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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | DISTRESS CALL DETECTION SYSTEM FOR EMERGENCY SCENARIOS USING CONVOLUTIONAL NEURAL NETWORKS |
| Authors Name: | Sai Pavan Gurugubelli , A.Durga Praveen Kumar , DANTULURI HARSHA VARDHAN RAJU , Mahesh Reddy Dharmala , Sukesh chandu Pakkurthi |
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IJNRD_217903
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| Published Paper Id: | IJNRD2404727 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | his paper discusses the development of a robust system for the automated detection of distress calls in emergency situations, leveraging advanced technologies and signal processing techniques. In contemporary emergency response scenarios, accurate identification of distress signals is crucial for efficient and swift assistance. The proposed system will employ state-of-the-art algorithms and artificial intelligence to analyze various communication channels, including audio and environmental files, to recognize patterns associated with distress signals. The paper will explore the integration of sophisticated convolutional networks to process real-time data, differentiating distress signals from background noise and non-emergency communications. This model will be trained on a diverse dataset of diverse audio speech datasets to enhance the system's adaptability and accuracy in recognizing varying communication patterns. Key objectives include the development of a user-friendly interface for emergency response teams, facilitating seamless integration of distress call data into their decision-making processes. The project also aims to address challenges such as signal variability, multiple communication formats, and evolving technologies by implementing adaptive algorithms. |
| Keywords: | Distress Call Detection, AI-based solution, Disaster Scenarios, Audio analysis, Pre-Processing, Convolutional Neural Network, Performance Metrics, Emotion Classification, Web Application Interfac |
| Cite Article: | "DISTRESS CALL DETECTION SYSTEM FOR EMERGENCY SCENARIOS USING CONVOLUTIONAL NEURAL NETWORKS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h224-h231, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404727.pdf |
| Downloads: | 00028 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404727 Registration ID: 217903 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: h224-h231 Country: Anakapalli, Andhra Pradesh, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404727 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404727 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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