2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)最新文献

Optical Text Translator from Images using Machine Learning 使用机器学习的图像光学文本翻译器

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844383

Shivani Joshi, Praveen Kumar Rai, Rajiv Kumar, Rikendra, Avinash Dwivedi

{"title":"Optical Text Translator from Images using Machine Learning","authors":"Shivani Joshi, Praveen Kumar Rai, Rajiv Kumar, Rikendra, Avinash Dwivedi","doi":"10.1109/CISES54857.2022.9844383","DOIUrl":"https://doi.org/10.1109/CISES54857.2022.9844383","url":null,"abstract":"In the actual world, when people go to a new location, they may have difficulties with language, signboards, or other kinds of communication. People in the digital age utilize Google Translate, Pocket Dictionary, and other similar applications. A signboard or other kind of notice may communicate important information or even act as a warning. Important information may be lost if the message is unavailable to individuals of different linguistic backgrounds; furthermore, visitors may struggle to carry out their duties in a new place if they do not comprehend the language spoken there. A portable dictionary, on the other hand, may be ineffective if users wish to translate a language in which words are not organized alphabetically. In another research, it is also understood in the same manner that users are unable to type the text of what they see. Because they are unable to comprehend the language despite the pocket dictionary and online translation service offered, people from various linguistic backgrounds may experience a breakdown in communication. The purpose of this article is to create an app that will translate information shown on a signboard into the language of the user's choice. When the user points their phone's camera at the signboard, the App takes a picture of it and then translates the text on the signboard.","PeriodicalId":284783,"journal":{"name":"2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127160946","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

Effective Motion planning and Navigation for Reconfigurable Mobile Robots using Modified A* Algorithm 基于改进A*算法的可重构移动机器人有效运动规划与导航

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844272

Karan Sehgal, M. Verma, Keshav, M. M. Rayguru, Shreyansh Upadhyaya

{"title":"Effective Motion planning and Navigation for Reconfigurable Mobile Robots using Modified A* Algorithm","authors":"Karan Sehgal, M. Verma, Keshav, M. M. Rayguru, Shreyansh Upadhyaya","doi":"10.1109/CISES54857.2022.9844272","DOIUrl":"https://doi.org/10.1109/CISES54857.2022.9844272","url":null,"abstract":"Robotic systems that can transform their structure while in operation are known as reconfigurable robots. The additional configuration flexibility makes them ideal for a variety of industrial applications involving motion planning, such as sanitizing, space vehicle maintenance, and surveillance. Every floor cleaning robot needs to have a coverage route planning strategy. Navigation and its planning in the case of a moving cleaning robot, using a grid map is the subject of this paper. An essential assumption has been made here, that the given autonomous vehicle is fully operational and has a consistent reactive navigation system. As a result, such topics are not covered in this article. The study introduces an enhancement to the conventional A* algorithm. These changes are particularly concerned with computational effort, reconfiguration time, and path efficiency. These were then tested in a simulation-based circumstance with varying degrees of environmental complexity, which demonstrated the utility of the proposed algorithm. The results show that the suggested technique showcases a good performance in terms of the area covered and the distance traveled.","PeriodicalId":284783,"journal":{"name":"2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123318458","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

Stroke Disease Prediction based on ECG Signals using Deep Learning Techniques 基于深度学习技术的心电信号中风疾病预测

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844403

M. Anand Kumar, N. Abirami, M. S. Guru Prasad, M. Mohankumar

{"title":"Stroke Disease Prediction based on ECG Signals using Deep Learning Techniques","authors":"M. Anand Kumar, N. Abirami, M. S. Guru Prasad, M. Mohankumar","doi":"10.1109/CISES54857.2022.9844403","DOIUrl":"https://doi.org/10.1109/CISES54857.2022.9844403","url":null,"abstract":"Stroke-related diseases are rapidly increasing day by day due to the changes in environmental factors including lifestyles, food habits, and stress-related working cultures. According to a recent report from World Health Organization (WHO), Stroke is the second largest disease after cardiovascular disease that leads to death. Early diagnosis of stroke-related diseases was one of the major requirements for patients as well as medical professionals. Deep learning techniques are one of those methods that are suitable for stroke disease diagnosis when deployed properly. This research proposed a medical framework approach for the detection of abnormalities in the ECG data related to stroke diseases. ECG plays a vital role in the detection of several stroke risk factors including left ventricular hypertrophy. This work proposed a framework based on Long Short-term Memory (LSTM) network for predicting stroke-related diseases with ECG data and other parameters. The experimental results show that 90% accuracy results with the combination of ECG data and the Deep learning approach. Finally, Receiver operating characteristic (ROC) curves has shown promising results. This work also proved that the model is suitable for the early detection of stroke-related diseases with minimum overhead in terms of efficiency.","PeriodicalId":284783,"journal":{"name":"2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122478636","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: 7

