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Binary Classification of Human Emotion using EEG and LTSM 基于EEG和LTSM的人类情绪二分类
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111854
Sharzeel Saleem, J. O, Pratikshit Vashishta
{"title":"Binary Classification of Human Emotion using EEG and LTSM","authors":"Sharzeel Saleem, J. O, Pratikshit Vashishta","doi":"10.1109/ICRTEC56977.2023.10111854","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111854","url":null,"abstract":"Emotion detection is an important aspect in the development of AI based systems to assist humans. People affected with neurological disorders are paralyzed and have difficulty in expressing their emotions. Identifying their emotions and act accordingly helps to keep them happy and healthy. In this paper we have attempted a system that detects and classifies human emotion using Electroencephalography (EEG) signals. The process involves getting the data from the four electrodes placed on the scalp of a human and monitoring the brain activity. The algorithm uses a Long Short-Term Memory network (LTSM) which gives a training accuracy of 95.55%.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131391424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design and analysis of microstrip patch antenna 微带贴片天线的设计与分析
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111920
R. Mahapatra, G. S. Satapathi, Pradeep Kumar, Akshith N Shetty, Shashwath Shettigar, Abhinav J P, B. Patro, Dipika Satapathy
{"title":"Design and analysis of microstrip patch antenna","authors":"R. Mahapatra, G. S. Satapathi, Pradeep Kumar, Akshith N Shetty, Shashwath Shettigar, Abhinav J P, B. Patro, Dipika Satapathy","doi":"10.1109/ICRTEC56977.2023.10111920","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111920","url":null,"abstract":"This work represents the design of a rectangular microstrip patch antenna resonating at 2.4 GHz to 11 GHz with better notch in the band. The structure of the rectangular microstrip patch antenna consists of the dielectric material in between the patch and the ground plane. The antenna is designed with a suitable substrate such as Flame-Retardant-4 (FR-4) which has a dielectric constant of 4.4, a height of 1.6 mm, and a loss tangent of 0.02. Microstrip feed lines are used for the design. The performance evaluation is measured in terms of return loss, gain, directivity and notch. From the results, this antenna has shown better performance in comparison to other related works.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126884728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Efficient Novel Binary to Gray Code Converter Using Coulombic Interaction on Quantum Dot Cellular Automata 利用量子点元胞自动机上的库仑相互作用的新型高效二值到灰码转换器
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111872
Insha Yaqoob Sheikh
{"title":"Efficient Novel Binary to Gray Code Converter Using Coulombic Interaction on Quantum Dot Cellular Automata","authors":"Insha Yaqoob Sheikh","doi":"10.1109/ICRTEC56977.2023.10111872","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111872","url":null,"abstract":"Quantum-dot Cellular Automata (QCA) has gained significant attention as a promising technology for implementing digital circuits due to its unique properties such as low power consumption, high speed, and small size. In this research paper, a novel design for a Binary to gray code converter using QCA technology is presented. The proposed design utilizes the coulombic interaction between cells in QCA, which allows for interaction via electrostatic forces, to implement the logic function for converting a binary number to its corresponding gray code representation. The proposed design is simulated and analyzed using various tools and techniques to verify its functionality and performance. The simulation results demonstrate the effective-ness and efficiency of the proposed design in terms of power consumption, speed, and accuracy. The proposed design has the potential to be implemented in various digital systems, including communication systems, computer systems, and control systems, to improve the performance and reliability of these systems.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123483318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
IoT enabled Smart Car with V2X Enhanced Comunication and Safety Alert system 具有V2X增强通信和安全警报系统的物联网智能汽车
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111919
Sanjay S Tippannavar, Y. D, Chandrashekar Murthy B N, P. S
