Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047826
Deepa Joshi, T. Singh
In this day and age, X-rays are the principal instruments for assessing suspected fractures in humans. Expert radiologists are required to suspect the fractures by manually inspecting them, which is a time-consuming process. Automatic detection is beneficial, especially in under-resourced areas where scarce resources and experienced radiologists are observed. Wrist Fracture Dataset (WFD) and Surface Crack Dataset (SCD) were developed to detect and segment wrist bone fractures automatically. The number of wrist fracture images obtained from the Indian hospitals is 315, having 733 annotations/cracks, which is insufficient to produce accurate results using deep learning techniques. As a result, we included SCD for improved model generalization. WFD consists of 3,000 images collected by capturing the minute cracks from road, pavement, and walls, which has similar patterns as the bone fracture cracks. The proposed architecture is a modified version of mask-RCNN architecture where the surface crack dataset's weights are transferred to the wrist X-ray dataset for better model convergence. The results obtained from the modification done at the sub-architecture level (levels 1 and 2) are examined. Combining the modifications proposed at level 1 and level 2, we have obtained improved results against the standard mask-RCNN model for the wrist fracture dataset. We achieved an average precision of 92.278% and 79.003% for fracture detection and 77.445 and 52.156% for fracture segmentation on 50 0 and 75 0 scales, respectively.
{"title":"Novel Use of Deep Convolution Architecture Pre-Trained on Surface Crack Dataset to Localize and Segment Wrist Bone Fractures","authors":"Deepa Joshi, T. Singh","doi":"10.1109/SMART55829.2022.10047826","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047826","url":null,"abstract":"In this day and age, X-rays are the principal instruments for assessing suspected fractures in humans. Expert radiologists are required to suspect the fractures by manually inspecting them, which is a time-consuming process. Automatic detection is beneficial, especially in under-resourced areas where scarce resources and experienced radiologists are observed. Wrist Fracture Dataset (WFD) and Surface Crack Dataset (SCD) were developed to detect and segment wrist bone fractures automatically. The number of wrist fracture images obtained from the Indian hospitals is 315, having 733 annotations/cracks, which is insufficient to produce accurate results using deep learning techniques. As a result, we included SCD for improved model generalization. WFD consists of 3,000 images collected by capturing the minute cracks from road, pavement, and walls, which has similar patterns as the bone fracture cracks. The proposed architecture is a modified version of mask-RCNN architecture where the surface crack dataset's weights are transferred to the wrist X-ray dataset for better model convergence. The results obtained from the modification done at the sub-architecture level (levels 1 and 2) are examined. Combining the modifications proposed at level 1 and level 2, we have obtained improved results against the standard mask-RCNN model for the wrist fracture dataset. We achieved an average precision of 92.278% and 79.003% for fracture detection and 77.445 and 52.156% for fracture segmentation on 50 0 and 75 0 scales, respectively.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130075407","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10046944
Atul Mathur, R. Dwivedi, Rajul Rastogi
Novel computational tools based on ML schemes are useful in knowing the complex brain functions and its diseases. It was found during the study that differentiation among various neurological disorders is not easy task due to similarities in symptoms. This paper significantly examines and compares performances of many ML based methods to diagnose neurological illness—emphasized on Alzheimer's disease, Parkinson's disease and schizophrenia. The article provides the overview of computational intelligence methods evaluates and diverse performance metrics used to predict neurological disorders from different type of data.
{"title":"A Survey of Machine Learning Based Approaches for Neurological Disorder Predictions","authors":"Atul Mathur, R. Dwivedi, Rajul Rastogi","doi":"10.1109/SMART55829.2022.10046944","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046944","url":null,"abstract":"Novel computational tools based on ML schemes are useful in knowing the complex brain functions and its diseases. It was found during the study that differentiation among various neurological disorders is not easy task due to similarities in symptoms. This paper significantly examines and compares performances of many ML based methods to diagnose neurological illness—emphasized on Alzheimer's disease, Parkinson's disease and schizophrenia. The article provides the overview of computational intelligence methods evaluates and diverse performance metrics used to predict neurological disorders from different type of data.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129301005","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047792
S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross
One of its most serious diseases that may affect kids and teens is a cancerous tumor. Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated 11,700 individuals get a glioma diagnosis per year. When a person has a benign brains or CNS cancer, their five - year survival is around 36% for women and approximately 34% for men. There are several distinct types of brain cancers, including benign, aggressive, endocrine, and other types. The average lifespan of people should really be increased by using appropriate treatment, scheduling, and precise diagnosis. Mri scan is the most effective method for finding tumour (MRI). An large quantity of picture data is produced by scanners. The surgeon looks over these pictures. Algorithms (ML) and intelligent systems (AI)-based automation classification systems have repeatedly beaten hand categorisation in high accuracy. Therefore., offering a system can perform classification and tracking using Deep Learning Techniques such as Fully Convolutional Systems (CNN), Knn (ANN), (Template matching), and Transfer Learning (TL) would be helpful to physicians everywhere.
