Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63559
Jitendra Kumar Gautam, Pankaj Verma
Abstract: One of the most appealing and economical uses of solar energy is drying agricultural goods. With differing degrees of technical performance, a multitude of solar dryer types have been devised and developed across the globe. In general, solar dryers come in four different varieties: (1) direct solar dryers, (2) indirect solar dryers, (3) mixed-mode dryers, and (4) hybrid solar dryers. The product being dried, as well as technical and financial concerns, are reviewed in this paper together with other solar dryer kinds. Technically speaking, integrated storage, high efficiency, compact collector design, and long-life drying systems are the main focuses in the development of solar-assisted drying systems for vegetables. There exist alternative systems to air-based solar collectors. By using a water-to-air heat exchanger, water-based collectors are another option. A water-to-air heat exchanger can be used to push hot air used for drying agricultural products to pass through it. As part of the solar drying system, the hot water tank stores heat
{"title":"Review Paper on Diffierent Types of Solar Dryer","authors":"Jitendra Kumar Gautam, Pankaj Verma","doi":"10.22214/ijraset.2024.63559","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63559","url":null,"abstract":"Abstract: One of the most appealing and economical uses of solar energy is drying agricultural goods. With differing degrees of technical performance, a multitude of solar dryer types have been devised and developed across the globe. In general, solar dryers come in four different varieties: (1) direct solar dryers, (2) indirect solar dryers, (3) mixed-mode dryers, and (4) hybrid solar dryers. The product being dried, as well as technical and financial concerns, are reviewed in this paper together with other solar dryer kinds. Technically speaking, integrated storage, high efficiency, compact collector design, and long-life drying systems are the main focuses in the development of solar-assisted drying systems for vegetables. There exist alternative systems to air-based solar collectors. By using a water-to-air heat exchanger, water-based collectors are another option. A water-to-air heat exchanger can be used to push hot air used for drying agricultural products to pass through it. As part of the solar drying system, the hot water tank stores heat","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"10 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63631
Harsh Kumar
Abstract: Ten years ago, there were barriers to ideal accuracy in many computer vision issues. But the emergence of deep learning techniques brought about a dramatic change that greatly improved the accuracy of these problems. Among these, image classification stands out as a key problem: it is the challenge of accurately classifying images into their corresponding classifications, such dogs and cats. This research aims to improve accuracy by utilizing state-of-the-art object detecting algorithms. In order to tackle this, a great deal of effort has gone into building a convolutional neural network (CNN) that is robust and designed with image categorization in mind. The principal goal is to leverage the capabilities of cutting-edge object identification techniques in order to achieve significant improvements in image classification accuracy.
{"title":"Image Categorization through Convolutional Neural Network","authors":"Harsh Kumar","doi":"10.22214/ijraset.2024.63631","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63631","url":null,"abstract":"Abstract: Ten years ago, there were barriers to ideal accuracy in many computer vision issues. But the emergence of deep learning techniques brought about a dramatic change that greatly improved the accuracy of these problems. Among these, image classification stands out as a key problem: it is the challenge of accurately classifying images into their corresponding classifications, such dogs and cats. This research aims to improve accuracy by utilizing state-of-the-art object detecting algorithms. In order to tackle this, a great deal of effort has gone into building a convolutional neural network (CNN) that is robust and designed with image categorization in mind. The principal goal is to leverage the capabilities of cutting-edge object identification techniques in order to achieve significant improvements in image classification accuracy.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"53 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63723
Vatam Teja
Abstract: In order to monitor the operating status of vehicles, it is necessary to collect vehicle operating data in real time through IoT devices and analyze these data. However, the collected data has the characteristics of multi-source heterogeneous, network resources are limited and server performance is poor. It is difficult to truly realize data processing in real time. In addition, data needs to be transmitted over the network, it is particularly important to ensure the safety of data transmission. Considering the above problems, it is necessary to structure the data and define a unified data format to facilitate data transmission and analysis. At the same time, improve the server communication program and improve the server's concurrent processing capabilities. In addition, considering that data needs to be transmitted over the network, in order to ensure that the data is not stolen or tampered with, the PRESENT lightweight encryption algorithm is adopted to ensure the safety of data transmission. Compared with encryption algorithms such as AES, this algorithm has much lower hardware requirements. This article combines the characteristics of the project and uses the number of communications between the device and the server to achieve the dynamic key update which is approximately one-time pad, and greatly improves the security of the data.
