Forensic Breakthrough for Crime Scene Analysis via Mobile Data and NLP Applications
B. Krishna Veni, Khateeb Syed Muskan, Bingi Pranitha Raj, Jenne Sumithra, Gogula Sai Ganesh, Subramanyam Sujeeth Kumar
With the rise of digital communication, chat logs have become a crucial source of evidence in
forensic investigations. The crime scene analysis by integrating Natural Language Processing (NLP)
techniques to analyze chat data for identifying key information, suspect behavior, and potential criminal
intent. Using advanced NLP methods such as sentiment analysis, named entity recognition, and text
classification, it can detect hidden connections, and contextual meanings within conversations. This
automated analysis enhances the efficiency and accuracy of forensic investigations, reducing manual
effort and enabling law enforcement to make data-driven decisions. By leveraging chat-based forensic
analysis, this contributes to modern crime-solving techniques, offering a powerful tool for digital
evidence examination. Advancements in Natural Language Processing (NLP) and digital forensics have
revolutionized crime scene investigations, particularly in analyzing digital communication for crucial
evidence. forensic breakthrough that leverages chat logs and NLP applications to extract, analyze,
and interpret conversations relevant to criminal cases. By providing law enforcement agencies with an
intelligent and scalable tool for chat-based forensic analysis, this significantly improves digital evidence
handling, accelerates crime resolution, and supports judicial proceedings with data-driven insights. It
ultimately contributes to modern forensic science by bridging the gap between technology and criminal
investigations, making digital communication a key asset in solving crimes efficiently