{"title":"Computational Intelligence Approach to Improve The Classification Accuracy of Brain Tumor Detection","authors":"S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross","doi":"10.1109/SMART55829.2022.10047792","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047792","url":null,"abstract":"One of its most serious diseases that may affect kids and teens is a cancerous tumor. Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated 11,700 individuals get a glioma diagnosis per year. When a person has a benign brains or CNS cancer, their five - year survival is around 36% for women and approximately 34% for men. There are several distinct types of brain cancers, including benign, aggressive, endocrine, and other types. The average lifespan of people should really be increased by using appropriate treatment, scheduling, and precise diagnosis. Mri scan is the most effective method for finding tumour (MRI). An large quantity of picture data is produced by scanners. The surgeon looks over these pictures. Algorithms (ML) and intelligent systems (AI)-based automation classification systems have repeatedly beaten hand categorisation in high accuracy. Therefore., offering a system can perform classification and tracking using Deep Learning Techniques such as Fully Convolutional Systems (CNN), Knn (ANN), (Template matching), and Transfer Learning (TL) would be helpful to physicians everywhere.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124546557","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047004
Divya Paikaray, G. Jethava
BC's high mortality and morbidity rates endanger female patients. Thus, a breast cancer detection method is essential. Logistic regression, DTs, random forests, and CNN predicted breast cancer. Predicting early breast cancer symptoms requires ML. This study uses three classification ML techniques. We'll evaluate each algorithm's performance and accuracy. Classification systems must carefully manage and preprocess unbalanced data. We'll train ML models on BC patient data. Performance and accuracy comparisons identify the best algorithm for this task. This study will compare BC classification models to determine the optimal approach. This study predicts BC classification system accuracy.
{"title":"ML based with Decision Tree Method for Classifying The Breast Cancer Level","authors":"Divya Paikaray, G. Jethava","doi":"10.1109/SMART55829.2022.10047004","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047004","url":null,"abstract":"BC's high mortality and morbidity rates endanger female patients. Thus, a breast cancer detection method is essential. Logistic regression, DTs, random forests, and CNN predicted breast cancer. Predicting early breast cancer symptoms requires ML. This study uses three classification ML techniques. We'll evaluate each algorithm's performance and accuracy. Classification systems must carefully manage and preprocess unbalanced data. We'll train ML models on BC patient data. Performance and accuracy comparisons identify the best algorithm for this task. This study will compare BC classification models to determine the optimal approach. This study predicts BC classification system accuracy.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131346490","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10046805
D. K. Sinha, S. Reddy
Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.
{"title":"Just Use a Perceptron to Anticipate Dry","authors":"D. K. Sinha, S. Reddy","doi":"10.1109/SMART55829.2022.10046805","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046805","url":null,"abstract":"Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121623440","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047167
C. Gupta, Vipin Kumar, K. Kumar
Management of the supply chain is essential for running any kind of organisation in this paper, in which we provide an overview of the developments in supply chain management. Following a review of the difficulties involved in managing supply chains, we give alternate definitions and major concerns linked to supply chain management. We then talk about considerable supply chain management inefficiencies. An overview of current research efforts and a discussion of impending supply chain management difficulties are provided as a conclusion.
{"title":"A Study on the Applications of Supply Chain Management","authors":"C. Gupta, Vipin Kumar, K. Kumar","doi":"10.1109/SMART55829.2022.10047167","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047167","url":null,"abstract":"Management of the supply chain is essential for running any kind of organisation in this paper, in which we provide an overview of the developments in supply chain management. Following a review of the difficulties involved in managing supply chains, we give alternate definitions and major concerns linked to supply chain management. We then talk about considerable supply chain management inefficiencies. An overview of current research efforts and a discussion of impending supply chain management difficulties are provided as a conclusion.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115904408","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10046907
Amit Jain, Muskan Kumari
Stress is considered as the leading problem in healthcare. This paper is about a brief review of machine learning Algorithms and IoT, and their roles in the prediction of stress. A lot of research has been done by researchers in the prediction of stress by taking reference to previous research we compare SVM and KNN accuracy and performanceon the basis of PSS (perceived stress scale), EDR and ECG. This paper discusses ML Techniques that are implemented on the Internet of things (IoT) nowadays. Also, emphasis has been laid on identifying the causes, symptoms of stress along with studying the existing Machine Learning algorithms related to Stress.
{"title":"Prediction of Stress using Machine Learning and IoT","authors":"Amit Jain, Muskan Kumari","doi":"10.1109/SMART55829.2022.10046907","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046907","url":null,"abstract":"Stress is considered as the leading problem in healthcare. This paper is about a brief review of machine learning Algorithms and IoT, and their roles in the prediction of stress. A lot of research has been done by researchers in the prediction of stress by taking reference to previous research we compare SVM and KNN accuracy and performanceon the basis of PSS (perceived stress scale), EDR and ECG. This paper discusses ML Techniques that are implemented on the Internet of things (IoT) nowadays. Also, emphasis has been laid on identifying the causes, symptoms of stress along with studying the existing Machine Learning algorithms related to Stress.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120891398","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10046959
Pardeep Kumar, Sanjay Arora
Distance-based definition of graph families the range in between nodes or sides here on network is known as the shortest route size between both two nodes or sides. The degree of a specific edge is defined as the total number pf triangles that surround that apex. The node e sequence's length level series () is the quantity of nodes but rather vertices at a length I from v, where () = 0(), 1(),…,()(). Here, utilizing their distance extent sequence, they have covered the creation and classification of total circles, cycles of extremely weird and now even dimensions, and complete PPI network 2. In addition, some of the findings have really been provided with methodologies.
