The digitization of financial systems has brought unprecedented convenience, but it has also increased fraud. This article explores the important intersection of cybersecurity and fraud detection in financial transactions. As the need to effectively combat fraud increases, he explores a variety of cybersecurity approaches and technologies. This article examines advanced technologies such as data mining, machine learning, biometric authentication, and blockchain through a comprehensive review of existing literature. It also highlights the challenges and limitations faced by modern fraud detection methodologies, including sophisticated cyberattacks and regulatory issues. By recognizing these challenges, stakeholders can work to implement holistic solutions that address both technical and regulatory aspects. Ultimately, the purpose of this document is to provide practical guidance for strengthening fraud detection capabilities, strengthening financial systems, and protecting consumer interests in the digital economy.
{"title":"Enhancing Fraud Detection in Financial Transactions through Cyber Security Measures","authors":"Vishva Gandhi, Tirthesh Gajjar","doi":"10.32628/cseit2410281","DOIUrl":"https://doi.org/10.32628/cseit2410281","url":null,"abstract":"The digitization of financial systems has brought unprecedented convenience, but it has also increased fraud. This article explores the important intersection of cybersecurity and fraud detection in financial transactions. As the need to effectively combat fraud increases, he explores a variety of cybersecurity approaches and technologies. This article examines advanced technologies such as data mining, machine learning, biometric authentication, and blockchain through a comprehensive review of existing literature. It also highlights the challenges and limitations faced by modern fraud detection methodologies, including sophisticated cyberattacks and regulatory issues. By recognizing these challenges, stakeholders can work to implement holistic solutions that address both technical and regulatory aspects. Ultimately, the purpose of this document is to provide practical guidance for strengthening fraud detection capabilities, strengthening financial systems, and protecting consumer interests in the digital economy.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"3 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681351","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}
Computer vision is the field of computer science in which computers are made capable to see and recognize like human being. Deep learning is using multiple layers for the purpose of understanding and recognizing various objects. Deep Simple Real Time Tracker is the area in which the objects are tracked in real time from multiple images and videos. Many researchers have contributed to the field and various algorithms have been proposed. The current study presents the deep SORT related studies in which the various algorithms have been presented for the sake of understanding and starting point for the researchers interested in computer vision and deep sorting. The single shot detection, feature extraction, have been explained along with the research conducted. Feature selection and extraction, matching recognition, object tracking through frames have been appended to the current study.
{"title":"Deep SORT Related Studies","authors":"Abdul Majid, Qinbo Qinbo, Saba Brahmani","doi":"10.32628/cseit2410230","DOIUrl":"https://doi.org/10.32628/cseit2410230","url":null,"abstract":"Computer vision is the field of computer science in which computers are made capable to see and recognize like human being. Deep learning is using multiple layers for the purpose of understanding and recognizing various objects. Deep Simple Real Time Tracker is the area in which the objects are tracked in real time from multiple images and videos. Many researchers have contributed to the field and various algorithms have been proposed. The current study presents the deep SORT related studies in which the various algorithms have been presented for the sake of understanding and starting point for the researchers interested in computer vision and deep sorting. The single shot detection, feature extraction, have been explained along with the research conducted. Feature selection and extraction, matching recognition, object tracking through frames have been appended to the current study.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140685290","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}
In the pursuit of precise forecasts in machine learning-based breast cancer categorization, a plethora of algorithms and optimizers have been explored. Convolutional Neural Networks (CNNs) have emerged as a prominent choice, excelling in discerning hierarchical representations in image data. This attribute renders them apt for tasks such as detecting malignant lesions in mammograms. Furthermore, the adaptability of CNN architectures enables customization tailored to specific datasets and objectives, enhancing early detection and treatment strategies. Despite the efficacy of screening mammography, the persistence of false positives and negatives poses challenges. Computer-Aided Design (CAD) software has shown promise, albeit early systems exhibited limited improvements. Recent strides in deep learning offer optimism for heightened accuracy, with studies demonstrating comparable performance to radiologists. Nonetheless, the detection of sub-clinical cancer remains arduous, primarily due to small tumor sizes. The amalgamation of fully annotated datasets with larger ones lacking Region of Interest (ROI) annotations is pivotal for training robust deep learning models. This review delves into recent high-throughput analyses of breast cancers, elucidating their implications for refining classification methodologies through deep learning. Furthermore, this research facilitates the prediction of whether cancer is benign or malignant, fostering advancements in diagnostic accuracy and patient care.
