Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10059632
G. Madhuri, J. Selvakumar, K. S. Krishna
In this survey paper, various methodologies adopted in skew minimization of Clock tree are addressed and the results of these methodologies are compared. Due to fast technology growth and complicated design circumstances, Clock skew reduction has become a tedious task for designers. Effective clock skew optimization improves the design performance. Minimizing clock skew among various corners becomes more difficult in current SoCs.
{"title":"Performance Analysis on Skew Optimized Clock Tree Synthesis","authors":"G. Madhuri, J. Selvakumar, K. S. Krishna","doi":"10.1109/ICERECT56837.2022.10059632","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10059632","url":null,"abstract":"In this survey paper, various methodologies adopted in skew minimization of Clock tree are addressed and the results of these methodologies are compared. Due to fast technology growth and complicated design circumstances, Clock skew reduction has become a tedious task for designers. Effective clock skew optimization improves the design performance. Minimizing clock skew among various corners becomes more difficult in current SoCs.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125790973","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}
The quantity of internet businesses providing tribal clothes is constantly increasing, and people tend to exaggerate how often they shop at such sites. However, we are concerned about the authenticity of the outfits. The study recommends using Convolutional Neural Networks (CNN) to automatically identify and categorize authentic images of particular tribal dresses used by some Bangladeshi tribes into predetermined categories. The study's impetus comes from the expansion of commerce and the desire to spread these traditional clothes over the globe. In order to categorize the clothing, we obtained images from actual tribal residences, shops, and a few online marketplaces. To that end, we made an effort to provide a dataset we've labeled “TribalBd,” which has 680 samples, including six different classes. Then, use the YOLOv5, YOLOv6, and YOLOv7 models to put these datasets for detection and classification on our CNN. As a means of evaluating the efficacy of our model, we have experimented with a number of different CNN topologies and tweaks. We put the model through its tests with YOLOv6 and YOLOv7. YOLOv5 achieved the best results among these models. The final result shows that the YOLOv6 model gives 86.24%, the YOLOv7 model gives 71.28% accuracy whereas YOLOv5 gives 89.97% accuracy in classifying the images in the training and testing sets which are best compared to the other two models.
{"title":"An Automatic System for Identifying and Categorizing Tribal Clothing Based on Convolutional Neural Networks","authors":"Ashraful Islam, Tuhin Chowdhury, Mehrab Hossain, Nafiz Nahid, Ariful Islam Rifat","doi":"10.1109/ICERECT56837.2022.10060409","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060409","url":null,"abstract":"The quantity of internet businesses providing tribal clothes is constantly increasing, and people tend to exaggerate how often they shop at such sites. However, we are concerned about the authenticity of the outfits. The study recommends using Convolutional Neural Networks (CNN) to automatically identify and categorize authentic images of particular tribal dresses used by some Bangladeshi tribes into predetermined categories. The study's impetus comes from the expansion of commerce and the desire to spread these traditional clothes over the globe. In order to categorize the clothing, we obtained images from actual tribal residences, shops, and a few online marketplaces. To that end, we made an effort to provide a dataset we've labeled “TribalBd,” which has 680 samples, including six different classes. Then, use the YOLOv5, YOLOv6, and YOLOv7 models to put these datasets for detection and classification on our CNN. As a means of evaluating the efficacy of our model, we have experimented with a number of different CNN topologies and tweaks. We put the model through its tests with YOLOv6 and YOLOv7. YOLOv5 achieved the best results among these models. The final result shows that the YOLOv6 model gives 86.24%, the YOLOv7 model gives 71.28% accuracy whereas YOLOv5 gives 89.97% accuracy in classifying the images in the training and testing sets which are best compared to the other two models.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125820478","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060124
Jinu Thomas, V. Ulagamuthalvi
Mouth-related pathologies represent an important challenge for public authorities. To develop a methodology, through studies on Computer Vision techniques, for the automatic identification of dental cysts in panoramic radiography images, providing Dental professionals with an alternative to aid in the interpretation of these images. For this purpose, two CNN architectures were analyzed for classification and experimentation using image pre-processing techniques. One such proposal, using morphological contrast, had a better performance, with a precision of 0.937 and an F1 score of 0.847.
