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Increasing Emergency Response Time: A Smart GPS and IoT-Based Approach for Ambulance Optimization 2

Increasing Emergency Response Time: A Smart GPS and IoT-Base...

引用

2nd IEEE international conference on advances in Information Technology, ICAIT 2024

作者： Prajwal, V. Rahul, I.V. Sai Adithya, A. Chayadevi, M.L. Computer Science and Engineering BNMIT Bangalore India HOD Computer Science and Engineering BNMIT Bangalore India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383867

This paper proposes a novel approach to enhance ambulance response times and streamline patient transportation during emergencies by leveraging a smart GPS-based system integrated with Internet of Things (IoT) technology at traffic signals. Traditional methods, relying on camera detection or manual traffic clearance, often lead to delays in granting priority to ambulances. In contrast, our system pre-empts traffic signals in real-time, ensuring swift passage for ambulances by communicating with IoT devices installed at traffic control boxes. The proposed system optimizes ambulance routes using real time traffic data and machine learning algorithms, dynamically adjusting paths to avoid congestion. Components include a smart GPS navigation system, IoT devices at traffic signals, robust communication protocols, and centralized control systems. In summary what makes this design effective is its ability to prioritize clearing intersections ahead of emergency vehicles thus reducing time spent on responding to medical calls while at same time giving hope for better outcomes among patients. © 2024 IEEE.

关键词： Traffic signals

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Language Translator Using Python 1

Language Translator Using Python

引用

1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Raj, Mayank Devang, Ashish Chanchal, Satya Saini, Kavita Galgotias University School of Computer Science and Engineering Department of Computer Science and Engineering India

ISBN: (纸本)9798350356816

The most well-known type of correspondence between people is Discourse and correspondence assumes a vital part for conveying data. The truth of the matter is that each specific person on the planet won't discuss the same language, numerous people will be communicating in various dialects. Summing up the required content is particularly vital to conveying the right message. On the off chance that the data required isn't conveyed appropriately then numerous entanglements might happen. If either side of the imparting people is uninformed about the language, then the pattern of discourse will be deficient. Thus, we want a framework that will settle our language obstruction issue. So, we concocted a framework for example "Language Convertor utilizing Python"which will change over discourse of one language into another dialect utilizing Python. project intends to foster a flexible and easy-to-use instrument that can consistently interpret text between different dialects. This undertaking uses the force of Python, alongside famous libraries like Google Decipher Programming interface or DeepL API, to make a proficient language change device. © 2024 IEEE.

关键词： Python

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Feature as a Service (FaaS): Customized Service in Cloud Computing 1

Feature as a Service (FaaS): Customized Service in Cloud Com...

引用

1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Sharma, Aditi Kaushik, Deepti Maurya, Santosh Kumar Malik, Suraj Kumar, Gaurav Asim, Mohammad IIMT University Computer Science and Engineering Department Uttar Pradesh Meerut India Sharda University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350356816

The world is changing due to technological changes. Like the business approach, there is a need to maintain tremendous pressure for reliable service architecture. Features of trust may include cost-effectiveness, reliability for services, pay per use, etc. Cloud services are very much appreciated as it is giving tremendous market to the business audience. Inspired by this, processing and storage capacity is also improving. By proposing a new service FaaS (Feature as a Service), more measuring factors can be obtained to achieve greater growth in technology and will also benefit the business audience. The offered service is directly related to both the things i.e. server and user related, in terms of system optimization and user satisfaction. The measuring function is also proposed in the paper. Ultimately the new customized service model will yield benefits. As the world has now become digital, the system efficiency should be further increased by designing these types of services which can cover the entire cloud system in all aspects. © 2024 IEEE.

关键词： Cloud computing architecture

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Minor Damage Detection in Cars using Transfer Learning Techniques 2

Minor Damage Detection in Cars using Transfer Learning Techn...

