MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202541117222 A) filed by Dhivya K; Akshiya C; Ishwarya S; Jeevith V; and Karan R J, Coimbatore, Tamil Nadu, on Nov. 26, 2025, for 'narcox-exposing the shadows of drug trade.'
Inventor(s) include Dhivya K; Akshiya C; Ishwarya S; Jeevith V; and Karan R J.
The application for the patent was published on Jan. 23, under issue no. 04/2026.
According to the abstract released by the Intellectual Property India: "The rapid expansion of social media platforms has created diverse avenues for communication and information exchange but has simultaneously facilitated the proliferation of illicit drug promotion, marketing, and sales activities. Platforms such as Telegram and Instagram have emerged as primary channels where individuals and organized groups exploit technological anonymity and multimedia communication to distribute, promote, or advertise illegal substances. Telegram, on the other hand, offers encrypted private groups and channels that enable the covert exchange of such content The detection of these illicit activities remains a significant challenge due to rapidly evolving slang, coded imagery, hashtags with double meanings, and limited accessibility to encrypted communications. To address these challenges, this study proposes an Al-driven drug detection framework that integrates multimodal data sources from both Telegram and Instagram. The framework combines Natural Language Processing (NLP) for text understanding and deep learning-based image recognition (YOLOv8) for visual analysis. On Telegram, a custom monitoring bot captures real-time chat messages, images, and shared links using the Telegram API. On Instagram, automated scraping and API-based collection are employed to gather data based on hashtags (e.g., #weed, #mdma,#painkillers, #xanax) and user mentions, alfowing the model to identify networks of related accounts and recurring content patterns. In conclusion, this integrated Telegram-lnstagram Al surveillance framework provides a scalable and adaptive approach for the early detection and monitoring of drug-related activities. The proposed architecture can further be extended to other social media and communication platforms such as WhatsApp, Facebook, and X (formerly Twitter), allowing a unified and intelligent system for comprehensive online drug surveillance. By leveraging multimodal analysis, contextual cues from hashtags and mentions, and deep learning-based visual recognition, the system enhances detection reliability and supports law enforcement, social media platforms, and public health agencies in mitigating the spread of illicit drug distribution online."
Disclaimer: Curated by HT Syndication.
