Intellectual Property India Publishes Patent Application for “an Intelligent Dynamic Guarantee Management System For A Gig Economy Platform”

MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641074779 A) filed by Vellore Institute Of Technology on June 17, 2026, for “an Intelligent Dynamic Guarantee Management System For A Gig Economy Platform”.

Inventors include Dr. Yokesh Babu Sundaresan; Sebin Shaiju; Vaibhav Kumar; and Dr. Kumaresan P.

The application for the patent was published on June 26, 2026, under issue no. 26/2026.

Abstract: The present invention relates to a system and method for intelligent dynamic guarantee management in gig economy platforms using an Exponential Moving Average– Gaussian Process Regression (EMA-GPR) framework. The invention addresses income instability and unfair task allocation experienced by gig workers by dynamically generating worker-specific income guarantees based on historical worker activity, temporal demand characteristics, and platform demand-supply conditions. The system comprises a worker data processing module, a feature extraction module, a Gaussian Process Regression prediction engine, an Exponential Moving Average smoothing module, a cumulative guarantee tracking module, a demand-adaptive matching module, a cost matrix generation module, an assignment optimization module, and a guarantee settlement module. The prediction engine generates guarantee ratios for individual workers, while the smoothing module continuously updates the guarantee ratios over predefined time intervals to balance responsiveness and stability. The cumulative guarantee tracking module preserves guarantee commitments across a worker session, and the demand-adaptive matching module dynamically adjusts task assignment strategies according to real-time demand density. A monetary cost matrix is generated to facilitate rate-invariant worker-task assignment through optimization algorithms, thereby reducing platform expenditure while maintaining fairness among workers. The system further computes compensation shortfalls based on cumulative guarantees and actual earnings. The invention provides improved worker income predictability, adaptive task allocation, reduced guarantee volatility, enhanced fairness across worker categories, and scalable deployment for large-scale gig economy platforms. Fig 1 to 6.

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