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Apple Leaf Disease Identification Using Resnet50

Apple Leaf Disease Identification Using Resnet50

2024 International Conference on Innovative Computing, Intelligent communication and Smart Electrical Systems, ICSES 2024

作者： Karthigaiveni, S. Archana, R. Ravi, Vasanth Khatoon, P Salma Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India St. Joseph's Institute of technology Department of Artificial intelligence and Data science OMR Chennai India Jain Deemed to be University Faculty of Engineering and Technology Department of Computer Science and Engineering Jain Global Campus India Mlr Institute of Technology Department of CSE-DS Hyderabad India

ISBN: (纸本)9798331543617

Apple leaf disease is a primary issue limiting apple yield and quality. The standard diagnostic approach requires considerable time for illness detection, causing farmers to frequently miss the optimal period for prevention and treatment. The detect of leaf diseases through leaf imagery is a vital study area in computer vision, with the primary objective being to devise an effective method for representing images of sick leaves. The efficient diagnosis and categorization of plant diseases constitutes a significant research aim in agriculture. This paper proposes a novel deep learning, ResNet. To evaluate the efficacy of the ResNet model, a number of comparative experiments were performed with leading transfer learning methodologies. This demonstrates that the proposed method is both possible and successful. © 2024 IEEE.

关键词： CNN Diseases Leaf Resnet Transfer Learning

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Cutting-Edge technology: An Intelligent Channel Allocation and Spectrum Sensing Procedures Over 5G Heterogeneous Networks

Cutting-Edge Technology: An Intelligent Channel Allocation a...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Janakiraman, V. Shobana, D. Aravind, A.R. Nesakumar A, Darwin Sahitya, Pinnamaraju Jyothi Prasad, M. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Ece Tamilnadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India R. M. K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India Engineering Rmd Engineering College Department of Electronics and Communication Tamilnadu Chennai India

ISBN: (纸本)9798350375237

The Spectrum Insight Predictive System (SIPS) represents a groundbreaking approach to optimizing spectrum allocation and enhancing network performance in 5G heterogeneous networks. With the exponential increase in data traffic and the advent of 5G technologies, managing spectrum resources efficiently has become imperative. SIPS addresses this challenge by integrating advanced machine learning algorithms, including K-means clustering and ARIMA forecasting, to intelligently predict spectrum demand and dynamically allocate channels, thereby ensuring efficient spectrum utilization. This paper presents a comprehensive evaluation of SIPS, showcasing its significant impact on network operations and user experience. Through meticulous analysis, SIPS identifies common traffic patterns and peak usage times, leveraging these insights to predict future spectrum demands with high precision. The system then utilizes decision tree algorithms to dynamically allocate spectrum resources, adapting in real-time to the evolving needs of the network. Performance metrics, both before and after SIPS implementation, demonstrate substantial improvements in average throughput, packet loss rates, and spectrum utilization across various times of the day, indicating a more efficient and reliable network. © 2024 IEEE.

关键词： 5G mobile communication systems

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Automated target regression framework for LACP

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Materials Today: Proceedings 2022年 64卷 570-577页

作者： Arun Raj, V. Patil, Shruti Bamini, A. Department of Electronics and Communication Engineering Mepco Schlenk Engineering College Sivakasi India Department of Information Technology MLR Institute of Technology Hyderabad Telangana India Department of Computer Applications The Standard Fireworks Rajaratnam College for Women Sivakasi India

In the world of networking, new protocols are developed every year to meet the customer demands. communication Service Providers are working aggressively to either build new networks or enhance existing ones to support recent technologies and growing end user demands Each protocol has distinctive features and functionalities to be tested. Set-up, tear-down and re-setup of different lab configurations for each test can consume a lot of time and resources. Also, multiple teams often compete for test resources, each with its own aggressive schedule. Forming different topologies for setting the environment itself takes more time. The biggest benefit of automation is that it saves labour, energy and materials. automation is a key enabler for this requirement which can help minimize guess work and human error and at the same free up resources to focus on scenarios that require manual intervention. While scripting capabilities vary by vendor and product, most network products offer a command line interface (CLI) available via telnet or SSH, allowing scripts to simply feed a series of commands to the equipment. In this project, we automate the Link Aggregation protocol testing with the help of Automation Framework to reduce the efforts taken for manual testing. © 2022

关键词： Automation

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Innovative Approaches to Image Processing: Real-Time Applications and Future Prospects 3

Innovative Approaches to Image Processing: Real-Time Applica...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Ravi, Kiran Chand Kannan, K.S. Porselvi, R. Banumathi, S. Manikandan, R. Sultan Saleem, A. MLR Institute of Technology Department of ECE Hyderabad India Kalasalingam Academy of Research and Education Department of CSE Tamil Nadu Krishnankoil India Tagore Engineering College Department of Electronics and Communication Engineering India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering India Panimalar Engineering College Department of Electronics & Communication Engineering Chennai India Dhanalakshmi College of Engineering Department of CSE Chennai India

