2024

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Browsing 2024 by Author "Meher, Kunal"

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    AgroScan : Crop Identification Application using Artificial Intelligence Approach
    (Nanotechnology Perceptions, 2024) Meher, Kunal
    Artificial intelligence (AI) has the potential to revolutionize agriculture, particularly in the realm of crop analysis. AI-based systems can accurately identify crops in images, even under challenging conditions such as low light or shading. These systems have numerous applications, including crop monitoring and management, precision agriculture, and food safety and security. The goal of this research paper is to develop a robust, accurate, and efficient AI-based crop identification system. The system will be trained on an extensive dataset of crop images to identify various crops and detect certain diseases in new images. To evaluate our system's performance, we will compare it against new and emerging methods using a held-out test set. This study aims to develop an AI-driven crop identification system that will benefit farmers and other stakeholders in the agricultural sector by improving crop yields and quality, reducing costs, minimizing environmental impacts, and enhancing food safety.
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    Blockchain Solution for Patient Record Security
    (2024) Meher, Kunal
    The presented Electronic Health Record (EHR) system aims to leverage blockchain technology to achieve enhanced security in transmission of data, improving data integrity, providing controlled access, interoperability, maximize productivity and empowering patients by empowering them to manage their health data. Blockchain system is recognized as a promising approach to these problems, providing a safe and decentralized platform for managing patient records. Our solution, which is built on blockchain technology, addresses critical issues in healthcare data management, such as unauthorized access, data tampering, and the absence of a unified and interoperable platform. By utilizing a distributed ledger, our system guarantees that patient data stays private while being easily available to authorized stakeholders. Smart contracts are utilized to govern access permissions and streamline the process of data sharing among healthcare providers, thereby facilitating a safe and efficient sharing of medical information. The presented EHR system utilize blockchain system to establish a protected, decentralized, and unchangeable record of patients’ medical histories. The system revolutionize the way health records are stored, accessed, and managed. By integrating Ethereum, Smart Contracts, and the Interplanetary File System (IPFS), the system ensures safe, transparent, and efficient handling of medical data. The integration of blockchain system into EHR systems has demonstrated considerable potential in mitigating some of the foremost obstacles within the domain. Due to its intrinsic decentralization, immutability, and openness, blockchain is the ideal tool for improving security, preserving data integrity, and building stakeholder trust in EHR systems.
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    Exploration of OpenCV for Hand Gesture Recognition Techniques - A Review
    (Nanotechnology Perceptions, 2024) Meher, Kunal
    This paper reviews hand gesture recognition techniques by leveraging the strengths of OpenCV and TensorFlow, two of the most widely used libraries in computer vision and deep learning. OpenCV's sophisticated image processing capabilities are utilized for preprocessing, feature extraction, and establishing a solid foundation for further analysis. TensorFlow is employed to construct and train deep neural networks capable of identifying fine-grained details and subtle variations in hand gestures. This integration allows for precise and accurate differentiation and understanding of a predefined set of gestures, demonstrating the potential for robust hand gesture recognition systems.
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    Machine Learning Predication Techniques for Student Placement Job Role Predictions
    (Nanotechnology Perceptions, 2024) Meher, Kunal
    Placements is of endless importance for university students and educational institutions. It helps students build a solid foundation for their future careers and ensure a good enrollment record that gives them a good advantage in school or university. Machine learning is an analytical method that establishes analysis patterns. This article describes the features of the machine that can predict whether a student will see or not, as currently it only depends on the student's qualification, age and experience. The predictor uses three machine learning algorithms: Decision Tree, Naive Bayes, and Random Forest are used. The algorithms are then assessed according to the accuracy of the predictions.
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    Obstacles to the Full Realization and Adoption of Artificial Intelligence (AI)
    (SEEJPH, 2024-10-25) Meher, Kunal
    Artificial Intelligence (AI) holds transformative potential across various sectors, yet its journey to full realization and widespread adoption is impeded by several significant obstacles. These challenges span technical, ethical, societal, research and development, implementation, and regulatory domains, necessitating a comprehensive and multi-faceted approach to address them. Technical Challenges: AI systems require vast amounts of high-quality, labeled data, which is often unavailable or of poor quality. AI models also struggle to generalize beyond specific tasks, and their opaque decision-making processes hinder trust. Scaling AI to handle large datasets and interactions, while ensuring robustness and security against adversarial attacks, poses major technical hurdles. Ethical and Societal Challenges: AI can perpetuate and amplify biases, leading to unfair outcomes and privacy issues. AI-driven automation risks job displacement, necessitating measures for worker support and retraining. The rapid development of AI outstrips regulatory bodies' abilities to create appropriate frameworks, complicating responsible deployment. Research and Development Challenges: AI struggles to integrate information from different modalities and lacks human-like common sense and reasoning. Improving AI's learning efficiency to reduce its dependence on vast data is a significant research focus. Implementation Challenges: Integrating AI into legacy systems, addressing the talent shortage, and managing the high costs of AI development and deployment are substantial barriers. Ethical and Regulatory Uncertainty: The absence of universally accepted ethical guidelines and varying regulatory landscapes create uncertainty and potential misuse. Addressing these multifaceted obstacles requires a concerted effort from researchers, developers, policymakers, and society to create robust, fair, and transparent AI systems, unlocking AI's full potential and societal benefits.
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    Voice Based E-Mail System for Visually Impaired People
    (Nanotechnology Perceptions, 2024) Meher, Kunal
    This article talk about the internet and other technological advancements, communication has been easier in recent years. However, visually impaired persons find it difficult to use this equipment. Despite the fact that numerous new developments have been incorporated to assist them in effectively using the computer, this requires some expertise with the current technology. This study aims to develop an email system that will allow even the most unskilled visually impaired person to interact using the services without any prior training. The system provides the user with a voice based assistant which helps users to perform basic tasks related to handling email by giving voice commands thus providing a user friendly and interactive experience to the users.