MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641089564 A) filed by Premkumar Sivankutty on July 23, 2026, for System And Method For Predictive Audience Density-Based Dynamic Pricing And Content Scheduling For Digital Display Advertising Networks.
Inventor includes Chethana S Nair.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: A computer-implemented system and method for self-serve physical display advertising networks fuses heterogeneous passive aggregate location density signals — comprising mobile network operator (MNO) aggregate API data, satellite imagery density estimates, historical footfall pattern records, and optionally optical person- count data from camera devices — to derive per-display-location forward-looking predicted audience density scalar values. A weighted combination function P(i,t) = w1·MNO(i,t) + w2·SAT(i,t) + w3·HIST(i,t) + w4·CAM(i,t) is applied to normalised signals, and the resulting scalar simultaneously drives: (i) automated per-minute slot pricing via a slot-rate computation module; (ii) audience persona classification for adaptive content queue management; and (iii) an AI-assisted ad placement recommendation engine. All pricing and reach estimates are surfaced to advertisers prior to payment confirmation in a self-serve booking interface. A machine learning feedback module automatically adjusts fusion weights to minimise prediction error over time. A confidence scoring mechanism triggers fallback to historical baseline predictions when data source availability falls below a threshold. A schedule lock module closes reservations at a daily cutoff, generates playlist execution files for display edge hubs, and issues automatic wallet credits for pre-cutoff cancellations. The invention addresses four distinct technical problems — data heterogeneity, temporal mismatch, siloed functionality, and pre-payment uncertainty — that are not solved by any known prior art system.
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