{"title":"Automatic Detection of Dental Cysts in Panoramic Radiography Images using Preprocessing Techniques and Convolutional Neural Networks","authors":"Jinu Thomas, V. Ulagamuthalvi","doi":"10.1109/ICERECT56837.2022.10060124","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060124","url":null,"abstract":"Mouth-related pathologies represent an important challenge for public authorities. To develop a methodology, through studies on Computer Vision techniques, for the automatic identification of dental cysts in panoramic radiography images, providing Dental professionals with an alternative to aid in the interpretation of these images. For this purpose, two CNN architectures were analyzed for classification and experimentation using image pre-processing techniques. One such proposal, using morphological contrast, had a better performance, with a precision of 0.937 and an F1 score of 0.847.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124676967","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060671
V. Yatnalli, Saroja S. Bhusare, K. M., Akshatha Naik, Ashwini T, Dakhshayani, Chandana D
Multipath fading affects the radio communication links in one form or another. Rayleigh and Rician are the two types of multipath fading channels. During the transmission of data over these channels, the images are affected by many types of noise similar to Additive White Gaussian Noise (AWGN), Impulse Noise (IN) or the combination of both called as “mixed noise”. Removal of such noise is a critical and challenging work. The noise spreading in this case does not have any predefined model and due to this, the quality of the image further reduces. In the proposed method, the mixed noise is removed using Weighted Encoding with Sparse Nonlocal Regularization (WESNR). The Weighted Encoding technique performs better when compared to the existing image denoising methods. The parameters, PSNR and SSIM are considered to compare the performance of Adaptive Median Filter (AMF) and WESNR.
{"title":"Restoration of Images Corrupted by Multipath Fading Channel with Weighted Encoding","authors":"V. Yatnalli, Saroja S. Bhusare, K. M., Akshatha Naik, Ashwini T, Dakhshayani, Chandana D","doi":"10.1109/ICERECT56837.2022.10060671","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060671","url":null,"abstract":"Multipath fading affects the radio communication links in one form or another. Rayleigh and Rician are the two types of multipath fading channels. During the transmission of data over these channels, the images are affected by many types of noise similar to Additive White Gaussian Noise (AWGN), Impulse Noise (IN) or the combination of both called as “mixed noise”. Removal of such noise is a critical and challenging work. The noise spreading in this case does not have any predefined model and due to this, the quality of the image further reduces. In the proposed method, the mixed noise is removed using Weighted Encoding with Sparse Nonlocal Regularization (WESNR). The Weighted Encoding technique performs better when compared to the existing image denoising methods. The parameters, PSNR and SSIM are considered to compare the performance of Adaptive Median Filter (AMF) and WESNR.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124735948","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060101
Abhilash Kumar Saxena, R. Mathur
With the present IT, the sky is the limit on the web through sent thinking, permitting us to make, coordinate, use, and adjust sites, associations, and cutoff points. Most frequently, cryptography is used. Cryptography is the investigation of putting together figures, block figures, stream codes, and hash powers. Security associations like underwriting, accessibility, assurance, legitimacy, and non-repudiation ought to be upheld by cryptographic procedures in the cloud. It offers an attractive design with a large information portion to ensure the security of these organizations. The purpose of this work is to provide guidance on how best to address the security of scattered storage using a combination of hashing and encryption functions. Using Netbeans IDE 8.0.2, a JDK 1.7 device, and EyeOS 2.6 as the cloud tier, he proposes to perform his two calculations of Rivest-Shamir-Adleman and the Huge Level Encryption Standard on secure hash gauges. increase. This completes on Ubuntu 15.03.