Efficient Crop Yield Prediction of Kharif Crop using Deep Neural Network 基于深度神经网络的作物产量高效预测

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844369

Preeti Saini, Bharti Nagpal

引用次数: 0

Smart Automatic Accident Detection & Information System 智能自动事故检测与信息系统

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844371

S. Rathor, Prateek Dubey, Shivam Samadhiya

{"title":"Smart Automatic Accident Detection & Information System","authors":"S. Rathor, Prateek Dubey, Shivam Samadhiya","doi":"10.1109/CISES54857.2022.9844371","DOIUrl":"https://doi.org/10.1109/CISES54857.2022.9844371","url":null,"abstract":"Our lives have been made easier by the advancement of technology and infrastructure. The introduction of technology has also led to an increase in traffic risks and accidents on the road, resulting in significant loss of life and property due to inadequate emergency resources. This paper consists of a few automated devices that detect accidents and notify responsible person. This technology may be used to pinpoint the location of the accident, directing medical assistance there promptly. The system is equipped with an accelerometer, GPS, and a GSM module for message transmission. Accelerometers detect abrupt changes in the magnitude, acceleration, and speed of a vehicle’s axis. Additionally, a switch is provided to halt the transmission of a message in the unlikely event that there is no casualty; this can save the responsible person’s valuable time. The GSM module delivers an alert message to the mobile device informing it of the accident’s location. The location of the accident is indicated via a Google Maps link obtained from the GPS module’s latitude and longitude. After confirming the situation, essential actions will be done, which will aid in obtaining rescue assistance in a timely manner and so saving a precious human life. In addition to detecting alcoholic drivers and fires in vehicles, this paper can also produce alerts for those situations.","PeriodicalId":284783,"journal":{"name":"2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122148061","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

Transient Switching Study for 120 MVAr Variable Shunt Reactor at 220 kV Substation 220kv变电站120mvar可变并联电抗器暂态开关研究

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844359

Ayyaj S Maner, Amol Salunkhe, Raiju Hassan, Sonu Karekar, Mahesh Ambardekar, Arvindkumar Sharma

引用次数: 0

Mid–Point Sorting Algorithm:A New Way to Sort 中点排序算法:一种新的排序方法

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844386

Anjali Garg, Varun M. Patel, Divya Mishra

引用次数: 0

Facial Emotion Recognition 面部情绪识别

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844366

Japleen Kaur, Jhalak Saxena, Jayesh Shah, Fahad, S. Yadav

引用次数: 0

Plant Disease Classification Using Deep Learning Framework 基于深度学习框架的植物病害分类

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844352

Ayushi Verma, Shashi Shekhar, Hitendra Garg

{"title":"Plant Disease Classification Using Deep Learning Framework","authors":"Ayushi Verma, Shashi Shekhar, Hitendra Garg","doi":"10.1109/CISES54857.2022.9844352","DOIUrl":"https://doi.org/10.1109/CISES54857.2022.9844352","url":null,"abstract":"This Agriculture is the main source of livelihood in India. Major destruction occurs in the field of agriculture is due to the diseases in plants. Disease causes heavy devastation in the field of farming. An automatic system needs to be developed for the prevention of crops at initial stages from diseases. The automatic system will diagnose plant disease and identify its category. The paper proposed an automatic disease detection system which recognize the category of the diseases and healthiness in plants. The classification of diseases have done on the basis of symptoms appeared on the leaf surface. The paper broadly categorises the diseases into three categories such as fungal, bacterial and viral. The deep learning approach namely Convolutional Neural Network is used for the classification of the diseases. The dataset consists of 64963 number of samples in which training has performed on 80% of the samples of dataset and validation has performed on 20% of the samples of dataset. The simulation results shows that the convolutional neural network that have been trained on given dataset acquired an accuracy of 99.12%.","PeriodicalId":284783,"journal":{"name":"2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348821","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

Modelling and Simulation of Charging Based on Solar/Grid Powered Electric Vehicle 基于太阳能/电网的电动汽车充电建模与仿真

2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) Pub Date : 2022-05-20 DOI: 10.1109/CISES54857.2022.9844405

Narendra Kumar, R. Soni

引用次数: 1