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Handy Smart Stick: A Guide for Visually Impaired People 8

Handy Smart Stick: A Guide for Visually Impaired People

引用

8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Gupta, Mansi Laddha, Aditi Chouhan, Maahi Mishra, Yashasvi Gutte, Vitthal Dr. Vishwanath Karad Mit World Peace University B. Tech School of Computer Science and Engineering Rajsamand India

ISBN: (纸本)9798350396638

It's a perpetual human quest and a constant effort of science to develop and design equipment and aids to help physically challenged people live their lives independently and confidently. blindness and visual impairment are prevalent disabilities that inhibit the independence of the patient and increase the reliance on family members, friends, and guide dogs for navigation and other daily duties. The proposed work outlines a reliable, low-cost, and power-efficient solution that enables safe and secure navigation for visually impaired people. Many researchers have worked on and proposed solutions to the typical problems, but those works have some shortcomings that are addressed in this study. Existing technologies have not focused on optimizing power consumption and reliability, thereby reducing the life of the system. It is vital to reduce power consumption in order to extend the operating lifetime of devices that use batteries as a power source. A methodology has been put forward to address the crucial concern of a gadget that is left on for an extended period of time without being switched off to improve the overall performance of the system. The iot is entrusted with taking into account heterogeneous equipment that might be severely constrained by its nature and pose problems in the hardware layer of the system. So methods to make the system reliable, accurate, and resistant to failures are inscribed in this study. Additionally, existing systems aren't economical compared to the offered features, lack automation, and lack audio feedback, particularly notifying obstacles. This study proposes audio feedback in multiple languages and automates the command execution, thereby making it effortless for impaired people to engage with the product. Also, the present state of technology faces challenges in locating the misplaced stick, which means the person has to be dependent on loved ones, friends, or caretakers to find the stick. The proposed automated and handy Smart S

关键词： Internet of things

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Energy conservation: Virtual energy audit of an industrial plant

Energy conservation: Virtual energy audit of an industrial p...

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作者： Joshi, Atharva Khandelwal, Niyati Suryavanshi, Yash broota, Sumir Kurulekar, Maya Dhaneshwar, Pranav LY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune411048 India TY B.Tech Computer Engineering Department of Science and Technology Vishwakarma University MS Pune411048 India Department of Engineering Science Vishwakarma University MS Pune411048 India Department of Mechanical Engineering Vishwakarma University MS Pune411048 India

Energy consumed by manufacturing industries constitutes a large part of the total energy consumption of the world. In India, almost 50% of the total energy consumption is done by Industries. Energy bills are usually a major contributor to the operating expenses of a company. Industries can profit from the opportunities coming out of energy saving by the implementation of effective energy management using appropriate tools. An industrial plant layout is usually designed within several constraints, mainly operational. The objectives were decided by the company to study and identify energy gaps in the industrial plant and suggest suitable solutions to reduce energy consumption all while reducing the average working temperature inside the plant from 38 °C to an ideal value below 30 °C, preferably without installing an air conditioning system. The study was divided into two parts;Primarily, Data collection and observations of the plant operations and then building Energy Modelling and simulation. The base model with existing conditions was modelled, simulated and validated with historical energy consumption data and temperature readings taken inside the plant. The proposed solutions include limited modifications in the existing set up considering the operational constraints. The simulations run with proposed modifications indicate a maximum of 11 % savings in energy consumed by lighting and potential to reduce temperature to 33.23 °C from 38 °C. The effect of ambient factors according to the geographical location such as sun exposure, wind directions, humidity were also taken into consideration. © 2023

关键词： Energy utilization

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A Real-Time Approach to Classify the Water Quality of the River Ganga at Mehandi Ghat, Kannuaj 4

A Real-Time Approach to Classify the Water Quality of the Ri...

引用

4th IEEE International Conference on Artificial Intelligence in engineering and technology, IICAIET 2022

作者： bajpai, Abhishek Chaubey, Srishti Patro, bdk Verma, Abhineet Rajkiya Engineering College Department of Computer Science and Engineering UP Kannauj India B.Tech Computer Science and Engineering Rajkiya Engineering College UP Kannauj India

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Only 0.3 percent of the total water on Earth is available in rivers and ponds, and the majority of it is polluted to the point where drinking it directly can cause disease. In this paper, we will identify the quality of the river Ganges and check if it is portable and healthy. We aim to classify the water on some parameters using different classification algorithms, such as Random Forest, which is a supervised machine learning algorithm. This model's accuracy is around 99 percent, which is far superior to other approaches taken for water quality prediction. © 2022 IEEE.