为了在基于机器学习的乳腺癌分类中实现精确预测，人们探索了大量算法和优化器。卷积神经网络（CNNs）在辨别图像数据中的分层表示方面表现出色，已成为一种突出的选择。这一特性使其适用于检测乳房 X 光照片中的恶性病变等任务。此外，CNN 架构的适应性使其能够根据特定数据集和目标进行定制，从而加强早期检测和治疗策略。尽管乳房 X 射线照相筛查效果显著，但假阳性和假阴性的持续存在也带来了挑战。计算机辅助设计（CAD）软件已显示出良好的前景，尽管早期系统的改进有限。最近在深度学习方面取得的进展为提高准确性带来了希望，有研究表明其性能可与放射科医生媲美。尽管如此，亚临床癌症的检测仍然十分困难，这主要是由于肿瘤尺寸较小。将完全注释的数据集与缺乏感兴趣区（ROI）注释的大型数据集合并，对于训练强大的深度学习模型至关重要。本综述深入探讨了最近对乳腺癌的高通量分析，阐明了它们对通过深度学习完善分类方法的影响。此外，这项研究还有助于预测癌症是良性还是恶性，从而促进诊断准确性和患者护理方面的进步。
{"title":"Breast Cancer Classification Using Machine Learning","authors":"Ankit, Harsh Bansal, Dhruva Arora, Kanak Soni, Rishita Chugh, Swarna Jaya Vardhan","doi":"10.32628/cseit2410274","DOIUrl":"https://doi.org/10.32628/cseit2410274","url":null,"abstract":"In the pursuit of precise forecasts in machine learning-based breast cancer categorization, a plethora of algorithms and optimizers have been explored. Convolutional Neural Networks (CNNs) have emerged as a prominent choice, excelling in discerning hierarchical representations in image data. This attribute renders them apt for tasks such as detecting malignant lesions in mammograms. Furthermore, the adaptability of CNN architectures enables customization tailored to specific datasets and objectives, enhancing early detection and treatment strategies. Despite the efficacy of screening mammography, the persistence of false positives and negatives poses challenges. Computer-Aided Design (CAD) software has shown promise, albeit early systems exhibited limited improvements. Recent strides in deep learning offer optimism for heightened accuracy, with studies demonstrating comparable performance to radiologists. Nonetheless, the detection of sub-clinical cancer remains arduous, primarily due to small tumor sizes. The amalgamation of fully annotated datasets with larger ones lacking Region of Interest (ROI) annotations is pivotal for training robust deep learning models. This review delves into recent high-throughput analyses of breast cancers, elucidating their implications for refining classification methodologies through deep learning. Furthermore, this research facilitates the prediction of whether cancer is benign or malignant, fostering advancements in diagnostic accuracy and patient care.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":" 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140684627","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}
In today’s digitized era, where the whole world is interconnected and every information about individuals are collected, it is important to process and store the data such that it is safe from unauthorized access. Encryption is used to turn the plain text into cipher text which makes the data unreadable, thus maintaining its confidentiality and integrity. Among the several encryption methods available, Advanced Encryption Standard (AES) and Rivest Shamir Adleman (RSA) are popularly used due to their effectiveness and efficiency. However, alternative encryption techniques exist, each offers different level of security and performance. This study presents a thorough comparative analysis of AES and RSA alongside other encryption methods to assess their suitability for secure communication. Factors such as encryption strength, computational complexity, key management, scalability, and versatility are examined to provide a comprehensive understanding of each technique's strengths and weaknesses. By scrutinizing these aspects, this research aims to offer insights for decision-makers in selecting the most suitable encryption method tailored to specific requirements and constraints.