{"title":"Graph Family Characterization using the Path Length Array","authors":"Pardeep Kumar, Sanjay Arora","doi":"10.1109/SMART55829.2022.10046959","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046959","url":null,"abstract":"Distance-based definition of graph families the range in between nodes or sides here on network is known as the shortest route size between both two nodes or sides. The degree of a specific edge is defined as the total number pf triangles that surround that apex. The node e sequence's length level series () is the quantity of nodes but rather vertices at a length I from v, where () = 0(), 1(),…,()(). Here, utilizing their distance extent sequence, they have covered the creation and classification of total circles, cycles of extremely weird and now even dimensions, and complete PPI network 2. In addition, some of the findings have really been provided with methodologies.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121166130","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 : 2022-12-16DOI: 10.1109/smart55829.2022.10047079
Vipin Kumar, Priyanka Jain
In the business area of India mergers and acquisitions are expanding fundamentally. Indian organizations are taking their oppositions to the next level by procuring unfamiliar organizations while permitting unfamiliar financial backers to put resources into India. The Indian business area is liable to relentless rivalry, subsequently, they have become inseparable from instruments that assist in enduring the market. Business rebuilding have frequently come about emphatically because of an expansion in the effectiveness and maintainability of the organizations. Because of globalization, numerous organizations advanced towards the Indian business area and the Indian organizations continued procuring unfamiliar foundations. Organizations are more worried about protecting their worth on the lookout because the business world has turned aggressive. Exchanges of offer or acquisition of any foundation request a computation of having fair worth which console partners and regulators. In these computation of having fair worth should be possible by different strategies. Paper talk about the valuation required during mergers and acquisitions.
{"title":"Valuation of Mergers and Acquisitions","authors":"Vipin Kumar, Priyanka Jain","doi":"10.1109/smart55829.2022.10047079","DOIUrl":"https://doi.org/10.1109/smart55829.2022.10047079","url":null,"abstract":"In the business area of India mergers and acquisitions are expanding fundamentally. Indian organizations are taking their oppositions to the next level by procuring unfamiliar organizations while permitting unfamiliar financial backers to put resources into India. The Indian business area is liable to relentless rivalry, subsequently, they have become inseparable from instruments that assist in enduring the market. Business rebuilding have frequently come about emphatically because of an expansion in the effectiveness and maintainability of the organizations. Because of globalization, numerous organizations advanced towards the Indian business area and the Indian organizations continued procuring unfamiliar foundations. Organizations are more worried about protecting their worth on the lookout because the business world has turned aggressive. Exchanges of offer or acquisition of any foundation request a computation of having fair worth which console partners and regulators. In these computation of having fair worth should be possible by different strategies. Paper talk about the valuation required during mergers and acquisitions.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121181363","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047540
Sagrika Goswami, Abhishek Dubey
In the contemporary work-from-home period and the previous Covid-19 times, fitness or, to put it another way, obesity, has emerged as a significant issue. Technology usage has suddenly increased and become ingrained in our daily lives. For the development of such individuals, we are developing the fitness application FITWORLD, which supports individuals in achieving their objectives by offering customised training and dietary regimens. Our proposal is based on research into the workout habits of many individuals with various objectives and BMIs. These guidelines are simple to follow and help boost immunity, which further guards against Covid. We are leveraging a variety of technologies and tools, including: •Android Studio •Kotlin •XML •Draw.io •Figma •Star UML •Firebase As a consequence, we are striving to create Fitworld, an app, employing the tools and technologies indicated above. By assisting individuals in maintaining a healthy lifestyle via the use of our app, we want to make our nation healthy and fit in the future.
{"title":"Fitness Industry Propelling on IoT","authors":"Sagrika Goswami, Abhishek Dubey","doi":"10.1109/SMART55829.2022.10047540","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047540","url":null,"abstract":"In the contemporary work-from-home period and the previous Covid-19 times, fitness or, to put it another way, obesity, has emerged as a significant issue. Technology usage has suddenly increased and become ingrained in our daily lives. For the development of such individuals, we are developing the fitness application FITWORLD, which supports individuals in achieving their objectives by offering customised training and dietary regimens. Our proposal is based on research into the workout habits of many individuals with various objectives and BMIs. These guidelines are simple to follow and help boost immunity, which further guards against Covid. We are leveraging a variety of technologies and tools, including: •Android Studio •Kotlin •XML •Draw.io •Figma •Star UML •Firebase As a consequence, we are striving to create Fitworld, an app, employing the tools and technologies indicated above. By assisting individuals in maintaining a healthy lifestyle via the use of our app, we want to make our nation healthy and fit in the future.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125952864","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}
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