{"title":"A United Architecture For AES/Present Ciphers and Its Usage in a Soc Environment","authors":"Vatam Teja","doi":"10.22214/ijraset.2024.63723","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63723","url":null,"abstract":"Abstract: In order to monitor the operating status of vehicles, it is necessary to collect vehicle operating data in real time through IoT devices and analyze these data. However, the collected data has the characteristics of multi-source heterogeneous, network resources are limited and server performance is poor. It is difficult to truly realize data processing in real time. In addition, data needs to be transmitted over the network, it is particularly important to ensure the safety of data transmission. Considering the above problems, it is necessary to structure the data and define a unified data format to facilitate data transmission and analysis. At the same time, improve the server communication program and improve the server's concurrent processing capabilities. In addition, considering that data needs to be transmitted over the network, in order to ensure that the data is not stolen or tampered with, the PRESENT lightweight encryption algorithm is adopted to ensure the safety of data transmission. Compared with encryption algorithms such as AES, this algorithm has much lower hardware requirements. This article combines the characteristics of the project and uses the number of communications between the device and the server to achieve the dynamic key update which is approximately one-time pad, and greatly improves the security of the data.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"49 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63671
B. Pranesh, Dr G. Suresh Babu
Abstract: This research investigates the innovative use of Magnetic Resonance Coupling (MRC) in Electric Vehicle (EV) power transfer, focusing on its potential and challenges. Key objectives include understanding MRC's operational principles, optimizing efficiency, and tackling real-world EV charging issues. Essential components like coil design, resonance frequency tuning, and power control are covered, utilizing MATLAB and Simulink for performance simulation under various conditions. The impact of MRC on EV charging infrastructure is highlighted, emphasizing advancements in power transmission and efficiency. The findings promise to revolutionize EV charging, leading to more efficient, convenient, and sustainable power transfer methods.
{"title":"The Impact of Magnetic Resonance Coupling in Electric Vehicle Power Transfer Systems","authors":"B. Pranesh, Dr G. Suresh Babu","doi":"10.22214/ijraset.2024.63671","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63671","url":null,"abstract":"Abstract: This research investigates the innovative use of Magnetic Resonance Coupling (MRC) in Electric Vehicle (EV) power transfer, focusing on its potential and challenges. Key objectives include understanding MRC's operational principles, optimizing efficiency, and tackling real-world EV charging issues. Essential components like coil design, resonance frequency tuning, and power control are covered, utilizing MATLAB and Simulink for performance simulation under various conditions. The impact of MRC on EV charging infrastructure is highlighted, emphasizing advancements in power transmission and efficiency. The findings promise to revolutionize EV charging, leading to more efficient, convenient, and sustainable power transfer methods.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"41 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63734
K. P. Heena
Abstract: Advancements in Finite Impulse Response (FIR) filter design have significantly propelled the field of Digital Signal Processing (DSP), addressing the increasing need for high-performance and efficient digital filters. FIR filters are renowned for their stability, linear phase response, and computational efficiency, making them indispensable in applications such as image filtering and frequency modulation. Their inherent advantages, including the ability to leverage Fast Fourier Transformation (FFT) techniques and minimal finite precision arithmetic errors, often make them preferable over Infinite Impulse Response (IIR) filters. Recent research efforts have focused on algorithmic and hardware modifications to optimize FIR filter architectures, employing techniques such as retiming, pipelining, and parallel processing. This paper explores various design techniques and architectures aimed at optimizing FIR filter performance. Additionally, the role of high-speed adder structures, like carry-lookahead adders, is examined for their impact on enhancing digital filter efficiency and the critical role of continuous exploration and optimization in FIR filter design to advance DSP. By addressing the demands of modern technology, these innovations foster the development of high-performance, efficient digital filters, essential for diverse applications and the ongoing progression of digital signal processing.