{"title":"IoT enabled Smart Car with V2X Enhanced Comunication and Safety Alert system","authors":"Sanjay S Tippannavar, Y. D, Chandrashekar Murthy B N, P. S","doi":"10.1109/ICRTEC56977.2023.10111919","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111919","url":null,"abstract":"This work conducted makes four-wheeled driving safer than ever before to prevent accidents from becoming an unforeseen and unexpected occurrence, despite the rise in the number of motorcycle riders and accidents in our nation. Because of the dramatic ending. The main cause of fatality in half of all traffic accidents is a delay in receiving care. The initiative intends to enable early accident detection and to quickly provide information to emergency personnel, enabling them to give the wounded individual urgent aid. In the event that a passenger is involved in an accident and the helmet strikes the ground, the vibrating sensor included into the helmet detects a vibration and sends the value to the raspberry pi module fastened to it. Even if the vibration threshold frequency exceeds the cap, the gearsing board extracts GPS data from the GPS module, and an alert message with all the relevant information is promptly transmitted to the registered passenger emergency contacts. With the help of this software, the accident victim will get prompt aid. Particular danger regions are shown by the findings.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114684684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Temperature Dependent Capacity Fade Prediction of Electric Vehicles Batteries 电动汽车电池温度相关容量衰减预测
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111909
B. Bairwa, ShriHarinayaka P, Sagar B S, A. P
{"title":"Temperature Dependent Capacity Fade Prediction of Electric Vehicles Batteries","authors":"B. Bairwa, ShriHarinayaka P, Sagar B S, A. P","doi":"10.1109/ICRTEC56977.2023.10111909","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111909","url":null,"abstract":"The aim of this project is to examine the impact of aging, on various types of electric vehicle batteries. This ambient temperature range from 0 degrees to 50 degrees has been considered, this wide range of temperature shows the arctic to desert areas for electric vehicle operation. In this investigation mainly lead-acid batteries, lithium-ion batteries, nickel-cadmium batteries, and nickel metal hayride batteries have been considered. Various types of drive cycles have been used to check the battery age for electric vehicle applications. The proposed work has been performed with the help of MATLAB Simulink, the obtained results show good agreement with published work in the same domain. Results have been compared with published literature for batteries.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124099643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forest Fire Detection Using nRF24L01 Wireless Sensor Network And Prediction by Machine Learning Model 基于nRF24L01无线传感器网络的森林火灾探测与机器学习模型预测
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111910
P. A. Anshad, Niteesh M Gowda, V. K, A. S. Prasad
{"title":"Forest Fire Detection Using nRF24L01 Wireless Sensor Network And Prediction by Machine Learning Model","authors":"P. A. Anshad, Niteesh M Gowda, V. K, A. S. Prasad","doi":"10.1109/ICRTEC56977.2023.10111910","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111910","url":null,"abstract":"Forest fire is a major problem in recent years which creates natural disasters. An effective method for the detection and prediction of forest fires reduces the devastating effect. An effective method to predict and detect forest fires in real time is implemented in the paper. Real-time forest fire detection is done by considering various parameters like temperature, humidity, and smoke intensity with the help of nRF24L01 based wireless sensor network established using tree topology. Prediction of forest fire is done by integrating neural prophet and logistic regression machine learning models by considering key environmental parameters. The prediction accuracy of 86.67% was obtained by considering the parameters like earth skin temperature, wind speed, relative humidity, and precipitation. The prediction model is able to predict fire occurrence efficiently from 2013 to 2015 which has been validated with the available dataset.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130192893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Energy-Efficient Ant Colony Task Assignment Based Spectrum Sensing for Cognitive Radios 基于节能蚁群任务分配的认知无线电频谱感知
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111884
Rajalekshmi Kishore, Sanjeev Gurugopinath
{"title":"Energy-Efficient Ant Colony Task Assignment Based Spectrum Sensing for Cognitive Radios","authors":"Rajalekshmi Kishore, Sanjeev Gurugopinath","doi":"10.1109/ICRTEC56977.2023.10111884","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111884","url":null,"abstract":"In this paper, we discuss the energy efficiency (EE) of an ant colony task assignment-based cooperative spectrum sensing (CSS) algorithm for cogntive radios. The main idea in this technique, called the 2EACRAC2S algorithm, is that a secondary (SU) participates in the CSS procedure only when the path loss between itself and the primary user (PU) exceeds a threshold. Otherwise, it does not carry out SS and refrains from sending the decision to a fusion center (FC), which saves energy. The FC uses the AND fusion rule to combine the decisions from active SUs. Expressions for the achievable throughput, energy consumption and EE of the 2EACRAC2S algorithm are derived. Results based on numerical techniques show that the 2EACRAC2S outperforms CSS technique, in terms of EE.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121320374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Real Time Tomato Plant Leaf Disease Detection Using Convolutional Neural Network 基于卷积神经网络的番茄叶片病害实时检测