在当今的信息技术下，通过发送思维，网络是无限的，允许我们制作、协调、使用和调整站点、关联和截止点。最常用的是密码学。密码学是对数字、块数字、流代码和哈希能力的研究。安全关联，如承销、可访问性、保证、合法性和不可抵赖性，应该由云中的加密过程来维护。它提供了一个有吸引力的设计与大的信息部分，以确保这些组织的安全性。这项工作的目的是为如何使用散列和加密功能的组合来最好地解决分散存储的安全性提供指导。使用Netbeans IDE 8.0.2、JDK 1.7设备和EyeOS 2.6作为云层，他建议在安全哈希表上执行Rivest-Shamir-Adleman和Huge Level Encryption Standard的两个计算。增加。这在Ubuntu 15.03上完成。
{"title":"An Enhancing the Security of Cloud Data via an Attribute-Based Encryption Model and Linked Hashing","authors":"Abhilash Kumar Saxena, R. Mathur","doi":"10.1109/ICERECT56837.2022.10060101","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060101","url":null,"abstract":"With the present IT, the sky is the limit on the web through sent thinking, permitting us to make, coordinate, use, and adjust sites, associations, and cutoff points. Most frequently, cryptography is used. Cryptography is the investigation of putting together figures, block figures, stream codes, and hash powers. Security associations like underwriting, accessibility, assurance, legitimacy, and non-repudiation ought to be upheld by cryptographic procedures in the cloud. It offers an attractive design with a large information portion to ensure the security of these organizations. The purpose of this work is to provide guidance on how best to address the security of scattered storage using a combination of hashing and encryption functions. Using Netbeans IDE 8.0.2, a JDK 1.7 device, and EyeOS 2.6 as the cloud tier, he proposes to perform his two calculations of Rivest-Shamir-Adleman and the Huge Level Encryption Standard on secure hash gauges. increase. This completes on Ubuntu 15.03.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127304310","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10059773
Shreyas S Korti, Suvarna G. Kanakaraddi
Depression is the one of the most seviour mental issue that the people of world-wide are irrelevant of their ages gender caste and races‥etc. In this modern communication world peoples are more comport to express their thoughts in front of social media almost every day. The main agenda of this paper is to propose the data-analytics based model to detect depressed tweeter tweets of the peoples. In this paper then data is going to collect from different user's posted tweets from most popular social-media website like twitter. The depression level can be identified based on the tweets of the users in social-media. The standard methods to detect depression of the users via tweets which is in the form of structured, these methods needs a larger amount of the data from the users. Now a day's social media platform like twitter. Twitter has become more popular to express their views and their emotions in the form of tweets. The data screening can be done based on tweets it shows depressive symptoms of the users. By using machine learning technique we are going to do pre-processing of the data collected from the users. And even using Recurrent neural network (RNN) and NLP techniques, LSTM Deep-learning techniques to identify the depressed tweets in a more convenient manner.
{"title":"Depression detection from Twitter posts using NLP and Machine learning techniques","authors":"Shreyas S Korti, Suvarna G. Kanakaraddi","doi":"10.1109/ICERECT56837.2022.10059773","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10059773","url":null,"abstract":"Depression is the one of the most seviour mental issue that the people of world-wide are irrelevant of their ages gender caste and races‥etc. In this modern communication world peoples are more comport to express their thoughts in front of social media almost every day. The main agenda of this paper is to propose the data-analytics based model to detect depressed tweeter tweets of the peoples. In this paper then data is going to collect from different user's posted tweets from most popular social-media website like twitter. The depression level can be identified based on the tweets of the users in social-media. The standard methods to detect depression of the users via tweets which is in the form of structured, these methods needs a larger amount of the data from the users. Now a day's social media platform like twitter. Twitter has become more popular to express their views and their emotions in the form of tweets. The data screening can be done based on tweets it shows depressive symptoms of the users. By using machine learning technique we are going to do pre-processing of the data collected from the users. And even using Recurrent neural network (RNN) and NLP techniques, LSTM Deep-learning techniques to identify the depressed tweets in a more convenient manner.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129136468","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060430
P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.
The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.
{"title":"Plant foliage Recognition based on Classification using Artificial Neural Network","authors":"P. G K, Virupakshaiah H K, B. P. T., A. Karegowda, Tejaswini K M, K. K.","doi":"10.1109/ICERECT56837.2022.10060430","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060430","url":null,"abstract":"The state-of-the-art method to find the pictographic four types of foliage (flower, fruit, medical and tree) identification is proposed. Foliage is represented by a boundary of local feature using edge detection, followed by applying convex hull algorithm. In the second phase, ANN has been applied for simulating the system using the features identified in first phase. The proposed work resulted in an average identification rate of 96.75% and 94% with training and test data.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128037840","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060720
C. Manjunath, Rohit Singh
Gliomas, the most widely recognized sort of threatening cerebrum growth, are on the ascent and are progressively being identified at standard specialist visits. Attractive Reverberation Imaging (X-ray) is regularly utilized in the discovery and conclusion of cerebrum growths. Consequently, in the clinical space, there is a requirement for mechanized and exact division methods to decrease the weight of time and intricacy of errands. To beat this trouble, various Profound Learning techniques have been presented, including Convolutional Brain Organizations (CNN) and Completely Associated Organizations (FCN), which have shown empowering division results on various datasets. Ongoing examination has shown that FCNs like U-Net can outflank cutting edge strategies in division errands and can be adjusted to address a great many spaces. Here, we propose a change to a current exchange learning technique and test it on the Cerebrum Growth Division (Whelps) 2020 dataset, where it performs hardly better compared to the pattern.
