Modern technical systems incorporate hundreds of patents, standards, and software packages—each with distinct intellectual property requirements. A typical enterprise software system may include over 100 third-party libraries, while a telecommunications product might implement 50+ technical standards and thousands of patent claims.

The fundamental challenge lies in maintaining compliance across rapidly evolving systems while managing the computational overhead of continuous IP verification.

This page brings together solutions from recent research—including machine learning approaches for patent-standard mapping, automated license detection in CI/CD pipelines, and real-time compliance monitoring systems. These and other approaches help organizations systematically track and verify intellectual property obligations during development.

1. Automated System for Remote Evaluation of Vendor Information Security Compliance

CLEAROPS, INC., 2022

Automated vendor compliance assessment that allows customers to rapidly and accurately evaluate the information security practices of their vendors. The system evaluates vendor compliance with predefined information security criteria like cybersecurity, regulatory, intellectual property, data management, and policy. It accesses remotely located sources to gather data about the vendor's performance against these criteria. The system compares the vendor's data against predetermined standards to determine compliance. If the vendor falls short in certain areas, it can identify remedial actions to bring them into compliance. The system reports back to the customer whether the vendor is compliant or not.

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2. AI-Driven Distributed System for Identifying Intellectual Property Infringement with Reinforcement Learning and Data Normalization

The Third Research Institute of the Ministry of Public Security, THE THIRD RESEARCH INSTITUTE OF THE MINISTRY OF PUBLIC SECURITY, 2022

Active early warning system for identifying parties involved in intellectual property infringement using AI. The system collects data from various sources like transactions, logistics, communications. It preprocesses the data to generate a normalized dataset. An AI model is trained using reinforcement learning to identify infringers based on feedback scores. The model is deployed in a distributed server architecture with clustering and distributed storage. The system can continuously learn and improve by feeding back scores from the model's predictions.

3. Automated System for Web-Based Intellectual Property Infringement Detection and Encrypted Evidence Collection

Chongqing Yibaquan Network Technology Co., Ltd., CHONGQING EBAOQUAN NETWORK TECHNOLOGY CO LTD, 2021

Method and device for infringement monitoring and evidence collection to help protect intellectual property online. It involves automated monitoring of user-specified data across the web for infringements. The method involves solidifying and encrypting the user's monitored data, user info, and timestamps. It then searches for similar data in the monitored area and extracts infringing matches. These infringements are solidified, timestamped, and sent to the user along with the original data. If the user confirms infringement, they can send an infringement notice. The solidified infringement data is then filed with a judicial institution. This provides a way to generate legally enforceable evidence for IP protection.

4. Enterprise Intellectual Property Management System with Encryption, Identity Verification, and Automated Rights Assignment

JIANGSU YUNBIAO TECH CO LTD, JIANGSU YUNBIAO TECHNOLOGY CO LTD, 2020

Intelligent management system for enterprise intellectual property (IP) patent submission and communications that improves IP security, prevents theft, and streamlines management. The system uses encryption, identity verification, and rights assignment to secure IP access. It also has a module to detect and eliminate expired or unqualified IP to avoid occupying space. The system connects terminals to a database with a rights management device. User identity is verified and permissions assigned based on rules. Firewalls determine access based on permissions. This prevents IP file theft by making access encrypted and difficult to bypass. It also avoids occupying space with expired IP.

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5. System for Crawling and Analyzing App Store Metadata to Detect Intellectual Property Infringement

Focus IP Inc., 2016

Monitoring app stores for intellectual property infringement by crawling app stores, collecting metadata about apps, and analyzing it to detect potential IP violations. The system can also allow users to define brand tracking and receive alerts when apps using their brands change metadata. This provides a tool to combat trademark infringement and dilution in the app ecosystem.

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The development of a strong and inventive IT landscape is reliant on intellectual property and standards. A better and more dependable technical future can be achieved by the tech sector by making use of these developments to promote innovation and collaboration.

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