NAARI: An Intelligent Android App for Women Safety

Chakraborty, Shreya; Singh, Debabrata; Biswal, Anil Kumar

doi:10.1007/978-981-33-4604-8_48

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Using a USB cable, the Android phone is connected to the IOIO-OTG microcontroller. [6] Developed a security device to defend ladies from vulnerable activity and lonely traveling on the road mistreatment IoT supported the fingerprint security methodology. [7], during this system the GPS pursuit and electronic communication system plays a vital role.…”

Section: Introduction: -mentioning

confidence: 99%

Handy App for Safety Against Violence

Janokar¹,

Gaikwad²,

Ghuge³

et al. 2023

Preprint

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Heinous offenses against women have forced us to undertake many precautionary measures and put on a large array of ideas so that to provide security systems to women via their phones. Here we present, an Android Application for women safety, this app can be activated by just normal movements like shaking, as situation demands. Our main agenda is to create a model that removes the financial and physical complexities in GPS, since it is a satellite-based service alongside being available anytime anywhere. GPS system can come handy to extract data which contains parameters like latitude, longitude along with the time details, etc. There exists no prior financial investment for its usage. ’Google Maps’ is a popular service for this purpose. Mobile phone catches hold of location which communicates with the help of General Packet Radio Service (GPRS), being one of the superior modes as far as tracking concerned.

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Section: Introduction: -mentioning

confidence: 99%

Handy App for Safety Against Violence

Janokar¹,

Gaikwad²,

Ghuge³

et al. 2023

Preprint

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Development of Rakshak - A Risk Free App for People's Safety Using Map Embedded API

L.M.A,

Shashank,

Kumar

et al. 2023

2023 International Conference on Data Science and Network Security (ICDSNS)

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Performance Evaluation of Different Machine Learning Algorithms Using Credit Scoring Model

Singh,

Mahapatra,

Biswal

et al. 2023

Advances in Systems Analysis, Software Engineering, and High Performance Computing

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The project focuses on the development of a credit scoring model. Concerns with credit scoring are being raised when developing an empirical model to support the financial decision-making process for financial institutions. This chapter focuses on the development of a credit scoring model using a combination of feature selection and ensemble classifiers. The most relevant features are identified, and an ensemble classifier is used to reduce the risk of overfitting with the aim of improving the classification performance of credit scoring models in the proposed method. Several metrics, including accuracy, precision, recall, F1 score, and AUC-ROC, are used to evaluate the performance of the model. The accuracy and robustness of credit scoring models can potentially be improved by the proposed method, and the evaluation metrics can be used to further enhance it.

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NAARI: An Intelligent Android App for Women Safety

Cited by 3 publications

References 12 publications

Handy App for Safety Against Violence

Handy App for Safety Against Violence

Development of Rakshak - A Risk Free App for People's Safety Using Map Embedded API

Performance Evaluation of Different Machine Learning Algorithms Using Credit Scoring Model

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