{"title":"Comparative Analysis of AES and RSA with Other Encryption Techniques for Secure Communication","authors":"Prashant, MD Sohail Haque, Amrinder Kaur, Pankaj Yadav","doi":"10.32628/cseit2410263","DOIUrl":"https://doi.org/10.32628/cseit2410263","url":null,"abstract":"In today’s digitized era, where the whole world is interconnected and every information about individuals are collected, it is important to process and store the data such that it is safe from unauthorized access. Encryption is used to turn the plain text into cipher text which makes the data unreadable, thus maintaining its confidentiality and integrity. Among the several encryption methods available, Advanced Encryption Standard (AES) and Rivest Shamir Adleman (RSA) are popularly used due to their effectiveness and efficiency. However, alternative encryption techniques exist, each offers different level of security and performance. This study presents a thorough comparative analysis of AES and RSA alongside other encryption methods to assess their suitability for secure communication. Factors such as encryption strength, computational complexity, key management, scalability, and versatility are examined to provide a comprehensive understanding of each technique's strengths and weaknesses. By scrutinizing these aspects, this research aims to offer insights for decision-makers in selecting the most suitable encryption method tailored to specific requirements and constraints.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140684191","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}
Dr. Sandeep Tayal, Taniya Sharma, Shivansh Singhal, Anurag Thakur
This study explores the utilization of Machine Learning (ML) and Natural Language Processing (NLP) in automating the resume screening process. Traditional methods, often manual and subjective, fail to efficiently manage the volume and variety of resumes. By employing NLP techniques like named entity recognition and part-of-speech tagging, coupled with ML classifiers such as K-Nearest Neighbors and Support Vector Machines, we propose a system that enhances the precision of candidate selection while significantly reducing time and effort.
{"title":"Resume Screening using Machine Learning","authors":"Dr. Sandeep Tayal, Taniya Sharma, Shivansh Singhal, Anurag Thakur","doi":"10.32628/cseit2410275","DOIUrl":"https://doi.org/10.32628/cseit2410275","url":null,"abstract":"This study explores the utilization of Machine Learning (ML) and Natural Language Processing (NLP) in automating the resume screening process. Traditional methods, often manual and subjective, fail to efficiently manage the volume and variety of resumes. By employing NLP techniques like named entity recognition and part-of-speech tagging, coupled with ML classifiers such as K-Nearest Neighbors and Support Vector Machines, we propose a system that enhances the precision of candidate selection while significantly reducing time and effort.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140683212","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}
This content provides an overview and analysis of popular messaging applications, focusing on encryption methods, security features, and usability. This work includes Signal, Telegram, WhatsApp, etc. By analyzing well-known platforms such as it evaluates usability and functionality while also evaluating their effectiveness in protecting user privacy. Key topics discussed include end-to-end encryption, encryption protocols, secure authentication methods, and preventing attacks such as man-in-the-middle and eavesdropping. Additionally, this content discusses issues and considerations related to secure messaging, including regulatory compliance, commercialization, and exchange cybersecurity threats. Combining current research and industry developments, it provides insight into the strengths and limitations of current messaging solutions as well as trending innovations in cryptography and privacy-enhancing techniques.
{"title":"Encryption, Privacy, and Usability : A Comparative Evaluation of Leading Secure Messaging Platforms","authors":"Kumar Ashish, Yaswanth Bolisetty, Deepanshu Singh, Amarinder Kaur","doi":"10.32628/cseit2410272","DOIUrl":"https://doi.org/10.32628/cseit2410272","url":null,"abstract":"This content provides an overview and analysis of popular messaging applications, focusing on encryption methods, security features, and usability. This work includes Signal, Telegram, WhatsApp, etc. By analyzing well-known platforms such as it evaluates usability and functionality while also evaluating their effectiveness in protecting user privacy. Key topics discussed include end-to-end encryption, encryption protocols, secure authentication methods, and preventing attacks such as man-in-the-middle and eavesdropping. Additionally, this content discusses issues and considerations related to secure messaging, including regulatory compliance, commercialization, and exchange cybersecurity threats. Combining current research and industry developments, it provides insight into the strengths and limitations of current messaging solutions as well as trending innovations in cryptography and privacy-enhancing techniques.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":" 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140687925","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}
In our everyday life we can see that innovation is advancing continually. The web of things (IoT) contains different applications and advancements that are accessible in brilliant homes, shrewd water system, and medical services. The IoT goes about as an extended variant of the web, which furnishes us with the information we really want to productively carry on with our lives more. It depends on interfacing up gadgets utilized every day. The fundamental goal of this paper is to figure out how to involve IoT in Brilliant Homes, Medical services, and Farming.