摘要：有限脉冲响应（FIR）滤波器设计的进步极大地推动了数字信号处理（DSP）领域的发展，满足了人们对高性能、高效率数字滤波器日益增长的需求。FIR 滤波器以其稳定性、线性相位响应和计算效率而著称，在图像滤波和频率调制等应用中不可或缺。与无限脉冲响应（IIR）滤波器相比，FIR 滤波器具有固有的优势，包括能够利用快速傅立叶变换（FFT）技术和最小的有限精度算术误差。近期的研究工作主要集中在算法和硬件修改上，通过采用重定时、流水线和并行处理等技术来优化 FIR 滤波器架构。本文探讨了旨在优化 FIR 滤波器性能的各种设计技术和架构。此外，本文还探讨了高速加法器结构（如前导加法器）对提高数字滤波器效率的影响，以及在 FIR 滤波器设计中不断探索和优化对推动 DSP 发展的关键作用。通过满足现代技术的需求，这些创新促进了高性能、高效率数字滤波器的发展，这对各种应用和数字信号处理的不断进步至关重要。
{"title":"A Review of High Throughput FIR Filter Design","authors":"K. P. Heena","doi":"10.22214/ijraset.2024.63734","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63734","url":null,"abstract":"Abstract: Advancements in Finite Impulse Response (FIR) filter design have significantly propelled the field of Digital Signal Processing (DSP), addressing the increasing need for high-performance and efficient digital filters. FIR filters are renowned for their stability, linear phase response, and computational efficiency, making them indispensable in applications such as image filtering and frequency modulation. Their inherent advantages, including the ability to leverage Fast Fourier Transformation (FFT) techniques and minimal finite precision arithmetic errors, often make them preferable over Infinite Impulse Response (IIR) filters. Recent research efforts have focused on algorithmic and hardware modifications to optimize FIR filter architectures, employing techniques such as retiming, pipelining, and parallel processing. This paper explores various design techniques and architectures aimed at optimizing FIR filter performance. Additionally, the role of high-speed adder structures, like carry-lookahead adders, is examined for their impact on enhancing digital filter efficiency and the critical role of continuous exploration and optimization in FIR filter design to advance DSP. By addressing the demands of modern technology, these innovations foster the development of high-performance, efficient digital filters, essential for diverse applications and the ongoing progression of digital signal processing.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"30 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63575
Ramesh Chandra Vishwakarma
Abstract: Understanding the intricate interactions between plants, mycorrhizal fungi, and soil health is crucial for sustainable agriculture and climate change mitigation. This review synthesizes current research to elucidate the multifaceted role of plantmycorrhizal-fungal interactions in soil health and carbon sequestration in agroecosystems. A meta-analysis of 75 studies spanning diverse ecosystems and plant species reveals a significant positive correlation between mycorrhizal colonization and soil organic carbon content, with an average increase of 25% compared to non-mycorrhizal systems. Furthermore, mycorrhizal symbiosis enhances soil structure and aggregation, promoting water retention and nutrient cycling, which are essential for maintaining soil fertility and resilience to environmental stressors. The contributions of different mycorrhizal types (arbuscular, ectomycorrhizal, and ericoid) to soil carbon dynamics are also examined, highlighting their unique roles in carbon allocation and stabilization. Additionally, the review discusses the potential implications of plant-mycorrhizal-fungal interactions for mitigating greenhouse gas emissions through enhanced carbon sequestration in agricultural soils. Insights into the mechanisms underlying these interactions, including mycorrhizal-mediated changes in root exudates, microbial communities, and soil enzymatic activities, are discussed. Overall, this review underscores the importance of integrating mycorrhizal symbiosis into agroecosystem management practices to enhance soil health, carbon sequestration, and climate resilience.
{"title":"The Role of Plant-Mycorrhizal-Fungal Interactions in Soil Health and Carbon Sequestration in Agroecosystems","authors":"Ramesh Chandra Vishwakarma","doi":"10.22214/ijraset.2024.63575","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63575","url":null,"abstract":"Abstract: Understanding the intricate interactions between plants, mycorrhizal fungi, and soil health is crucial for sustainable agriculture and climate change mitigation. This review synthesizes current research to elucidate the multifaceted role of plantmycorrhizal-fungal interactions in soil health and carbon sequestration in agroecosystems. A meta-analysis of 75 studies spanning diverse ecosystems and plant species reveals a significant positive correlation between mycorrhizal colonization and soil organic carbon content, with an average increase of 25% compared to non-mycorrhizal systems. Furthermore, mycorrhizal symbiosis enhances soil structure and aggregation, promoting water retention and nutrient cycling, which are essential for maintaining soil fertility and resilience to environmental stressors. The contributions of different mycorrhizal types (arbuscular, ectomycorrhizal, and ericoid) to soil carbon dynamics are also examined, highlighting their unique roles in carbon allocation and stabilization. Additionally, the review discusses the potential implications of plant-mycorrhizal-fungal interactions for mitigating greenhouse gas emissions through enhanced carbon sequestration in agricultural soils. Insights into the mechanisms underlying these interactions, including mycorrhizal-mediated changes in root exudates, microbial communities, and soil enzymatic activities, are discussed. Overall, this review underscores the importance of integrating mycorrhizal symbiosis into agroecosystem management practices to enhance soil health, carbon sequestration, and climate resilience.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"17 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63625
