Automatic Prediction and Identification of Smart Women Safety Wearable Device Using Dc-RFO-IoT

سال انتشار: 1402
محل انتشار: فصلنامه مدیریت فناوری اطلاعات، دوره: 15، شماره: 5
کد COI اختصاصی: JR_JITM-15-5_003
زبان مقاله: انگلیسی
تعداد مشاهده: 275

نویسندگان

Professor in CSE, Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad.

Professor, Department of C. S. E, Raghu Engineering College, Dakamarri, Bheemunipatnam Mandal, Visakhapatnam, divakararao.

Patel

Assoc. Professor Department of Electronics and Communication Engineering B V Raju Institute of Technology, Medak (Dist.), Narsapur. ۵۰۲۳۱۳ ibrahim.

Saikumar

Department of ECE, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, India ۵۲۲۵۰۲.

Vijendra Babu

Professor, Department of Electronics & Communication Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission&#۰۳۹;s Research Foundation, Paiyanoor-۶۰۳ ۱۰۴. Tamil Nadu, India.

چکیده

Women’s safety is very important for around the world and many anti-women safety incidents are happened in current decades. Women's criminality is on the rise in India, particularly on an hourly basis ۱۰۰۰ criminal cases are filed according to Indraprastha and Kannon organizations. The Internet of Things (IoT) application will assist women in difficult situations.This design with Dc-RFO-IoT has an emergency application that can be useful to provide critical thinking and suggestions to women in rescue time. When the emergency soft button is pushed, notifications are sent to registered contacts as well as to women's hotline lines with GPS and GSM. A GPS sensor is also used to transmit the position with longitude and latitude. Every one minute, the receiver sends a link to your location, updating them on your current position. The attacker may shut the victim's mouth and prevent her from requesting assistance. The speaker on this gadget generates high-frequency sound. It will raise the alarm in the surrounding area and make the attacker fearful. This IoT with deep learning application is giving accurate outcomes and measures are improved. The performance measures like accuracy ۹۳.۴۳%, sensitivity ۹۲.۸۷%, Recall ۹۸.۳۴%, safety ratio ۹۷.۳۴%, and F measure ۹۷,۸۹% had been improved these are outperformance the methodology and compete with present models.

کلیدواژه ها

Smart Phone, IOT, GPS, Sensors

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