{"title":"A Segmentation of Brain Tissue Using Transfer Learning","authors":"C. Manjunath, Rohit Singh","doi":"10.1109/ICERECT56837.2022.10060720","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060720","url":null,"abstract":"Gliomas, the most widely recognized sort of threatening cerebrum growth, are on the ascent and are progressively being identified at standard specialist visits. Attractive Reverberation Imaging (X-ray) is regularly utilized in the discovery and conclusion of cerebrum growths. Consequently, in the clinical space, there is a requirement for mechanized and exact division methods to decrease the weight of time and intricacy of errands. To beat this trouble, various Profound Learning techniques have been presented, including Convolutional Brain Organizations (CNN) and Completely Associated Organizations (FCN), which have shown empowering division results on various datasets. Ongoing examination has shown that FCNs like U-Net can outflank cutting edge strategies in division errands and can be adjusted to address a great many spaces. Here, we propose a change to a current exchange learning technique and test it on the Cerebrum Growth Division (Whelps) 2020 dataset, where it performs hardly better compared to the pattern.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129956841","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}
Automation enables organizations to manage complicated workloads and processes with ease which increases efficiency and saves time. One such tool is automated hiring which accelerates the process by eliminating the requirement for the recruiter to be present in person. This study proposes an innovative approach that includes all steps of a standard interview with proper monitoring, providing the candidate with an experience similar to a true face-to-face interview while ensuring no cheating occurs. The resume short lister uses natural language processing (NLP) to rate resumes based on job requirements and stores candidate data in a database for future communication. The interview bot uses deepfake technology to provide the user with a realistic experience. Using similarity metrics, questions are asked based on data retrieved from the resume as well as user responses to prior questions. The software would finally analyze the data collected to determine the right choice for the position offered. The entire procedure is monitored by extracting information from the camera during the interview to prevent cheating, and the candidate is disqualified in case of any malpractice.
{"title":"An End to End Solution For Automated Hiring","authors":"Yash Chaudhari, Prathamesh Jadhav, Yashvardhan Gupta","doi":"10.1109/ICERECT56837.2022.10060436","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060436","url":null,"abstract":"Automation enables organizations to manage complicated workloads and processes with ease which increases efficiency and saves time. One such tool is automated hiring which accelerates the process by eliminating the requirement for the recruiter to be present in person. This study proposes an innovative approach that includes all steps of a standard interview with proper monitoring, providing the candidate with an experience similar to a true face-to-face interview while ensuring no cheating occurs. The resume short lister uses natural language processing (NLP) to rate resumes based on job requirements and stores candidate data in a database for future communication. The interview bot uses deepfake technology to provide the user with a realistic experience. Using similarity metrics, questions are asked based on data retrieved from the resume as well as user responses to prior questions. The software would finally analyze the data collected to determine the right choice for the position offered. The entire procedure is monitored by extracting information from the camera during the interview to prevent cheating, and the candidate is disqualified in case of any malpractice.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121422102","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}
Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060830
Indira Priyadarsini, B. Tejaswini, Ashok Kumar, I.S. Manochitra, I. S. Chakrapani, K. Alaskar
In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT -based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.
{"title":"IoT Based Mobile App for Continuous Health Monitoring of the Person","authors":"Indira Priyadarsini, B. Tejaswini, Ashok Kumar, I.S. Manochitra, I. S. Chakrapani, K. Alaskar","doi":"10.1109/ICERECT56837.2022.10060830","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060830","url":null,"abstract":"In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT -based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121035044","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：