2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)最新文献_第6页

Attendance Marking System using Periocular Recognition with Temperature Monitoring (ASPR) 基于眼周识别和温度监测的考勤系统

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596524

KM Abhinav, Renil Aneesh, Priyamol James, Angel Varghese

{"title":"Attendance Marking System using Periocular Recognition with Temperature Monitoring (ASPR)","authors":"KM Abhinav, Renil Aneesh, Priyamol James, Angel Varghese","doi":"10.1109/icrito51393.2021.9596524","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596524","url":null,"abstract":"Of late the COVID pandemic has necessitated authorities to make sure that every candidates are being worn mask. So, this forces to quit from conventional attendance marking systems which only relies on face recognition for biometric identification that involves close proximity or body contact. Wearing of masks can definitely occlude a major area of face. So the proposed project aims at using periocular recognition for biometric identification. The system proposed uses a pre-trained Convolution Neural Network (CNN) model that is VGG16 trained on ImageNet dataset to achieve the target of periocular recognition. Here it involves only a smaller region of interest and so external factors cause only less constraints to periocular recognition. Mask detection, which is an image classification phase, is done with MobileNet V2. This includes training which serialises face mask detectors to disk and deployment which outputs images as ‘with mask’ or ‘without mask’ [1] [2]. Non-contact IR sensor, MLX90614 IR sensor will automatically detect body temperature to determine whether the candidate's temperature is exceeding a threshold value.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122194974","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

Smart Education Platform to Enhance Student Learning Experience during COVID-19 新冠肺炎期间提升学生学习体验的智慧教育平台

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596433

V. R. Naidu, S. Bhatia, Raza Hasan, Baldev Singh, K. Jesrani, Aparna Agarwal

{"title":"Smart Education Platform to Enhance Student Learning Experience during COVID-19","authors":"V. R. Naidu, S. Bhatia, Raza Hasan, Baldev Singh, K. Jesrani, Aparna Agarwal","doi":"10.1109/icrito51393.2021.9596433","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596433","url":null,"abstract":"The community of learners of these days are highly motivated to use the latest trends in education due to the current demand of the education sector. When the Smart education scenario is observed, various advancements in Smart cities play a vital role. Situations like the current pandemic of COVID-19 has forced the entire community of learners to learn through online mode and most of the educational institutions are opting for this mode for a safe learning environment. Several tools are available to support this of which Zoom is one of the most popular online tools and many institutions are using Zoom for online activities related to teaching and learning practice. This paper shows the results of one of such practice implemented during the current situation including the infrastructure of Video Streaming Server utilizing recorded zoom meetings and Moodle. Data is collected by means of a survey conducted among the staff and students. Results have revealed that this practice has shown a good impact on flexibility, accessibility and innovation on learners. The engagement has a scope for improvement to motivate the learners.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122260258","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

Dynamic Performance Enhancement Of Electric Vehicle Drive 电动汽车驱动的动态性能提升

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596190

Asha Singh, P. Choudekar, Ruchira

{"title":"Dynamic Performance Enhancement Of Electric Vehicle Drive","authors":"Asha Singh, P. Choudekar, Ruchira","doi":"10.1109/icrito51393.2021.9596190","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596190","url":null,"abstract":"Modeling and simulation of Electric Vehicles has garnered increased attention from researchers as Electric Vehicles become a promising solution for sustainable and cleaner energy discharge in transportation. The aim of this research work ‘Dynamic Performance enhancement of Electric Vehicle Drive’ is to construct an electric vehicle drive model using a PI controller with the assistance of a simulation tool, which in this work is MATLAB Simulink. This model examines power flow in regenerative motoring using a standard electric vehicle drive configuration. For detailed input load conditions, this model can be used to evaluate the electric drive's power flow and proficiency. Some of the most important factors were listed, while others were depicted as ideal. The system quality and power flow were governed using a Simulink model that was constructed and then utilised to control a set of driving and regeneration speed and torque conditions. This study is to seem into the power flow calculation in order that the quantity of electricity is in accordance with the requirements of electrical vehicle.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040842","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

Prediction of Heart Disease through Machine Learning Algorithms and Techniques 通过机器学习算法和技术预测心脏病