引用

2nd IEEE international conference on advances in Information Technology, ICAIT 2024

作者： Sungheetha, Akey Christopher, Kevin Maheswari, T. Latha Sasikalarani, K. Sharma, Rajesh R. Computer Science & Engineering Alliance University Bengaluru India Coimbatore India

ISBN: (纸本)9798350383867

The car scratch detection is a pivotal aspect of automotive maintenance and safety, crucial for preserving the visual appeal and structural integrity of vehicle exteriors. This paper investigates contemporary methodologies and advancements in car scratch detection, emphasizing both conventional and computer vision-based techniques. By scrutinizing diverse approaches including image processing algorithms, machine learning models, and sensor-driven systems, this study elucidates the efficacy and constraints of existing methodologies while delineating prospective avenues for further research and development in the realm of car scratch detection. Additionally, the paper underscores the significance of real-time detection systems and the integration of advanced technologies such as artificial intelligence and deep learning to enhance the accuracy and efficiency of car scratch detection mechanisms, ultimately contributing to the longevity and aesthetic maintenance of automotive surfaces. © 2024 IEEE.

关键词： Deep learning

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Classifying Authentic and Fake Anger Based on High-Performance LSTM Networks Model, Fuzzy Logic Model and Fully Connected Neural Network 4

Classifying Authentic and Fake Anger Based on High-Performan...

引用

4th international conference on advances in Electrical engineering and computer Applications, AEECA 2023

作者： Chen, Kangyu Peng, Zhiyuan The University of Hong Kong Department of Computer Science Hong Kong Nanjing University State Key Laboratory For Novel Software Technology Nanjing China

ISBN: (纸本)9798350308082

Understanding human's emotion is a vital task in the computer science and machine learning. People could easily distinguish the genuine and posed anger while it could be difficult for computers to judge the authenticity of anger. In this paper, apart from the fully connected Neural Networks built in the previous research, methods of LSTM (Long short-term memory) Networks and Fuzzy logic classification are also built for telling the posed angers from genuine ones using limited data. Then the paper compared the performance of these three popular classification methods. Carefully designed modifications have been made on these models to increase the performance. © 2023 IEEE.

关键词： Long short-term memory

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Machine Learning Approach for Handling Imbalanced Students' Performance Data 15

Machine Learning Approach for Handling Imbalanced Students' ...

引用

15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sujatha, E. Divya, S. Sakthivelan, R.G. Gopirajan, P.V. Thandalam Chennai India Chennai India Department of Computer Science and Engineering Gopalan College of Engineering and Management Bengaluru India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur campus Chennai India

ISBN: (纸本)9798331300579

Imbalanced student performance data in educational institutions is crucial for any machine learning prediction model. It affects the efficiency of classifiers and challenges the sampling methods for having a more significant number of features. The proposed model was designed to predict the student's performance by comparing the results with popular similar models. The Kaggle dataset having 386 rows and 33 columns of student data, was used in this study. In addition, the Portugal database was considered for experimental analysis, containing 394 students and 19 attributes. It proves that the Random Forest classifier yields the highest accuracy at 84.15% in handling imbalanced datasets. The results show that the SVM-SMOTE is higher accuracy as, 94.76%, than the other sampling methods in predicting the student's performance with various features. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

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Sarcasm Detection in English-Hindi Code-Mixed Text Data 2

Sarcasm Detection in English-Hindi Code-Mixed Text Data

引用

2nd international conference on advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Prajapati, Abhinav Singh, Ajeet Arora, Vasudha Bansal, Nidhi Department of Computer Science and Engineering Sharda School of Engineering and Technology U.P. Greater Noida India Department of Computer Science & Engineering Moradabad Institute of Technology Uttar Pradesh Moradabad India Nagpur Campus Pune India

ISBN: (纸本)9798331541217

Sarcasm-also termed as verbal irony, when the speaker presents something in a mocking or humorous way such that he or she actually conveys the opposite of what they seem to say. This article has a detailed analysis of sarcasm detection in English-Hindi code-mixed texts based on the difficulties one faces while identifying sarcasm in linguistically complex data. Several machine learning and deep learning methods are adopted and compared, Long Short-Term Memory, Bidirectional Encoder Representations from Transformers, and Support Vector Machines are some of them. In addition, the complexity in the detection of sarcasm is further compounded by the nuance of code-mixed language because the former does not have any tradition that can be adapted to traditional text classification methods. Feature extraction and the subsequent decision-making processes are also factored with broader implications for sentiment analysis. The results of the models analysed underwent a comparative analysis, which showed that the model produced out of the combination of BERT and Gated Recurrent Unit (GRU) surpasses other models to be used for this particular task with its detection accuracy rate, said to be the best in determining sarcasm. © 2024 IEEE.

