Very Larg... more Nowadays, power consumption is one of the primary considerations in the design of VLSI (Very Large Scale Integration) circuits based on complementary metal oxide semiconductors (CMOS) and carbon nanotube field effect transistors (CNTFET). This is because of the present circumstance. The fundamental reason for this is that power utilisation has been raised to the status of a top priority due to the improvements in integration and scaling as well as the constant increases in operating frequency. Additional power consumption from circuits and designs makes them challenging to implement in portable devices. The quantity of power lost during operation has an immediate effect on the cost of packaging the IC and systems. A variety of power dissipation sources and low power VLSI design strategies for CMOS and CNTFET-based circuits are discussed in this article.
Zenodo (CERN European Organization for Nuclear Research), Dec 23, 2022
In this paper, we propose a technique for weighted test sequence generation for synchronous seque... more In this paper, we propose a technique for weighted test sequence generation for synchronous sequential circuit's on-chip. Three weights-0, 0.5, and 1-are adequate for combinational circuits to completely cover stuck-at failures because they can accurately duplicate any given test pattern. We define the weights for sequential circuits based on subsequences of a deterministic test sequence. These weights enable us to partially replicate the test sequence and assure that the resulting weighted test sequences would receive full fault coverage. This accumulator-based 3-weight test pattern generating system is demonstrated and more effectively addresses the fundamental shortcomings of the suggested scheme. Compared to traditional techniques of creating test sequences for complicated large-scale systems, the weighted random test pattern generation represents a major improvement.
International Journal of Scientific Methods in Intelligence Engineering Networks
Diabetes Retinopathy(DR) occurs due to an injury to the retina, ultimately steering towards sight... more Diabetes Retinopathy(DR) occurs due to an injury to the retina, ultimately steering towards sightlessness. DR does not provide any early clues or signs and unnoticeably associates a new blood vessel towards the back portion of the eye, resulting in clots of blood in the eye, bleeding of eyes and distorted vision. The conventional methods are failed to produce the maximum classification accuracy. Therefore, this article is focused on implementation of hybrid logistic regression (HLR)-based machine learning model for classification of DR.Initially, histogram equalization is used to enhance the region of DR image. Then, segmentation of microaneurysmsis performed by using image morphological operations. Further, features extracted using gray level co-occurrence matrix (GLCM), which shows the internal relationship of DR disease. Then, selection of features is carried out using the Gaussian Mixture Model (GMM). Finally, HLR model is applied to perform the multi class classification operat...
International Journal of Scientific Methods in Engineering and Management, 2023
Recently, digital circuitry has demanded a decrease in space and power by decreasing time while s... more Recently, digital circuitry has demanded a decrease in space and power by decreasing time while simultaneously improving performance in speed. This has resulted in a need for more efficient use of the available space. Adders are fundamental components that are used in the construction of digital circuits. As a consequence of this, the performance of adders has to be improved in order to enhance the performance of integrated circuits that are used in the real world. The creation of a novel parallel prefix adder (PPA) architecture known as Hybrid PPA is the primary topic of this article. Hybrid PPA makes use of full carrier generation (FCG), full sum generation (FSG), half carry generation (HCG), and half sum generation (HSG) blocks. In addition to this, the N-bit Hybrid-PPA is constructed with features that may be reconfigured, and these features utilise square root additions through modified sum carry selection (MSCS). In addition, the implementation of multiplexer switching logic, which selects the whole sum bits and carry bits in a high-speed manner, reduces the amount of propagation time necessary for the generation of the sum and carry output. The results of the simulation show that using the proposed Hybrid PPA results in a reduction in area, latency, and power consumption when compared to using basic adders or approaches that are considered to be state of the art.
International Journal of Recent Technology and Engineering (IJRTE), 2019
The object of this paper is to detect faces in noisy images. All sample images show homogeneous b... more The object of this paper is to detect faces in noisy images. All sample images show homogeneous background faces. The transformation of the Hit-Miss is used to detect object boundaries and remove the noise effect. Two filters are cascaded to handle high noise levels in a special way. An application for face detection in noisy conditions is presented. The algorithm is implemented on faces taken from the Manchester face database after adding Gaussian noise to them.
FPGA Implementation of Arbiter PUFs for ideal Cryptographic Key Generation
2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2021
It is critical in today's security-conscious environments and communications to create unique... more It is critical in today's security-conscious environments and communications to create unique identities, and this can be done with software or hardware. Hardware can create a reliable and unique identity with less complexity than software because software requires more complex algorithms to keep the secret hidden from the adversaries. PUF is the name of one such basic circuit. Even when made using a nominally identical process, no two physical objects are exactly the same. When presented with a binary input, a PUF circuit responds with a binary, device-unique output. A PUF circuit is designed to be sensitive to manufacturing process variations. PUF as a hardware primitive is used as an authentication device in the real-world practical application scheme. The proposed IoT node-to-node mutual authentication algorithm does not require a server or a trusted third party. FPGA boards are used to implement the algorithm's main modules, such as the Nonce generation logic and the un...