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596319

Anand Kumar Shukla

{"title":"Prediction of Heart Disease through Machine Learning Algorithms and Techniques","authors":"Anand Kumar Shukla","doi":"10.1109/icrito51393.2021.9596319","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596319","url":null,"abstract":"Heart disease, by preference popular as CVD (Cardio Vascular Disease), encases differing environment that effect the soul and it is the basic physical foundation of end of life general from the period of the past some decades. And yes it involved with many risk determinant fashionable illness (disease) of the heart and a required some times to catch correct, trustworthy, and sensible approaches to create an early identification of problem to reach a goal prompt persons running an organization of the disease. Data excavating happen a usually used method for subject to series of actions to achieve result very large data fashionable the healthcare rule. Researchers put into use assorted data excavating and machine intelligence method to analyses huge complex healing information in visible form, portion of food healthcare professionals to express an outcome in advance disease of the heart. This paper stating beliefs presents miscellaneous attributes related to disease of the heart, and the model ahead of action of supervised knowledge algorithms as Naïve- Bayes, resolution reached abundant plant placed within in bark and peeling leaves, K-nearest neighbor, and haphazard area with a large number of trees invention. It uses the existent dataset from the Cleveland collection of data of UCI storage place of ailment of the soul person essential nature medicate for healing question. The basic document file make up 303 instances and 76 attributes. Of these 76 attributes, only 14 attributes happen deliberate for experiment, influential to plan the acting of miscellaneous algorithms. This long person actively learning essay aims to conceive the chance of something happening of something occurrence of nurture ailment of the soul fashionable the human being existence treated for healing question. The results pretend to be that the maximum precision or correctness score occur brings to profitable judgment following K-expected neighbor.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121159938","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

Human Activity Recognition based on Smartphone Sensors- A Comparative Study 基于智能手机传感器的人体活动识别——比较研究

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596305

Lokesh Dhammi, P. Tewari

{"title":"Human Activity Recognition based on Smartphone Sensors- A Comparative Study","authors":"Lokesh Dhammi, P. Tewari","doi":"10.1109/icrito51393.2021.9596305","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596305","url":null,"abstract":"HAR has become a leading area of research because of its noteworthy contribution in applications that aim to improve the quality and standard of life. HAR system also contributes to health and safety in smart cities, privacy and security, etc., which directly or indirectly improves the quality of service towards society. In this study, we studied the different techniques used for the detection of human activities using built-in sensors in smartphones. In all these techniques raw data is collected using gyroscope and accelerometer sensors inbuilt in the smartphones and then different data preprocessing steps are implemented to clean the data. Important features are extracted using different feature extraction techniques. Finally, the “Machine Learning” or “Deep Learning” models are trained which can accurately recognise the activities. We analyze several modern deep learning techniques which provide excellent results due to their capability of learning deep features. Also, we have analyzed the research gaps in the current literature which provides a sound understanding to identify the future work required in this area of research.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116226111","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

Automated Door System Using Arduino For Crowd Management 基于Arduino的人群管理自动门系统

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596388

Pranav Sharma, Akshet Patel

{"title":"Automated Door System Using Arduino For Crowd Management","authors":"Pranav Sharma, Akshet Patel","doi":"10.1109/icrito51393.2021.9596388","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596388","url":null,"abstract":"According to the COVID-19 Weekly Epidemiological Update released by WHO on 4th May 2021, India accounted for 46% of the new global Covid-19 cases, with over 29.4 million Indians contracted with the deadly virus in totality. Additionally, India accounted for 26% of global death in that week, with over 0.37 million citizens having succumbed to Covid-19 since the pandemic has begun. Furthermore, a data suggested that around 20% of people who contract coronavirus show no symptoms and being around them could be a great risk. Ignorance towards the government guidelines about social gathering has resulted in a huge spike of cases. Thus, taking all of this into consideration the objective of the project “Automated Door System Using Arduino for Crowd Management” is to reduce or to an extent totally eliminate the manual work that goes into opening and closing doors using a PIR sensor to detect people and an Arduino Uno as the microcontroller. Furthermore, we intend to only allow a certain number of restricted people in the room, in accordance with the government's social distancing guidelines, in order to help stop or reduce the spread of the deadly virus.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124949239","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

A Review of Trash Collecting and Cleaning Robots 垃圾收集和清洁机器人的研究进展

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596551

Sushma Chandra, Medhasvi Kulshreshtha, Princy Randhawa

引用次数: 1

Brain Tumour Detection on BraTS 2020 Using U-Net 基于U-Net的2020年BraTS脑肿瘤检测

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596530

BharathSimhaReddy Maram, Pooja Rana

引用次数: 1

Garbage Detection and Path-Planning in Autonomous Robots 自主机器人的垃圾检测与路径规划

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596382

S. S. Chandra, Medhasvi Kulshreshtha, Princy Randhawa

引用次数: 3

Recognition and classification of mathematical expressions using machine learning and deep learning methods 使用机器学习和深度学习方法的数学表达式识别和分类

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596161

Sakshi, V. Kukreja, S. Ahuja

引用次数: 8