Applying Insulin Management Technology to Novel Industries

Publication ID: 24-11857314_0007_PTD
Published: November 07, 2025
Category:New Applications & Use Cases

Legal Citation

pr1or.art Inc., “Applying Insulin Management Technology to Novel Industries,” Published Technical Disclosure No. 24-11857314_0007_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857314_0007_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. 11,857,314.

Summary of the Inventive Concept

This inventive concept leverages the core technology of insulin management to develop innovative solutions for optimizing crop yields, reducing food waste, monitoring indoor air quality, predicting water scarcity, and optimizing energy efficiency in commercial buildings.

Background and Problem Solved

The original insulin management patent addressed the critical need for accurate and efficient insulin dosing in medical settings. However, the underlying technology has broader applications beyond healthcare. This inventive concept tackles the limitations of the original patent by applying its core principles to novel industries, where data-driven decision-making and real-time analytics can drive significant improvements in efficiency, sustainability, and productivity.

Detailed Description of the Inventive Concept

The new claims encompass a range of applications, including crop yield optimization, food waste reduction, indoor air quality monitoring, water scarcity prediction, and energy efficiency optimization. In each of these domains, the inventive concept integrates data processing hardware, machine learning algorithms, and real-time analytics to drive informed decision-making. For instance, in crop yield optimization, the system analyzes weather patterns, soil conditions, and crop growth parameters to recommend optimal irrigation schedules and fertilizer application rates. Similarly, in food waste reduction, the system tracks inventory levels, expiration dates, and consumer demand patterns to generate optimized logistics and storage plans.

Novelty and Inventive Step

The novelty of this inventive concept lies in its application of insulin management technology to entirely new industries, leveraging the strengths of data-driven decision-making and real-time analytics to address pressing challenges. The inventive step is the recognition that the core principles of insulin management can be adapted and applied to diverse domains, resulting in innovative solutions that drive significant improvements in efficiency, sustainability, and productivity.

Alternative Embodiments and Variations

Alternative embodiments of this inventive concept could include the integration of additional data sources, such as IoT sensors, social media analytics, or satellite imaging. Variations could also involve the development of specialized modules or interfaces tailored to specific industries or use cases.

Potential Commercial Applications and Market

The commercial potential of this inventive concept is substantial, with applications in agriculture, logistics, real estate, and environmental sustainability. The target market includes companies and organizations seeking to optimize their operations, reduce waste, and improve their environmental footprint. By applying the core technology of insulin management to novel industries, this inventive concept has the potential to drive significant economic, social, and environmental impact.

Field of Art

Medical informatics and data processing systems for healthcare analytics, specifically focused on physiological parameter monitoring, data-driven decision support, and algorithmic management of complex medical conditions

Person of Ordinary Skill (PHOSITA) Profile

A professional with expertise in biomedical engineering, computer science, or healthcare information systems, possessing advanced knowledge of data processing, machine learning algorithms, sensor integration, and predictive analytics for healthcare and related complex systems

Obviousness Rationale

The PTD demonstrates a straightforward extension of the source patent's core technological framework of data-driven parameter monitoring and algorithmic decision support. By applying the fundamental principles of sequential measurement analysis, predictive modeling, and real-time intervention from insulin management to other complex systems, a PHOSITA would recognize an obvious technological translation. The source patent's core methodological approach of receiving sequential measurements, processing data through machine learning algorithms, and generating actionable recommendations is directly transferable across multiple domains.

Obvious Combinations & Variations

Source Patent Element
Receiving sequential glucose measurements from electronic medical record systems or continuous monitoring devices
PTD Variation
Receiving sequential environmental or operational measurements from IoT sensors and integrated data systems
Obviousness Reasoning
A PHOSITA would recognize that the measurement collection methodology is fundamentally consistent across different measurement domains, representing a predictable application of a known technique
Source Patent Element
Determining intervention rates based on current measurements and predefined algorithmic parameters
PTD Variation
Generating optimization recommendations for crop irrigation, energy consumption, or supply chain logistics using similar algorithmic frameworks
Obviousness Reasoning
The computational approach of parameter-driven decision support is a known technique that can be readily adapted across complex systems with measurable variables
Source Patent Element
Computer-implemented method utilizing data processing hardware to analyze sequential measurements
PTD Variation
Applying machine learning modules to analyze sensor data and predict trends in water scarcity, indoor air quality, and building energy efficiency
Obviousness Reasoning
The technical framework of data-driven predictive analytics represents a finite set of solution approaches that would be obvious to combine across different technical domains
Source Patent Element
Real-time analytics for medical intervention based on continuous monitoring
PTD Variation
Real-time analytics for operational optimization in agricultural, environmental, and infrastructure management systems
Obviousness Reasoning
The core principle of using continuous data streams to generate immediate, algorithmically-derived recommendations is a well-established and predictable technological approach
35 U.S.C. § 103 Summary: Based on the technological teachings of US Patent 11857314 for insulin management, the present publication demonstrates that the claimed innovations represent obvious variations to a Person Having Ordinary Skill In The Art, as the fundamental methodological approach of sequential measurement analysis, machine learning-driven decision support, and real-time intervention can be readily translated across complex systems through known computational techniques.

Original Patent Information

Patent NumberUS 11,857,314
TitleInsulin management
Assignee(s)Aseko, Inc.