ISBN: (纸本)9798350354171

The significance of the saying 'a picture is worth a thousand words' is evident in our daily experiences, showcasing the profound impact of images. This paper delves into the contemporary and emerging applications of imaging in our everyday lives, offering a broad spectrum for further exploration. With the advent of digital image processing, there has been a transformative shift in various technical domains, opening avenues for extensive research. There exists considerable potential for exploration and advancement within the realm of image processing, as highlighted in this paper. It encapsulates the foundational stages of digital image processing while emphasizing the diverse areas where research endeavors can enhance the quality of human life. © 2024 IEEE.

关键词： Image segmentation

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Power and Area Optimized Memristor-Based Majority Identifier for Digital Applications 3

Power and Area Optimized Memristor-Based Majority Identifier...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Raj, P. Michael Preetam Vittapu, Sravan K. Chinnasamy, P. Gupta, Manu Samatha, K. Sasivijaya, K. Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Nalla Narasimha Reddy Education Society's Group of Institutions Department of Electronics and Communication Engineering Hyderabad India Kalasalingam Academy of Research and Education Dept. of Computer Science and Engineering Tamil Nadu India Sreenidhi Institute of Science and Technology Department of Electronics and Computer Engineering Hyderabad India

ISBN: (纸本)9798331518592

In earlier developments, CMOS technology played a great role in realizing majority identifiers. There are huge drawbacks that affect the circuit's performance. To overcome the drawbacks of CMOS-based majority Identifiers, novel memristor-based majority and minority Identifiers have been proposed in this work. The features offered by memristor have motivated us to use the component and achieve greatly improved results compared to CMOS-based majority identifier circuits. After observing the behavior of the basic memristor-based majority identifier circuit, we have decided to design and implement a memristor-based majority and minority identifier circuit which can be used in many automation systems to increase quality and productivity. © 2024 IEEE.

关键词： CMOS integrated circuits

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The Role of Medical Informatics in Facilitating Evidence-Based Healthcare Practices

The Role of Medical Informatics in Facilitating Evidence-Bas...

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2025 International Conference on Intelligent Control, Computing and communications, IC3 2025

作者： Gupta, Manish Saeed, Ali Srinija, K. Kumar, Amit Jayanthi, Muthuswamy Lalitha, Yaragudipati Sri Lovely Professional University Phagwara India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India New Horizon College of Engineering Department of Electronics and Communication Engineering Bangalore India Griet Department of Information Technology Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

Medical knowledge, technology, and data have changed healthcare. A new method, OptimizedClinicalDecide (OCD), is transforming evidence-based health care and achieving this critical goal. To treat OCD, it is critical to use medical data as well as cutting-edge algorithms and learning systems that evolve over time. This strategy effectively addresses the long-standing issue of incompatible healthcare data sets, making it perfect for data integration. OCD's dynamic learning engine is continually adding new patient data to the knowledge base, guaranteeing that health care practitioners have the most up-to-date patient health information. Modern healthcare relies on decision-making aid, and flexible decision optimization techniques enhance it by providing patient-specific guidance. OCD's ability to use cutting-edge medical knowledge and promote lifelong learning are its assets. Advanced analytics and personalized patient outcome prediction methodologies increase forecasting and prognosis. The proposed strategy makes use of mobile health resources and is appropriate for the present era of patient-centered treatment. MEPCC promotes patients to work together on health-care decisions. Traditional approaches suffer with adaptability, data integration, and decision support. OptimizedClinicalDecide addresses these challenges and increases patient involvement. According to evidence, OCD has the ability to transform health care. This enhances our mission of providing educated, specialized, and collaborative patient care. © 2025 IEEE.

关键词： Personalized medicine

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KubeEdge for Scalable IoT Applications 7

KubeEdge for Scalable IoT Applications

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Saini, Lalit Mohan Ajmani, Prerna Asha, V. Pithamber, Khobragade Sreevani, N. Viveknanda Institute of Professional Studies Tc Ggsipu Delhi India New Horizon College of Engineering Department of Master of Computer Application Bangalore India Mlr Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Dundigal Hyderabad500043 India

ISBN: (纸本)9798350350067

The rise of IoT (Internet of Things) presents both opportunities and challenges in managing large-scale deployments. Traditional cloud solutions struggle with realtime data processing and scalability for numerous connected devices. KubeEdge, an extension of Kubernetes, addresses these challenges by extending cloud-native orchestration to the edge of the network. This paper explores how KubeEdge enhances IoT applications through efficient edge computing, crucial for reducing latency and optimizing resource utilization. KubeEdge extends Kubernetes' capabilities to manage containerized applications on edge nodes, enabling localized data processing and reducing reliance on centralized cloud infrastructures. This approach minimizes latency and lowers bandwidth costs, making it ideal for real-time, data-intensive IoT applications. This research paper highlights practical use cases and proposes strategic deployment frameworks, emphasizing KubeEdge's benefits in scalability, resource management, and operational efficiency. It also addresses potential challenges in deploying KubeEdge at scale, such as managing resource distribution and integrating with existing infrastructure. This paper provides actionable insights and best practices for Utilizing KubeEdge in various IoT contexts, demonstrating its impact on improving the performance and scalability of IoT systems. © 2024 IEEE.