关键词： Water quality

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Deep Learning based Driver Drowsiness Detection in Real Time Environment - An Enhanced Approach 4

Deep Learning Based Driver Drowsiness Detection in Real Time...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Ajay, Ashin Ashok, Naveen Kumar balajiram, Gokul Tamizhselvan, Abinesh Thangavel, Senthil Kumar Somasundaram, K. Amrita Vishwa Vidyapeetham M. Tech in Artificial Intelligence Coimbatore India Amrita Vishwa Vidyapeetham B. Tech in Computer Science and Engineering Coimbatore India Amrita School of Computing Coimbatore Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India School of Physical Sciences Department of Mathematics Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

Effective driver behavior monitoring is necessary due to the increase in traffic accidents caused by distracted driving. In order to identify distractions such as talking, drinking, napping, and using a phone, this research suggests a CNN-based methodology. The model uses facial characteristics such as eyes to detect and analyze these activities. Thousands of photos depicting various distracted driving postures are used to train it on a publicly accessible dataset. The strategy seeks to improve road safety by offering a reliable way to identify distractions. © 2025 IEEE.

关键词： Convolutional neural networks

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Deep Learning for Glioblastoma Subtyping: Leveraging DenseNet-201 in brain Tumor Radiogenomic Classification 1

Deep Learning for Glioblastoma Subtyping: Leveraging DenseNe...

引用

1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - RObINS 2024

作者： Jesuraj, S. Alvin Evangelin Sonia, S.V. Shirley, C.P. Karunya Institute of Technology and Sciences B.Tech Computer Science and Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India

ISBN: (纸本)9798350372748

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI brain Tumor Radiogenomic Classification aimed at predicting the genetic subtype of glioblastoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying glioblastoma cases based on MGMT promoter methylation status, a critical biomarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhibits robust performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ability to effectively distinguish between MGMT promoter methylation-positive and negative glioblastoma cases, offering valuable support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of glioblastoma genetics and guiding personalized therapeutic interventions, ultimately contributing to improved patient outcomes in brain cancer management. © 2024 IEEE.

关键词： biomarkers

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Multilingual Contemplation for Social Media data by Hybrid Classifier

Multilingual Contemplation for Social Media data by Hybrid C...

引用

2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Manoj, Challapalli Tejaswi, Talluru Sohana Nekkanti, Devi Sai Valiveti, Sriram Ganesan, Vithya Ramasamy, Viswanathan B. Tech Koneru Lakshmaiah Education Foundation Computer Science and Engineering Guntur India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Sentiment analysis procure substantial contemplation for abandon growth of the web and social media. The goal is to identify opinions, sensation, or conviction of multilingual tweet. A large set of manually labeled tweets in different languages, use them as training data, and construct sentiment analysis model. A machine-learning algorithm is used to identify and extract characteristics such as adjectives, adverbs, and abstract nouns from each cleaned tweet. If the input text is not in English, the Google Machine Translator is utilized to convert it into English. A hybrid model called voting-based ensemble model which integrates Naive bayes, Multinomial Naive bayes, bernoulli's Naive bayes, Logistic Regression, Stochastic Gradient Descent, Support Vector Machines, and Maximum Entropy classifiers to resolve the ambiguous language. If, same word appears in both English and non-English it utilizes a hybrid model retrieved features to translate a tweet /string. The classifiers identify the sentiment of translated multilingual tweets and extended with prediction. © 2022 IEEE.

关键词： Support vector machines

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Prediction of Herbs with its benefits using Deep Learning techniques

Prediction of Herbs with its Benefits using Deep Learning Te...

引用

2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022

作者： begum, M. Sharmila Haris, R. Vetrimaran, V. Raj, P. Ashwin B.Tech Computer Science and Engineering Pmist Tamil Nadu Vallam Thanjavur India

ISBN: (纸本)9781665478847

Automated plant identification is a very promising solution for bridging the taxonomic gap, which is receiving much attention from botany and computer science. As machine learning technology advances, more complex models have been proposed to automate crop identification. Herbal remedies are considered in the pharmaceutical industry due to fewer harmful side effects and less expensive than modern medicine. based on these data, many researchers have shown great interest in studying the recognition of natural herbal medicines. There are various possibilities for moving towards solid phase production capable of accurately discriminating medicinal plants in real time. In this project, efficient and reliable machine learning algorithms for plant catalogues using leaf images used in recent years are being studied. The review covers image processing techniques used to locate leaves and extract important leaf features from other machine learning steps. These deep learning stages are classified according to their function when it comes to discriminating leaf images based on common plant characteristics, i.e. shapes, ridges, textures and combinations of many elements. Then you get results using herbs with improved accuracy. The test results indicate that the proposed system provides an improved level of accuracy. © 2022 IEEE.

