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Machine Learning-Driven Identification of Cotton Leaf Diseases for Precision Agriculture

Authors : Tushar Mohite Patil , Sanjay Pandey2, Ravindra Duche DOI :10.46335/IJIES.2025.10.7.12 Abstract – In this study, we propose a machine learning-based method for automatic detection of cotton leaf diseases based on Random Forest classifier. Other features extracted are color based (RGB) and texture based (GLCM) that helps a lot in increasing the classification accuracy. […]

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Predicting Chronic Kidney Disease with Machine Learning Algorithms

Authors:  Jayesh Sanjay Patil ,Nilesh Vani DOI : 10.46335/IJIES.2025.10.6.14 Abstract – Chronic Kidney Disease (CKD) is a progressive, irreversible condition distinguish by a gradual decline in kidney functions, often remaining asymptomatic until advanced stages. Early detection is essential for improving patient outcomes and prolonging survival. This study shows a machine learning (ML) approach for diagnosing […]

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A Review of Machine Learning and Deep Learning Techniques for Identifying Cardiovascular Disease in ECG Images

Authors :Ms.Shraddha R. Mundada , Mr.Prashant Shimpi DOI : 10.46335/IJIES.2025.10.6.2 Abstract –Globally Cardiovascular diseases (CVDs) rank among the top causes of death. Electrocardiogram (ECG) readings provide vital information necessary for diagnosing heart ailments. Techniques in Machine Learning (ML) and Deep Learning (DL) have transformed the automatic identification and categorization of CVDs from ECG images. This […]

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An In-depth Review of Machine Learning & Deep Learning Models for Enhancing Security and Scalability in Edge Computing

Authors : Mr. Pankaj S. Wankhede , Ganesh Khekare ,  Dr. Amitabh Wahi DOI : 10.46335/IJIES.2025.10.8.20 Abstract: The current reality is very fast-paced edge computing that shortly will be demanding robust security and scaling solutions for its necessarily distributed and resource-constrained nature. Addressing this need, this paper critically assesses machine learning and deep learning models […]

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An Iterative Systematic Analytical Review of Modern Intrusion Detection Systems

Authors : Rahul V. Bambodkar, Amitabh Wahi, Ganesh Khekare DOI : 10.46335/IJIES.2025.10.8.19 Abstract: With the increasing dependence on cloud computing and Internet of Things (IoT) environments, data integrity, confidentiality, and availability become significantly larger issues. The reviews of the existing IDSs have often failed to consider the optimization techniques, scalability, privacy preservation, and adaptability of […]

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IoT and AI in Agriculture: Enhancing Productivity and Optimizing Resources – A Review

Author : Suvarna Girase , Dr. Nilesh Choudhary DOI : 10.46335/IJIES.2025.10.8.6 Abstract –IoT (Internet of Things) technologies are essential to supplying the world’s expanding food demand, and the change in farming methods has brought along both benefits and challenges. IoT sensors monitor essential parameters like soil pH, moisture, and water levels. For instance, water volume […]

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Smart College System Using AI

Authors : Pawar Rahul , Rathod Rahul, Ingale Kunal , Patil Kunal , Prof. Bhoir Swati DOI: 10.46335/IJIES.2025.10.8.4 Article Link Abstract – Smart College System to enhance communication, information dispersion, and virtual literacy gests within educational institutions. The system integrates four main modules: Voice Assistant, Chatbot, Virtual Classroom, and Admin Module. The Voice Assistant and […]

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Water Energy Audit and Consumption Prediction Using IOT and Machine Learning

Authors : Mitesh P Sapkale , Hemraj V. Dhanade, Dr. Hemant T. Ingale,Dr. Anilkumar Vishwakarma, Dr. Ishwar Jadhav DOI :10.46335/IJIES.2025.10.4.8 Article Link Abstract – Water, a vital resource for both human survival and industrial processes, faces increasing pressure due to population growth, climate change, and over-exploitation. Water conservation and efficiency, therefore, are paramount in ensuring […]

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Literature Survey on Intelligent Rainfall Prediction Systems Using Advanced Machine Learning Algorithms

Authors : Dr.M.V.Bramhe, Rushab Katekhaye, Manthan Raut, Sharwari Sonulkar,Yash Dhande, Mrs. Sangita Rajankar DOI : 10.46335/IJIES.2025.10.5.3 Article Link  Abstract  – Rainfall prediction is crucial to efficient water resource management, agriculture, and catastrophe avoidance. Statistical models have gained popularity, yet machine learning approaches are progressively boosting prediction accuracy. SARIMA stands out for the ability to understand […]

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