关键词： Resource allocation

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An Integrated IoT and Wireless System for Energy Optimization and Real-Time Monitoring Towards Sustainable and Efficient Building Management in Smart Buildings

An Integrated IoT and Wireless System for Energy Optimizatio...

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2025 International Conference on Intelligent Control, Computing and communications, IC3 2025

作者： Singh, Someet Malik, Praveen Kumar Chauhan, Ashish Singh Kumar, Manoj Yamsani, Nagendar Singh, Parulpreet School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Uttaranchal University Uttarakhand Dehradun India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798331527495

At a time when urbanization is increasing, and the world's energy need is growing, energy efficiency in building elements has become a key factor in the environment impact mitigation and operational cost reduction strategies. Building management is governed by traditional operational features that are often inadequate to contemporary occupation patterns, infrastructural demands, and environmental changes. Consequently, there is a growing tendency towards the implementation of integrated systems such as autonomous management systems which can oversee energy use and other resources without sacrificing comfort and safety. Cloud storage and wireless technologies have now made it possible to improve energy management like never before. By making use of such technologies, smart building systems are able to receive, transmit and monitor data from many networks in real time. This capability further enhances the control of energy-demanding devices and processes such as heating, ventilation, and lighting, which are controlled and manipulated by preset schedules and manual settings. In addition to this, predictive maintenance and detection of inefficiencies is possible due to real time data analysis trends, usage history and anticipation of external consumption forces. © 2025 IEEE.

关键词： Smart homes

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Sustainable Agriculture in Food Security Integrating Satellite Data Risk Assessment by Cyberattack Detection: AI Applications

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Remote Sensing in Earth Systems Sciences 2025年第2期8卷 435-443页

作者： Kumar, M. Prema Krishnammal, N. Gupta, Manu Begum, Mairaj Unisa Sultana, Sameera Degala, Divya Priya Dept. of ECE Shri Vishnu Engineering College for Women (A) Andhra Pradesh Bhimavaram 534202 India Department of Computer Science and Engineering Dr. N.G.P. Institute of Technology Tamilnadu Coimbatore India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and Technology Telangana Hyderabad India Department of CSE-AIML MALLAREDDY UNIVERSITY Telangana Hyderabad India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

Globally, chronic food insecurity persists and is made worse by shocks brought on by climate change, like floods and droughts. In order to guarantee prompt assistance delivery, humanitarian programming prioritizes predicting levels of food insecurity and identifying homes that are at risk. Using complicated and diverse data, machine learning (ML) models have been widely used to promote food security. This research proposes a novel technique in sustainable agriculture-based food security analysis and satellite data cyberattack detection using machine learning models. Here, the input is collected based on satellite data, and its cyber detection has been analyzed using a convolutional spatio adversarial encoder neural network. Then, from this satellite data, the food security analysis data has been collected and processed for noise removal and normalization. Processed data has been classified using the fuzzy Q-Boltzmann ResNet transfer neural network. Experimental analysis is carried out for the food security analysis dataset in terms of data integrity, detection accuracy, average precision, F-1 score, and recall. The proposed approach yielded 97% detection accuracy, data integrity of 98%, 96% average precision, 93% recall, and 94% F-1 score. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Cyberattack detection Food security analysis Machine learning models Satellite data Sustainable agriculture

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IoT Based Smart Notice Board for Smart Cities 12

IoT Based Smart Notice Board for Smart Cities

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12th International Conference on Computer communication and Informatics, ICCCI 2022

作者： Chinnasamy, P. Rajarajeswari, T.S. Subhasini, P. Naik, S.K. Lokesh Ashwini, A. Sivaprakasam, T. Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Sri Shakthi Institute of Engineering and Technology Department of Electronics and Communication Engineeirng Coimbatore India

ISBN: (纸本)9781665480352

Smart Web based notice board can be implemented in many fields like schools, institutions, banking, medical field, and railway stations etc. This will be a simple process as it need not require any paper information to be displayed. Especially, if this project is implemented in our institution, then it will be easy for the administration block, to easily pass the important information immediately to the staff or students within minutes. A webserver can be used, if the admin gives any information, then it will be displayed on the liquid crystal display. Here, we used microcontroller, Node MCU will read the data from the webpage and then can be seen on the notice board. © 2022 IEEE.

关键词： Smart city

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