{"title":"Web of Things (IoT): Shrewd Living and Way of life","authors":"Vedanti Patel, Mansi Vegad","doi":"10.32628/cseit2410243","DOIUrl":"https://doi.org/10.32628/cseit2410243","url":null,"abstract":"In our everyday life we can see that innovation is advancing continually. The web of things (IoT) contains different applications and advancements that are accessible in brilliant homes, shrewd water system, and medical services. The IoT goes about as an extended variant of the web, which furnishes us with the information we really want to productively carry on with our lives more. It depends on interfacing up gadgets utilized every day. The fundamental goal of this paper is to figure out how to involve IoT in Brilliant Homes, Medical services, and Farming.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"88 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140707958","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}
Shreya Pandey, Afaq Shaikh, Siddhi Keni, Uma Garodiya, Ayush Yadav
"OneWorldGiving: Uniting NGOs and donors for a Better World" is a project aiming to bridge the gap between donors and NGOs in India's philanthropic scene. The initiative aims to create a platform that promotes efficiency, transparency, and cooperation, fostering shared responsibility and trust among all parties involved. Other studies have focused on cloud-based mobile applications, automation of donation procedures using Azure Logic Apps, Android app for receiving food, clothing, and book contributions, and mobile applications for community projects and NGOs. However, challenges such as platform-specific specifications, outdated devices, and specialist knowledge in Flutter programming may arise. The NGO Portal website aims to help NGOs and potential volunteers interact, promoting a sense of community and unity among stakeholders. The Android application focuses on making book contributions to NGOs easier, with a Donation Registration component, Firebase database, and User Management feature. The project aims to create a transformative platform that promotes cooperation, openness, and group compassion, improving lives for those in need.
"OneWorldGiving：OneWorldGiving: Uniting NGOs and donors for a Better World"（"OneWorldGiving：团结非政府组织和捐助者，共创更美好的世界"）是一个旨在弥合印度慈善界捐助者和非政府组织之间差距的项目。该倡议旨在创建一个提高效率、透明度和合作的平台，促进有关各方共同承担责任和相互信任。其他研究侧重于基于云的移动应用程序、使用 Azure Logic Apps 实现捐赠程序自动化、接收食品、衣物和书籍捐赠的安卓应用程序，以及社区项目和非政府组织的移动应用程序。然而，可能会出现平台特定规格、过时设备和 Flutter 编程专业知识等挑战。非政府组织门户网站旨在帮助非政府组织和潜在志愿者进行互动，促进利益相关者之间的社区意识和团结。安卓应用程序的重点是通过捐赠登记组件、Firebase 数据库和用户管理功能，让向非政府组织提供图书捐助变得更加容易。该项目旨在创建一个变革性平台，促进合作、开放和集体同情心，改善需要帮助的人的生活。
{"title":"OneWorldGiving : Uniting NGO’s and Donors for a Better World","authors":"Shreya Pandey, Afaq Shaikh, Siddhi Keni, Uma Garodiya, Ayush Yadav","doi":"10.32628/cseit2410246","DOIUrl":"https://doi.org/10.32628/cseit2410246","url":null,"abstract":"\"OneWorldGiving: Uniting NGOs and donors for a Better World\" is a project aiming to bridge the gap between donors and NGOs in India's philanthropic scene. The initiative aims to create a platform that promotes efficiency, transparency, and cooperation, fostering shared responsibility and trust among all parties involved. Other studies have focused on cloud-based mobile applications, automation of donation procedures using Azure Logic Apps, Android app for receiving food, clothing, and book contributions, and mobile applications for community projects and NGOs. However, challenges such as platform-specific specifications, outdated devices, and specialist knowledge in Flutter programming may arise. The NGO Portal website aims to help NGOs and potential volunteers interact, promoting a sense of community and unity among stakeholders. The Android application focuses on making book contributions to NGOs easier, with a Donation Registration component, Firebase database, and User Management feature. The project aims to create a transformative platform that promotes cooperation, openness, and group compassion, improving lives for those in need. ","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"95 S4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140707278","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}
Jibin Joy, N Meenakshi, Thejas Vinodh,, Abel Thomas, Shifil S