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111895
Ananya H P, Shreya K Magadum, S. S, A. S. Prasad
{"title":"Real Time Tomato Plant Leaf Disease Detection Using Convolutional Neural Network","authors":"Ananya H P, Shreya K Magadum, S. S, A. S. Prasad","doi":"10.1109/ICRTEC56977.2023.10111895","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111895","url":null,"abstract":"A substantial threat in achieving a good harvest is crop diseases. To achieve better results, the field of leaf-based image classification requires the advancement of precise approaches. The dataset is created with 200 pre-processed images. The model training includes creation of dataset, further clearing of noise in the images and assigning their corresponding pixel values. After uploading the test image, passed through Convolution, pooling, flattening and full connection are steps in the feature extraction process. The pre-trained model is run after loading an image, scaling it, adjusting the value of the pixels. The convolution neural network (CNN) used for classification of real-time leaf disease of tomato plants. The solution employs a convolution neural network with 97.5% accuracy to identify disease in real time tomato plant leaves with in a span of 4 seconds.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121602792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
NBA Game Prediction Using Machine Learning Algorithm 使用机器学习算法预测NBA比赛
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111906
A. Patrot, H. H, Shambbavi B, Geetha P L, Sahana
{"title":"NBA Game Prediction Using Machine Learning Algorithm","authors":"A. Patrot, H. H, Shambbavi B, Geetha P L, Sahana","doi":"10.1109/ICRTEC56977.2023.10111906","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111906","url":null,"abstract":"The large financial transactions in fantasy sports show how popular is sports outcome prediction have become important in recent years. Basketball, especially the National Basketball Association (NBA) of the United States well-liked sports in the world that attracts investment and millions of fans on a global scale. This paper offer a novel intelligent machine learning framework with the goal of identifying the key factors that have the greatest impact on NBA game outcomes. Techniques of machine learning determines the result of an NBA using previously played games, and various variable quantities that influence the game results. Numerous machine learning techniques have been used to accomplish the goals.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128225260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Real-Time Artificial Mood-tracking and Health-monitoring System (RAMAHS) for people with mental illness and their Caregivers 用于精神疾病患者及其护理人员的实时人工情绪跟踪和健康监测系统(RAMAHS)
2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111897
Fida Fareesha, Chandanashree Y K, Gowthami V, R. Jayachandran, S. Kalathil
{"title":"Real-Time Artificial Mood-tracking and Health-monitoring System (RAMAHS) for people with mental illness and their Caregivers","authors":"Fida Fareesha, Chandanashree Y K, Gowthami V, R. Jayachandran, S. Kalathil","doi":"10.1109/ICRTEC56977.2023.10111897","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111897","url":null,"abstract":"Mental health has always been important and issues related to it have always been dangerous. Government has launched a lot of programs and campaigns for the awareness and for the help related to mental health. In this fast developing world, the big thing is technology which is used literally everywhere. Over the past few years there have been numerous developed technologies that could help people struggling with mental disorders. Along with the patients with mental illness, caregivers also face mental stress and health issues due to the stress faced by them on being with the family members with mental health disorders. In this paper, we discuss the various issues of mental health and the stress faced by their caregivers and the technology that is currently in use to monitor the patients with mental disorders. Existing health monitoring system lacks the monitoring of the mood swings of the patient and also the support for the caregiver. Here, we propose a real time artificial mood-tracking and health monitoring for both people with mental disorders and wide mood swings and their caregivers using various sensors. The proposed methodology is more accurate and unique as it monitors the brain chemical - dopamine level of the patient using biosensor, along with other vital health parameters and also provides measures to handle the worse situations.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130683668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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