Intellectual Property India Publishes Patent Application for Machine Learning And Iot-Based System For Predicting Psychological Buying Behaviour In E- Commerce Platforms

MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641105033 A) filed by Dr. Thanigaiyarasu. R; Dr. Chetna Priti; Dr. Amit Kumar Tiwari; Dr. Bairi Srinivas; Dr. Sandaboina Shivakumar; Durairaji V; Ganesan N M; Dr. Pintu Pal; Dr Ravindra Ashok Ahire; Ajay S Bhongade; Sangam Sharma; and M. Kayathri Devi on September 01, 2026, for Machine Learning And Iot-Based System For Predicting Psychological Buying Behaviour In E- Commerce Platforms.

Inventors include Dr. Thanigaiyarasu. R; Dr. Chetna Priti; Dr. Amit Kumar Tiwari; Dr. Bairi Srinivas; Dr. Sandaboina Shivakumar; Durairaji V; Ganesan N M; Dr. Pintu Pal; Dr Ravindra Ashok Ahire; Ajay S Bhongade; Sangam Sharma; and M. Kayathri Devi.

The application for the patent was published on September 11, 2026, under issue no. 37/2026.

Abstract: Machine Learning and IoT-Based System for Predicting Psychological Buying Behaviour in E-Commerce Platforms is the proposed invention. The proposed invention collects sequential consumer interaction data including product searches, views, comparisons, cart activities, wish-list events, transactions, and other behavioral events, together with optionally authorized contextual information obtained from IoT-enabled devices. The collected information is pre-processed and converted into a multimodal temporal representation. A Transformer-based behavioral learning module analyzes the representation to identify relationships among consumer actions and contextual observations and generates a dynamic behavioral representation. A purchase-intent prediction module utilizes the learned representation to estimate the likelihood of a future purchase within a predetermined time interval, while a behavioral-state module identifies the consumer's current purchasing stage. A recommendation engine generates context-aware product or promotional recommendations according to the predicted intent and behavioral state. A privacy- management module provides controlled processing of IoT and consumer information. The system enables adaptive purchase-intent prediction and personalized e- commerce recommendations based on continuously evolving consumer behavior.

Disclaimer: Curated by HT Syndication.