MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611056165 A) filed by Mr. Anivesh Tripathi; Mr. Bhavya Garg; Mr. Abhishek Dubey; and Mrs. Deepti Aggarwal on May 03, 2026, for Ai-Based Multi-Source Real Estate Price Forecasting System Using Ensemble Machine Learning And Data Fusion Techniques.
Inventors include Mr. Anivesh Tripathi; Mr. Bhavya Garg; Mr. Abhishek Dubey; and Mrs. Deepti Aggarwal.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: This invention presents an AI-powered system for predicting real estate prices using data from multiple sources and sophisticated machine learning algorithms. It leverages structured and unstructured data sources such as past property prices, demographic data, economic factors and social media data. It uses an ensemble learning model (Random Forest, XGBoost) to enhance prediction accuracy and stability. The system includes feature engineering, data preprocessing, and debiasing techniques to improve prediction accuracy. The framework also has robust data security measures with encryption and cloud-based scalability. The invention facilitates real-time, dynamic, and robust property price forecasting, aiding buyers, sellers, investors, and real-estate practitioners. Keywords AI, Machine Learning, Real Estate Price Prediction, XGBoost, Random Forest, Data Fusion, Predictive Analytics, Ensemble Learning
Disclaimer: Curated by HT Syndication.
