Published Technical Disclosure Archive

Intelligent Insulin Delivery System with AI, IoT, and Blockchain Integration

Publication ID: 24-11857763_0008_PTD
Published: November 07, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Intelligent Insulin Delivery System with AI, IoT, and Blockchain Integration,” Published Technical Disclosure No. 24-11857763_0008_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857763_0008_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,763.

Summary of the Inventive Concept

A novel insulin delivery system that combines AI-powered glucose level prediction, IoT-enabled insulin delivery, and blockchain-based secure data storage to provide personalized and optimized insulin delivery rates for diabetes patients.

Background and Problem Solved

The original patent, 'Adjusting insulin delivery rates,' has limitations in terms of accuracy and security. The new inventive concept addresses these limitations by integrating AI, IoT, and blockchain technologies to provide a more accurate, secure, and transparent insulin delivery system.

Detailed Description of the Inventive Concept

The system comprises a glucose measurement device, a processor, a communication module, and an insulin delivery module. The processor uses AI algorithms to predict multiple future blood glucose levels for multiple different basal insulin delivery profiles. The communication module transmits the predicted future blood glucose levels to a blockchain network, which verifies and securely stores the data. The insulin delivery module adjusts the basal insulin delivery rate based on the predicted future blood glucose levels. The system can also integrate with IoT devices to provide real-time monitoring and adjustments.

Novelty and Inventive Step

The new inventive concept is novel and non-obvious due to the integration of AI, IoT, and blockchain technologies, which provides a secure, transparent, and personalized insulin delivery system. The use of AI algorithms to predict future blood glucose levels and the integration with blockchain and IoT devices are significant advancements over the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include using different AI algorithms, such as neural networks or machine learning, to predict future blood glucose levels. The system could also be integrated with other technologies, such as wearables or mobile devices, to provide additional data and functionality.

Potential Commercial Applications and Market

The inventive concept has significant commercial potential in the diabetes management market, with potential applications in hospitals, clinics, and home care settings. The system could be marketed as a premium product, offering advanced features and functionality to diabetes patients and healthcare providers.

CPC Classifications

SectionClassGroup
A A61 A61M5/1723
A A61 A61B5/14532
A A61 A61B5/4839
A A61 A61M5/142
A A61 A61M5/145
A A61 A61M5/14244
A A61 A61M5/14248
G G16 G16H20/17
G G16 G16H40/60
G G16 G16H40/67
A A61 A61B2562/0295
A A61 A61M2005/14208
A A61 A61M2205/3303
A A61 A61M2205/3553
A A61 A61M2205/3561
A A61 A61M2205/3569
A A61 A61M2205/3584
A A61 A61M2205/502
A A61 A61M2205/52
A A61 A61M2230/005
A A61 A61M2230/201
G G16 G16H10/60
G G16 G16H40/40
G G16 G16H50/30

Field of Art

Medical device technology focused on diabetes management, specifically insulin delivery systems, involving complex algorithmic prediction of glucose levels and personalized medical treatment strategies

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device specialist with expertise in diabetes management technologies, proficient in AI/machine learning algorithms, data processing, and medical device integration, holding at least a master's degree with 3-5 years of relevant industry experience

Obviousness Rationale

A PHOSITA would recognize that integrating AI prediction, blockchain verification, and IoT monitoring into an existing insulin delivery method represents a predictable technological evolution. The source patent's foundational glucose prediction methodology provides a clear technical framework that naturally invites computational and networking enhancements. The proposed variations represent incremental improvements using standard engineering techniques available in the medical device and digital health domains.

Obvious Combinations & Variations

Source Patent Element
Calculating multiple insulin delivery profiles with probabilistic glucose level predictions
PTD Variation
Implementing AI and machine learning algorithms to enhance glucose prediction accuracy and generate more sophisticated delivery profiles
Obviousness Reasoning
Applying advanced computational techniques to existing probabilistic modeling represents a known method of improving medical prediction systems with predictable results
Source Patent Element
Obtaining user input regarding hypoglycemia risk
PTD Variation
Integrating blockchain technology to securely store and verify patient risk data and glucose predictions
Obviousness Reasoning
Using blockchain for secure medical data management is a standard approach in digital health technologies, representing an obvious extension of existing data handling methods
Source Patent Element
Calculating insulin delivery profiles across multiple time intervals
PTD Variation
Implementing IoT device integration for real-time monitoring and dynamic insulin rate adjustments
Obviousness Reasoning
Extending medical device functionality through networked monitoring represents a predictable technological progression in personalized medical treatment systems
Source Patent Element
Method for calculating future glucose values across multiple insulin delivery profiles
PTD Variation
Using neural network algorithms trained on multi-user diabetes data to improve prediction accuracy
Obviousness Reasoning
Applying machine learning techniques to medical prediction systems is a well-established approach for enhancing diagnostic and treatment methodologies
Source Patent Element
Baseline insulin rate adjustment based on probabilistic calculations
PTD Variation
Dynamic AI-powered selection of optimal insulin delivery profiles based on predicted future glucose levels
Obviousness Reasoning
Utilizing computational intelligence to optimize medical treatment parameters represents a standard engineering approach with predictable technological outcomes
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857763 and the disclosed technological variations, a person of ordinary skill in the art would find the proposed insulin delivery system improvements obvious and lacking inventive distinctiveness. The incremental advancements in AI prediction, blockchain verification, and IoT integration represent predictable technological extensions of existing medical device methodologies, thereby rendering potential patent claims obvious and unpatentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,763
TitleAdjusting insulin delivery rates
Assignee(s)INSULET CORPORATION