Design And Implementation Of A Multi-Modal Mobile Application Safety Analytics Utilizing Nlp

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 02 | Page :
    By

    Km Sandhya,

  • Navin Kumar Tyagi,

  • R. Prasad,

  1. Student, Marathwada Institute of Technology, Bulandshahr, Uttar Pradesh, India
  2. Assistant Professor, Marathwada Institute of Technology, Bulandshahr, Uttar Pradesh, India
  3. Assistant Professor, Hindustan College of Science & Technology, Mathura, Uttar Pradesh, India

Abstract

This study suggests a multi-modal mobile app safety analytics platform that uses natural language processing (NLP) to handle voice, text, and SOS messages. For effective intent recognition and decision-making, the platform processes all messages in a standard text or SOS flag format. Tokenization and normalization are used to process text communications, whereas noise reduction and text conversion are used to handle voice messages. For a quicker response, the SOS messages are processed without any intermediary processing. The platform’s performance evaluation reveals a high accuracy rate of (>90%) for intent detection, 85–90% for speech recognition, 98% for text processing, and 92% for the entire system. It is appropriate for real-time mobile app operation due to its low response time (~1.2 s) for efficient operation. The platform works well to increase user safety. Future research can focus on enhancing performance in noisy settings and including an effective intent detection method for increased effectiveness.

Keywords: Naive Bayes, Support Vector Machine, Save Our Souls, Artificial intelligence, Machine Learning, Natural language processing, and Deep Learning-based Web Attack Detection

How to cite this article:
Km Sandhya, Navin Kumar Tyagi, R. Prasad. Design And Implementation Of A Multi-Modal Mobile Application Safety Analytics Utilizing Nlp. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(02):-.
How to cite this URL:
Km Sandhya, Navin Kumar Tyagi, R. Prasad. Design And Implementation Of A Multi-Modal Mobile Application Safety Analytics Utilizing Nlp. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(02):-. Available from: https://journals.stmjournals.com/jomccmn/article=2026/view=242436


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Ahead of Print Subscription Review Article
Volume 13
02
Received 26/03/2026
Accepted 30/04/2026
Published 01/05/2026
Publication Time 36 Days
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