Sign language display software converts text/speech to animated sign language to support the special needs population, aiming to enhance communication comfort, health, and productivity. Advancements in technology, particularly computer systems, enable the development of innovative solutions to address the unique needs of individuals with special requirements, potentially enhancing their mental well-being. Using Python and NLP, a process has been devised to detect text and live speech, converting it into animated sign language in real-time. Blender is utilized for animation and video processing, while datasets and NLP are employed to train and convert text to animation. This project aims to cater to a diverse range of users across different countries where various sign languages are prevalent. By bridging the gap between linguistic and cultural differences, such software not only facilitates communication but also serves as an educational tool. Overall, it offers a cost-effective and widely applicable solution to promote inclusivity and accessibility.
{"title":"Translation System for Sign Language Learning","authors":"Jibin Joy, N Meenakshi, Thejas Vinodh,, Abel Thomas, Shifil S","doi":"10.32628/cseit2410257","DOIUrl":"https://doi.org/10.32628/cseit2410257","url":null,"abstract":"Sign language display software converts text/speech to animated sign language to support the special needs population, aiming to enhance communication comfort, health, and productivity. Advancements in technology, particularly computer systems, enable the development of innovative solutions to address the unique needs of individuals with special requirements, potentially enhancing their mental well-being. Using Python and NLP, a process has been devised to detect text and live speech, converting it into animated sign language in real-time. Blender is utilized for animation and video processing, while datasets and NLP are employed to train and convert text to animation. This project aims to cater to a diverse range of users across different countries where various sign languages are prevalent. By bridging the gap between linguistic and cultural differences, such software not only facilitates communication but also serves as an educational tool. Overall, it offers a cost-effective and widely applicable solution to promote inclusivity and accessibility.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"84 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140706961","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}
Uma Goradiya, Naman Pandey, Mantasha Khan, Satyam Tiwari, Mandar Pawar
In India, numerous crimes targeting women occur daily. We are far from knowing the actual figures due to hundreds of cases that go unnoticed. Recognizing this pressing issue, the objective of this project is to develop a mobile application that can provide features of self-defense training techniques and emergency services access, such as locating the nearest police station, hospitals, bus stops, and pharmacies. It will include a list of emergency calling options to dial emergency numbers and real-time location sharing. When activated, the app will send the user's location every 3 minutes and enable them to share their location with the nearest police station and government bodies with just one tap in case of an emergency. This application is integrated with numerous features in one app, playing a pivotal role in women’s safety while providing a user-friendly experience.
{"title":"SAKHII- Empowering Women with One-Tap Safety App","authors":"Uma Goradiya, Naman Pandey, Mantasha Khan, Satyam Tiwari, Mandar Pawar","doi":"10.32628/cseit2410254","DOIUrl":"https://doi.org/10.32628/cseit2410254","url":null,"abstract":"In India, numerous crimes targeting women occur daily. We are far from knowing the actual figures due to hundreds of cases that go unnoticed. Recognizing this pressing issue, the objective of this project is to develop a mobile application that can provide features of self-defense training techniques and emergency services access, such as locating the nearest police station, hospitals, bus stops, and pharmacies. It will include a list of emergency calling options to dial emergency numbers and real-time location sharing. When activated, the app will send the user's location every 3 minutes and enable them to share their location with the nearest police station and government bodies with just one tap in case of an emergency. This application is integrated with numerous features in one app, playing a pivotal role in women’s safety while providing a user-friendly experience.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"5 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140712392","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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