Intelligent Infusion System with Real-time Monitoring and Adaptive Therapy

Publication ID: 24-11857759_0003_PTD
Published: November 07, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Intelligent Infusion System with Real-time Monitoring and Adaptive Therapy,” Published Technical Disclosure No. 24-11857759_0003_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857759_0003_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. 11,857,759.

Summary of the Inventive Concept

The present inventive concept integrates IoT-enabled sensors, machine learning, computer vision, blockchain, and 3D printing to create a comprehensive infusion system that detects fluid levels in real-time, predicts optimal replenishment schedules, and provides personalized treatment recommendations, ensuring data integrity and transparency.

Background and Problem Solved

The original patent, 'System for detecting and reporting fluid levels in an infusion device', addressed the need for accurate fluid level monitoring in infusion devices. However, it had limitations in terms of real-time monitoring, data analysis, and adaptive therapy. The present inventive concept solves these limitations by incorporating advanced technologies to provide a more efficient, accurate, and personalized infusion system.

Detailed Description of the Inventive Concept

The intelligent infusion system consists of an IoT-enabled sensor module that tracks fluid levels in real-time, a machine learning module trained on historical infusion data to predict optimal fluid replenishment schedules, and a blockchain-based reporting module to ensure data integrity and transparency. The system can be integrated with a computer vision module to analyze images of the infusion bag, providing enhanced accuracy in fluid level detection. Additionally, the system can include a 3D printing module to fabricate customized infusion bags with integrated sensors, enabling real-time monitoring and adaptive therapy. The system can also be used to detect anomalies in infusion therapy, identifying deviations from expected patterns and alerting healthcare professionals of potential issues.

Novelty and Inventive Step

The integration of IoT-enabled sensors, machine learning, computer vision, blockchain, and 3D printing in a single infusion system is novel and non-obvious compared to the original patent. The use of machine learning to predict optimal fluid replenishment schedules and the incorporation of blockchain to ensure data integrity and transparency are particularly innovative aspects of the present inventive concept.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include using different types of sensors, such as ultrasonic or capacitive sensors, or integrating the system with electronic health records (EHRs) to provide a more comprehensive view of patient data. The system could also be adapted for use in different medical settings, such as clinics or ambulances.

Potential Commercial Applications and Market

The intelligent infusion system has significant commercial potential in the healthcare industry, particularly in hospitals and clinics. The system's ability to provide real-time monitoring, personalized treatment recommendations, and data integrity and transparency could lead to improved patient outcomes, reduced costs, and enhanced efficiency. The market for infusion systems is expected to grow significantly in the coming years, driven by the increasing demand for advanced medical technologies.

CPC Classifications

SectionClassGroup
A A61 A61M5/1684
A A61 A61J1/10
A A61 A61M2205/18
A A61 A61M2205/3306
A A61 A61M2205/3327
A A61 A61M2205/42

Field of Art

Medical Device Technology, specifically Infusion Monitoring Systems, involving sensor integration, data tracking, and medical device instrumentation

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device technologist with expertise in sensor systems, data analytics, IoT technologies, and medical instrumentation design, holding a master's degree or equivalent professional experience

Obviousness Rationale

A PHOSITA would recognize that the PTD's integration of IoT sensors, machine learning, and blockchain represents predictable technological extensions of the source patent's fluid monitoring framework. The core fluid detection methodology remains fundamentally consistent, with the PTD introducing standard engineering enhancements like computer vision and adaptive analytics. These variations represent incremental improvements using well-established technological approaches within medical device monitoring systems.

Obvious Combinations & Variations

Source Patent Element
Light-based fluid level detection system with control mechanisms
PTD Variation
IoT-enabled sensors with real-time tracking and machine learning predictive analytics
Obviousness Reasoning
Replacing analog sensor systems with digital IoT sensors is a known design evolution, representing a predictable technological progression with expected performance improvements
Source Patent Element
Reporting and warning module for system performance
PTD Variation
Blockchain-based reporting module ensuring data integrity and transparency
Obviousness Reasoning
Implementing blockchain for data verification is a standard approach in developing secure monitoring systems, representing an obvious technological enhancement
Source Patent Element
Fluid level monitoring using positioned light sources and sensors
PTD Variation
Computer vision module analyzing infusion bag images for enhanced detection accuracy
Obviousness Reasoning
Integrating computer vision with existing sensor systems is a predictable solution for improving measurement precision, utilizing known image processing techniques
Source Patent Element
Control system for monitoring infusion parameters
PTD Variation
AI-powered anomaly detection module identifying deviations from expected patterns
Obviousness Reasoning
Applying machine learning to detect system anomalies represents a standard engineering approach to enhancing monitoring capabilities
Source Patent Element
Basic infusion bag monitoring system
PTD Variation
3D printing module for fabricating customized infusion bags with integrated sensors
Obviousness Reasoning
Customizing medical device manufacturing through additive manufacturing is a recognized design optimization technique with predictable implementation strategies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857759 and the disclosed technological variations, a person of ordinary skill in the art would find the proposed infusion monitoring system improvements to be obvious extensions of existing fluid detection methodologies. The incremental technological enhancements represent predictable combinations of known techniques in medical device sensor systems, thereby rendering potential derivative claims non-patentable under standard obviousness criteria.

Original Patent Information

Patent NumberUS 11,857,759
TitleSystem for detecting and reporting fluid levels in an infusion device