In this paper, we developed Approximation layers based Weighted Average Image Fusion using Guided... more In this paper, we developed Approximation layers based Weighted Average Image Fusion using Guided Filter for Medical images. The proposed algorithm is very efficient and requires less computational time. Medical image fusion is a technique for clinical imaging analysis that is rapidly emerging as a research area present day. It helps in identifying abnormalities. Medical Imaging technique provides visual images of the interior body’s targeted organ (or) tissues in which we collect all the necessary information (or) complementary information based on the application. All the required information from the opted imaging modalities has to be combined to form a single output image. So here the challenge is to combine all the required information of opted image modalities to take accurate decisions clinically. Therefore, we proposed a Multi-modal fusion algorithm for medical images shown remarkable attainment in enhancing accurate decisions in medical images clinically. In comparison with...
Device-to-device verbal exchange is a beginning process that might cut down software transmission... more Device-to-device verbal exchange is a beginning process that might cut down software transmission force and enhance mobile advantage, which allows for coordinate verbal alternate amongst two mobile contraptions. Measure of little packets would in addition alternate between gadgets in burst mode transmission with the challenge of low overhead and espresso many-sided significant for vigor inexperienced coping with. Regularly the most certain troubles for out-bands D2D communications is bundle based synchronization. Keeping in ideas the quit intent to associate a couple of devices into the team, ongoing usefulness want to be completed, along these traces, the neighborhood segments ought to be synchronized involving every character-of-astyle. A synchronization method comprising of fairly a form of conventions and algorithms have got to be integrated into the framework all collectively accomplish non-avoid functionalities, inconsequential put off, and immoderate records fee. In preservin...
To prevent the large amount of noise and stay at the clear cut edges of the image in the smaller ... more To prevent the large amount of noise and stay at the clear cut edges of the image in the smaller lighting condition, we will invented a new denoising model based on the combination of total variation(TV) and non local comparison in the wavelet domain. TV denoising is an effective filtering method for recovering piecewise-constant signals. Denoising by minimizing the total variation yet staying close to the image. Reduces the oscillatory part of the signal that contains mostly noise (but also texture and some small details). The non local similarity is used for the noise reduction. The proposed denoising model can remove the large amount of noise very effectively and preserve the details of images than several up to date methods.Finally the performance of the system proposed is enhanced with the help of contourlet transform. PSNR performance will show us that proposed contourlet method will give better results.
Multi-Input and Multi output-OFDM system which is the merging of two systems, MIMO and OFDM, have... more Multi-Input and Multi output-OFDM system which is the merging of two systems, MIMO and OFDM, have more data transmission rate with huge diversity. STBC with MIMOOFDM has a better performance against the multipath interference including destructive interference which causes fading with less Bit Error rate, coding complexity and more SNR ratio. Created and analyzed a digital prototype of a physical model for estimating the performance of the MIMOOFDM system with STBC. The analysis carried out here shows that the MIMO-OFDM system along with STBC has better Signal to Noise Power Ratio with less BER than the Non-STBC MIMO-OFDM system.
International Journal of Engineering & Technology, Aug 15, 2018
This work gives a survey by comparing the different methods of image denoising with the help of w... more This work gives a survey by comparing the different methods of image denoising with the help of wavelet transforms and Convolutional Neural Network. To get the better method for Image denoising, there is distinctive merging which have been used. The vital role of communication is transmitting visual information in the appearance of digital images, but on the receiver side we will get the image with corruption. Therefore, in practical analysis and facts, the powerful image denoising approach is still a legitimate undertaking. The algorithms which are very beneficial for processing the signal like compression of image and denoising the image is Wavelet transforms. To get a better quality image as output, denoising methods includes the maneuver of data of that image. The primary aim is wavelet coefficient modification inside the new basis, by that the noise within the image data can be eliminated. In this paper, we suggested different methods of image denoising from the corrupted images with the help of different noises like Gaussian and speckle noises. This paper implemented by using adaptive wavelet threshold(Sure Shrink, Block Shrink, Neigh Shrink and Bivariate Shrink) and Convolutional Neural Network(CNN) Model, the experimental consequences the comparative accuracy of our proposed work.
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Papers by Kiran Kumar Gopathoti