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A Hidden Markov Model and Internet of Things Hybrid Based Smart Women Safety Device

机译:基于隐马尔可夫模型和物联网混合的智能女性安全装置

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Smart technologies for women safety are gaining popularity over the last few decades. Several nefarious approaches to women that outraged the entire nation awakened the scientists globally to design smart apps for women safety. This paper proposes a concept of a multivariate security paradigm for women under possible offensive threats by deep sensing approaches. Internet of Things (IOT) based platform provides dexterity and dynamicity in correlating a plethora of sensors and actuators to ensure women safety. Hidden Markov Models (HMM) offer scope for better predictive analysis for its dynamic probabilistic nature and helped us developing a dense sensing approach based on traces of suspicious activities. There is a situation-based analysis for relative modelling based on face recognition as well as fuzzy labeling of verbal conversations. If an emergency situation is triggered, a GSM/GP module will generate emergency in case of after-shock otherwise will warn the female device bearer. The results of experimentations proved to be really promising with an accuracy of 94.7%.
机译:在过去的几十年中,用于保护妇女安全的智能技术日益普及。激怒了整个国家的几种邪恶的对待女性的方法,唤醒了全球科学家为女性安全设计智能应用的想法。本文提出了一种可能的进攻威胁下的女性通过深度感知方法的多变量安全范式的概念。基于物联网(IOT)的平台在关联大量传感器和执行器以确保女性安全方面提供了灵活性和动态性。隐马尔可夫模型(HMM)提供了对其动态概率性质进行更好的预测分析的范围,并帮助我们基于可疑活动的痕迹开发了密集的感知方法。对于基于面部识别以及语音对话的模糊标记的相对建模,存在基于情况的分析。如果触发紧急情况,则在发生余震的情况下,GSM / GP模块将产生紧急情况,否则将警告母设备承载者。实验结果被证明具有94.7 \ n \\%\n。

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