Narla Sasikala
Abstract: In the context of a lack of fabric in concrete production, particularly in India where rapid infrastructure development has led to increased construction activities, the adoption of environmentally friendly practices is essential. India, renowned for its exceptional cement production worldwide, is now grappling with issues posed by the widespread Covid-19 pandemic, which is significantly disrupting the growth of the construction industry. This has led to neighbouring lockdowns and shortages in texture. The massive amounts of banana waste thrown out in India emit toxic quantities of carbon dioxide and methane gas into the atmosphere. Banana leaf ash may be produced after the bananas have been harvested. One possible use for the agriculture waste known as BANANA LEAF ASH (BLA) is to reduce the amount of cement needed to build concrete. E-GF stands for "ELECTRONIC-GLASS FIBER," which might refer to a material made up of many little glass filaments. In addition to increasing the material's flexural, ductile, and affect properties, these strands fulfil a function similar to the strengthening steel present in traditional reinforced concrete. This Paper talks about maintain the variable frequency to makeup BLA with cement 0%, 2.5%, 5%, 7.5%, 10% & 12.5% & EGF with constant frequency of 3%. Moreover the comparison is held with proxy blends like 0%BLA+0%EGF, 2.5%BLA+3%EGF, 5%BLA+3%EGF, 7.5%BLA+3%EGF, 10%BLA+3%EGF & 12.5%BLA+3%EGF. BANANA LEAF ASH and E-GLASS FIBER together provide a sustainable and strength-enhancing solution for concrete. Seeing how cutting-edge materials may revolutionize building methods is fascinating.
{"title":"Progression of M30 Strong on Banana Leaf Ash & E-Glass Fibre Infused in Cement","authors":"Narla Sasikala","doi":"10.22214/ijraset.2024.63625","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63625","url":null,"abstract":"Abstract: In the context of a lack of fabric in concrete production, particularly in India where rapid infrastructure development has led to increased construction activities, the adoption of environmentally friendly practices is essential. India, renowned for its exceptional cement production worldwide, is now grappling with issues posed by the widespread Covid-19 pandemic, which is significantly disrupting the growth of the construction industry. This has led to neighbouring lockdowns and shortages in texture. The massive amounts of banana waste thrown out in India emit toxic quantities of carbon dioxide and methane gas into the atmosphere. Banana leaf ash may be produced after the bananas have been harvested. One possible use for the agriculture waste known as BANANA LEAF ASH (BLA) is to reduce the amount of cement needed to build concrete. E-GF stands for \"ELECTRONIC-GLASS FIBER,\" which might refer to a material made up of many little glass filaments. In addition to increasing the material's flexural, ductile, and affect properties, these strands fulfil a function similar to the strengthening steel present in traditional reinforced concrete. This Paper talks about maintain the variable frequency to makeup BLA with cement 0%, 2.5%, 5%, 7.5%, 10% & 12.5% & EGF with constant frequency of 3%. Moreover the comparison is held with proxy blends like 0%BLA+0%EGF, 2.5%BLA+3%EGF, 5%BLA+3%EGF, 7.5%BLA+3%EGF, 10%BLA+3%EGF & 12.5%BLA+3%EGF. BANANA LEAF ASH and E-GLASS FIBER together provide a sustainable and strength-enhancing solution for concrete. Seeing how cutting-edge materials may revolutionize building methods is fascinating.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"17 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63609
Chinthalapati Meghana
Abstract: The occurrence of bacterial, viral, and fungal diseases on rice leaves significantly hampers rice production, posing a challenge to meet global demand for the staple crop. While the detection of rice leaf diseases is crucial, existing methods are constrained by limitations in image backgrounds and capture conditions. Convolutional Neural Network (CNN) models have emerged as a usefull avenue for disease recognition in rice leaves, yet current approaches suffer from decreased recognition rates when applied to independent datasets and are constrained by the need for large-scale network parameters. In this project, we propose an innovative CNN-based model aimed at mitigating these challenges by reducing network parameters. Through training multiple CNN- basedmodels to identify three common rice leaf diseases, our study aims to showcase the effectiveness and superiority of our approach compared to state-of-the-art CNN-based models for rice leaf disease recognition.