关键词： Deep neural networks

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iot-Genomics Analysis for Personal Health with Cybergenomics and Cloud technology 10

IoT-Genomics Analysis for Personal Health with Cybergenomics...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Prabakaran, T. babu, A. Ramesh Hemalatha, S. Ramasamy, Jayabharathi Kovarasan, Rajesh Kambattan Elango, b. Joginpally B.R. Engineering College Department of Computer Science and Engineering Telangana Hyderabad India Vidya Vikas Institute of Engineering and Technology School of Computer Applications Karnataka Mysore India Tagore Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

Recent innovations at the convergence of genomics and the Internet of Things (iot) have opened the way for an innovative strategy for administering individualized health care. This research study combines the potential of wearable health monitoring technologies with genetic insights to analyze the personal healthcare. A comprehensive knowledge of health dynamics may be achieved by seamlessly integrating real-time health data collected from iot-enabled wearables with individual genetic profiles. Using algorithms for machine learning, connections between genetic differences and instantaneous health responses may be uncovered, paving the way for the development of individualized therapies and lifestyle recommendations. The suggested framework allows people to improve their health and gives medical professionals access to data-driven insights that can be used for the early diagnosis of diseases and the development of individualized treatment plans. The work that has been done sheds light on the revolutionary potential of merging genetics with the Internet of Things to establish a new paradigm of preventative and individualized medical treatment. © 2024 IEEE.

关键词： Genome

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A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography 2

A Secure Data Encryption Mechanism in Cloud Using Elliptic C...

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2nd IEEE International Conference on Intelligent and Innovative technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Sudha, I. Donald, Cecil Navya, S. Nithya, G. balamurugan, Manivannan Saravanan, S. Saveetha Institute of Medical and Technical Sciences - Simats Department of Computer Science and Engineering Saveetha School of Engineering Chennai India Department of Computer Science Bengaluru India Raghu Engineering College Department of Computer Science Engineering Visakhapatnam India Department of Cse V. S. B College of Engineering Technical Campus Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Mathematics Tamil Nadu Avadi India

ISBN: (纸本)9798350306415

Cloud computing is undergoing continuous evolution and is widely regarded as the next generation architecture for computing. Cloud computing technology allows users to store their data and applications on a remote server infrastructure known as the cloud. Cloud service providers, such Amazon, Rackspace, VMware, iCloud, Dropbox, Google's Application, and Microsoft Azure, provide customers the opportunity to create and deploy their own applications inside a cloud-based environment. These providers also grant users the ability to access and use these applications from any location worldwide. The subject of security poses significant challenges in contemporary times. The primary objective of cloud security is to establish a sense of confidence between cloud service providers and data owners inside the cloud environment. The cloud service provider is responsible for ensuring user data's security and integrity. Therefore, the use of several encryption techniques may effectively ensure cloud security. Data encryption is a commonly used procedure utilised to ensure the security of data. This study analyses the Elliptic Curve Cryptography method, focusing on its implementation in the context of encryption and digital signature processes. The objective is to enhance the security of cloud applications. Elliptic curve cryptography is a very effective and robust encryption system due to its ability to provide reduced key sizes, decreased CPU time requirements, and lower memory utilisation. © 2024 IEEE.

关键词： Cloud computing cryptography data security ECC encryption

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Development of Green Computing through Power Management in Wireless Networks using Machine Learning 7

Development of Green Computing through Power Management in W...

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7th International Conference on Inventive Computation technologies, ICICT 2024

作者： Raja, S.R. Arya, Hemlata Ramya, D. Sivakumar, S. Arigela, Arun Kumar Venu, Nookala Saveetha Deemed University SIMATS Saveetha College of Liberal Arts And Science Department of Computer Science Chennai India Department of Computer Science & Engineering Madhya Pradesh Gwalior India Sathyabama Institute of Science And Technology Electrical And Electronics Engineering Rajiv Gandhi Salai Chennai India Vel Tech Rangarajan Dr. Sagunthala R And D Institute of Science And Technology Department of Electrical And Electronics Engineering Chennai Tamilnadu Avadi600062 India Department of Csit Telangana Hyderabad India Centre For IoT Madhya Pradesh Gwalior474 005 India

ISBN: (纸本)9798350359299

This study investigates the use of Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) to improve power utilization in green data centers. The study examines each model's individual capabilities in addressing key concerns about energy efficiency and sustainability. SVM is extremely accurate in workload prediction and resource allocation, whereas CNN excels in real-time monitoring and cooling system efficiency. RNN contributes by anticipating fluctuations in energy use and adapting to dynamic workload changes over time. The research uses ten hypothetical trials to demonstrate the models' consistent performance across multiple measures. These results suggest that SVM, CNN, and RNN have transformative potential in the development of flexible, efficient, and sustainable green data centers. The study adds to the larger discussion about green computing by emphasizing the role of powerful machine learning models in shaping the future of ecologically responsible data center operations. © 2024 IEEE.

关键词： Support vector machines

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