Published Technical Disclosure Archive

Sustainable Apparel Recycling System: AI-Driven Innovation

Publication ID: 24-11857013_0003_PTD
Published: October 27, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Sustainable Apparel Recycling System: AI-Driven Innovation,” Published Technical Disclosure No. 24-11857013_0003_PTD, Published October 27, 2025, available at https://archive.pr1or.art/24-11857013_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. 11,857,013.

Background and Problem Solved

The original patent disclosed methods of assembling apparel products with shape memory adhesives, but it did not address the significant environmental issue of apparel waste. The present invention addresses this limitation by integrating distinct technologies to create a closed-loop system for recycling and reusing apparel products.

Novelty and Inventive Step

The new claims introduce a synergistic combination of shape memory adhesives with AI, IoT, and blockchain technologies, enabling a closed-loop system for apparel recycling and management. This integration of distinct technologies provides a non-obvious solution to the environmental issue of apparel waste.

Alternative Embodiments and Variations

Alternative embodiments may include the use of different types of sensors, such as RFID or NFC, or the integration of additional technologies like augmented reality or 5G connectivity. Variations may also include the application of this system to other product categories, such as electronics or furniture.

Potential Commercial Applications and Market

The intelligent apparel recycling and management system has significant commercial potential in the sustainable fashion and textile industries, with potential applications in product design, manufacturing, and retail. The system can help companies reduce waste, improve supply chain efficiency, and enhance their environmental reputation.

CPC Classifications

SectionClassGroup
A A41 A41H43/04
C C09 C09J5/00
C C09 C09J2203/358

Field of Art

Textile engineering, materials science, and apparel product manufacturing with a focus on advanced adhesive technologies and smart material integration

Person of Ordinary Skill (PHOSITA) Profile

A professional with a bachelor's or master's degree in materials engineering, textile science, or related field, with expertise in polymer chemistry, adhesive technologies, and emerging smart material applications

Obviousness Rationale

A PHOSITA would recognize that integrating IoT, AI, and blockchain technologies with shape memory adhesive systems represents a predictable extension of existing smart material approaches. The source patent's focus on shape memory adhesives provides a clear technical foundation for incorporating advanced tracking and management technologies. The combination of these technologies addresses known challenges in product lifecycle management and recycling, using well-established integration techniques.

Obvious Combinations & Variations

Source Patent Element
Shape memory adhesive system for disassembling apparel products
PTD Variation
Adding blockchain-based tracking module to monitor product lifecycle
Obviousness Reasoning
Tracking product lifecycle is a known technique in smart manufacturing, and a PHOSITA would find it obvious to extend shape memory adhesive technologies with digital tracking systems to improve recyclability
Source Patent Element
Electromagnetic energy-responsive shape memory materials
PTD Variation
Integrating IoT sensors to monitor wear and trigger disassembly processes
Obviousness Reasoning
Sensor integration with responsive materials is a predictable solution for creating smart, self-monitoring systems, particularly in advanced textile engineering
Source Patent Element
Composition for assembling and disassembling apparel components
PTD Variation
AI-powered sorting module to categorize and direct recycling of disassembled components
Obviousness Reasoning
Automated sorting and material classification are well-known techniques in recycling technologies, representing an obvious application of machine learning to the existing shape memory adhesive system
Source Patent Element
Methods of applying shape memory compositions to apparel components
PTD Variation
Cloud-based platform for analyzing IoT sensor data and predicting product lifespan
Obviousness Reasoning
Data-driven lifecycle prediction is a standard approach in smart manufacturing, and a PHOSITA would find it obvious to apply such techniques to shape memory adhesive apparel systems
35 U.S.C. § 103 Summary: Based on US Patent 11857013's teachings of shape memory adhesive systems for apparel, the present disclosure demonstrates that a person having ordinary skill in the art would find the integration of blockchain, IoT, and AI technologies with shape memory adhesive systems to be an obvious and predictable variation, thus rendering potential claims in this domain anticipated and non-patentable prior art.

Original Patent Information

Patent NumberUS 11,857,013
TitleMethods of assembling apparel products having shape memory adhesives
Assignee(s)CreateMe Technologies Inc.