{"title":"Rice Leaf Disease Recognition using CNN","authors":"Chinthalapati Meghana","doi":"10.22214/ijraset.2024.63609","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63609","url":null,"abstract":"Abstract: The occurrence of bacterial, viral, and fungal diseases on rice leaves significantly hampers rice production, posing a challenge to meet global demand for the staple crop. While the detection of rice leaf diseases is crucial, existing methods are constrained by limitations in image backgrounds and capture conditions. Convolutional Neural Network (CNN) models have emerged as a usefull avenue for disease recognition in rice leaves, yet current approaches suffer from decreased recognition rates when applied to independent datasets and are constrained by the need for large-scale network parameters. In this project, we propose an innovative CNN-based model aimed at mitigating these challenges by reducing network parameters. Through training multiple CNN- basedmodels to identify three common rice leaf diseases, our study aims to showcase the effectiveness and superiority of our approach compared to state-of-the-art CNN-based models for rice leaf disease recognition.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"29 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63551
Kajal Saran Pradhan
Abstract: The integration of machine learning (ML) into Indian agriculture holds transformative potential for addressing critical challenges such as climate variability, water scarcity, soil degradation, and market fluctuations. This paper explores the current state of ML applications in Indian agriculture, highlighting successful case studies and initiatives led by government, private sector, and academic institutions. It discusses the technological integration of ML with the Internet of Things (IoT), remote sensing, and blockchain to enhance precision farming practices. Key barriers to widespread adoption, including data quality, infrastructure, and farmer awareness, are identified, along with strategies to overcome them. Future directions emphasize the importance of robust data infrastructure, localized ML models, collaborative research, sustainable practices, and supportive policy frameworks. By leveraging ML, Indian agriculture can achieve significant improvements in productivity, sustainability, and profitability.
摘要：将机器学习（ML）融入印度农业具有变革潜力，可解决气候多变性、水资源短缺、土壤退化和市场波动等严峻挑战。本文探讨了 ML 在印度农业中的应用现状，重点介绍了由政府、私营部门和学术机构主导的成功案例研究和倡议。它讨论了将 ML 与物联网 (IoT)、遥感和区块链进行技术整合，以加强精准农业实践的问题。报告指出了广泛采用的主要障碍，包括数据质量、基础设施和农民意识，以及克服这些障碍的策略。未来的发展方向强调了强大的数据基础设施、本地化的 ML 模型、合作研究、可持续的实践和支持性政策框架的重要性。通过利用 ML，印度农业可以在生产率、可持续性和盈利能力方面实现显著改善。
{"title":"Intelligent Farming Systems in Future Using Machine Learning: A Focus on India","authors":"Kajal Saran Pradhan","doi":"10.22214/ijraset.2024.63551","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63551","url":null,"abstract":"Abstract: The integration of machine learning (ML) into Indian agriculture holds transformative potential for addressing critical challenges such as climate variability, water scarcity, soil degradation, and market fluctuations. This paper explores the current state of ML applications in Indian agriculture, highlighting successful case studies and initiatives led by government, private sector, and academic institutions. It discusses the technological integration of ML with the Internet of Things (IoT), remote sensing, and blockchain to enhance precision farming practices. Key barriers to widespread adoption, including data quality, infrastructure, and farmer awareness, are identified, along with strategies to overcome them. Future directions emphasize the importance of robust data infrastructure, localized ML models, collaborative research, sustainable practices, and supportive policy frameworks. By leveraging ML, Indian agriculture can achieve significant improvements in productivity, sustainability, and profitability.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63604
J. Chaitanya, Sk. Sahera, Dr. K. Chandramouli, B.N L Srikanth
Abstract: This experimental investigation explores the impact of incorporating zeolite powder as a partial replacement for fine aggregate, along with silica fume and cashew nut shell ash (CNSA) as partial replacements for cement in concrete. Zeolite, a natural aluminosilicate mineral, is known for its pozzolanic properties, which can enhance the mechanical and durability characteristics of concrete. Silica fume, a byproduct of silicon and ferrosilicon alloy production, is renowned for its high silica content and fineness, contributing to the strength and density of concrete. Cashew nut shell ash, an agricultural waste product, offers a sustainable alternative to traditional cementitious materials, potentially reducing the environmental footprint of concrete production. This experimental study investigated the effects of partially replacing fine aggregate with zeolite powder (5%,10% and 15%) and cement with silica fume (3%,6%,9%,12% and 15%) and cashew nut shell ash (5%,7.5%,10%,12.5%,15% and 17.5%) on the properties of concrete. This study underscores the viability of using zeolite powder, silica fume, and CNSA in sustainable concrete production, contributing to the development of more environmentally friendly construction materials. Further research is recommended to explore the long-term performance and environmental benefits of these alternative materials in concrete applications.
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