关键词： Support vector machines

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Real-Time Interaction in AR/VR Environments: A Deep Learning Approach to Human-computer Interaction 1

Real-Time Interaction in AR/VR Environments: A Deep Learning...

引用

1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Chindiyababy, U. Mehta, Vishal Kakkar, Preetish Dilbar, Matchanova Umidbek, Abdalov Sharma, Aditya SRM Valliammai Engineering College Department of Information Technology India India Urgench state university Uzbekistan Mamun university Department of History Khiva Uzbekistan Tula's Institute Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798331518578

AR and VR technologies represent Innovative technologies of HCI providing rich and dynamic user experiences. This work proposes a framework based on deep learning for interacting in real-time with AR/VR environments and employing innovative multimodal input handling and flexible response strategies. The implementation consists of convolutional neural networks (CNNs) for gesture recognition, recurrent neural models for natural language understanding, and transformer-based models for gaze tracking. These models are latency-reduced and are deployed with minimal overhead architectures to fit into constrained AR/VR devices. Several assessments are done based on actual data, and mock AR/VR is used to help prototypes. Experimental evaluation confirms that the proposed framework has better interaction latency, accuracy, and adaptability over conventional approaches. For instance, gesture recognition has a success rate of 96.3% the response is facilitated in less than 50 and the natural language commands have a processing delay of 30 ms. The user surveys support the case that the system effectively presents context-based and individualized communication making the system more engaging and easier to use. It focuses on the issues that arise while implementing such methods, including computational load and integration difficulties, and provides a more detailed version of this work that describes solutions to them. The findings map the feasibility of deep learning in augmenting HCI within the AR/VR systems, which will help propel advancements across education, healthcare, and more notably, game-designing and telepresence. © 2025 IEEE.

关键词： Convolutional neural networks

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A Review of Machine Learning Algorithm used in Crop Recommendation 15

A Review of Machine Learning Algorithm used in Crop Recommen...

引用

15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sonkar, Ranjeet Tyagi, Yash Arora, Aditi Joshi, Anju ABES Engineering College Ghaziabad India

ISBN: (纸本)9798331300579

In India, Agriculture plays a pivotal role in the Indian economy, contributing approximately 17% to the total GDP and employing over 60% of the population. Not only in India, agriculture sector is one of the most important sectors in all over the world. In the past few years many machine learning algorithms are being used to recommend the best crop for farmers under the different conditions. It is important to recommend the best crop to the farmers not only for the better growth but also for the decrease the risk of farmers. Tn this paper we are doing the review of different machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine, Extra Trees, Decision Tree, Randam Forest and many more. And then we find out the best algorithms based on their accuracy rate and used that algorithm in our project to recommend the crop. It also requires the dataset to train our system. So, we take the dataset of values like N, P, K, temperature, humidity, ph, and rainfall. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

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Multiscale Feature Extraction Techniques for Emotion Recognition from Physiological Signal 1

Multiscale Feature Extraction Techniques for Emotion Recogni...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Taley, Shruti G. Pund, M.A. Prof. Ram Meghe Institute of Technology & Research Department of Computer Science & Engineering Amravati India

ISBN: (纸本)9798350356816

Emotion detection from physiological data is a growing field with important uses in affective computing, HCI, and medical imaging. To achieve significant progress in human-computer interaction, ability to recognise emotions is essential, particularly when using non-intrusive physiological sensors. This work investigates multiscale feature extraction methodologies used in emotion detection systems, with a focus on methodology and benefits. We examine physiological signals like electrocardiogram (ECG), galvanic skin response (GSR) & electroencephalogram (EEG) and we discuss state-of-the-art multiscale feature-based deep learning and machine learning methods. The aim of the paper is to present thorough assessment of state-of-the-art multi-scale machine learning techniques. © 2024 IEEE.

关键词： Electroencephalography

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