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Ching Lee, Jeanne Tan and Jun Jong Tan's Chromaheat AI Heating Textile presents a striking compositional study centered upon the human figure captured from a posterior vantage point, the frame tightly
Chromaheat AI Heating Textile by Ching Lee, Jeanne Tan and Jun Jong Tan presents a sophisticated profile view of a technical garment composition that demonstrates exemplary integration of functional i
Ching Lee, Jeanne Tan and Jun Jong Tan's Chromaheat AI Heating Textile presents a sophisticated exploration of intelligent material design through the macro-photographic documentation of a technical t
Chromaheat AI Heating Textile by Ching Lee, Jeanne Tan and Jun Jong Tan presents a sophisticated exercise in minimalist product photography rendered against a pristine pale neutral ground that approac
A figure captured mid-motion in left-directed profile presents the dynamic performance of Ching Lee, Jeanne Tan and Jun Jong Tan's Chromaheat AI Heating Textile against a gradient atmospheric field tr

Laboratory for Artificial Intelligence in Design (AiDLab)

Bronze Wearable Technologies Design · 2025

Chromaheat AI Heating Textile

by Ching Lee, Jeanne Tan and Jun Jong Tan

  • A' Design Award 2025 Bronze Winner in Wearable Technologies Design
  • Awarded April 15, 2025
  • CLIENT: Laboratory for Artificial Intelligence in Design (AiDLab)
  • Estimated Number of Design Views: 35,031
  • Verification code 16E0679376 · Verify this award
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About Chromaheat AI Heating Textile

Chromaheat AI is an intelligent heating jacket that utilizes AI-driven temperature regulation and thermochromic yarn to provide adaptive warmth and real time visual feedback . Its self trained AI system adjusts heating based on age, gender, and environmental conditions, optimizing thermal comfort across different temperatures, humidity levels, and wind speeds. The color changing yarn offers visible heat indicators, enhancing safety, usability, and monitoring. Designed for daily wear, its energy efficient automated control makes it ideal for healthcare applications and smart textiles.

Chromaheat AI Heating Textile by Ching Lee, Jeanne Tan and Jun Jong Tan emerges from a rich lineage of wearable technology exploration that has accelerated dramatically in recent decades as miniaturized electronics, flexible circuitry, and advanced textile engineering converge to reimagine the fundamental relationship between clothing and human physiological support. This work appears to engage meaningfully with traditions of performance apparel design where garments transcend passive covering to become active environmental mediators, responding dynamically to bodily needs and external conditions, a conceptual territory pioneered by military and aerospace research before migrating into civilian applications ranging from athletic performance enhancement to medical therapeutic textiles and everyday comfort optimization. The compositional achievement demonstrates sophisticated understanding of visual communication strategies that must simultaneously document technical innovation and evoke experiential benefits, the centered posterior view eliminating distracting facial particularity to universalize the wearer, transforming the specific human figure into an everywearer with whom diverse audiences can identify, while the dramatic illumination of the integrated heating element creates immediate visual comprehension of the technology's location, form, and functional elegance. The chromatic sophistication merits particular attention, the design team evidently selecting a cyan-turquoise luminescence that suggests both technological modernity through its LED-like quality and natural vitality through associations with bioluminescence, clear water, and atmospheric phenomena, this color choice avoiding aggressive red or orange heating visualization that might connote danger or discomfort, instead proposing a cooling aesthetic paradoxically representing warming function, a conceptual sophistication that invites reflection on how color semiotics can expand or complicate functional associations. The garment's formal integration reveals accomplished technical execution, the heating element's linear grid pattern conforming elegantly to the curved topography of shoulders and upper back, suggesting either intelligent pattern cutting that pre-accommodates bodily contours or flexible circuitry capable of conforming to movement and posture variation, this successful integration of rigid technological components with soft flexible textile substrates representing one of wearable technology's persistent design challenges, here apparently resolved with grace that maintains both thermal performance and aesthetic refinement. The work seems to explore thematic territories surrounding human vulnerability to environmental conditions, the perpetual need for thermal regulation that consumes significant energy resources in built environments, and the potential for personalized microclimate control that could reduce collective heating demands while increasing individual comfort agency, themes resonating with contemporary sustainability discourse, energy conservation imperatives, and the broader cultural movement toward personalized responsive technologies that adapt to individual rather than collective needs. One might observe how this heating textile participates in longer design histories of augmented clothing, referencing perhaps early electrically heated flight suits, therapeutic heat wraps, and even metaphorically the luminous halos and radiant garments of religious iconography that visualize sanctity, protection, and divine favor, here secularized and democratized through technological means accessible to everyday users seeking practical comfort enhancement. The documentation style reveals careful attention to legibility and aesthetic appeal, the neutral background eliminating contextual distraction, the controlled lighting creating dramatic visual impact while maintaining faithful material representation, the tight cropping focusing attention precisely where innovation resides, these formal choices suggesting design team awareness that technological innovation must be communicated through compelling visual narratives that engage both rational understanding and emotional response, making abstract technical achievement tangible and desirable through strategic aesthetic framing. Viewers encountering this work might consider how wearable technologies propose new relationships between bodies and environments, how clothing evolves from passive protection toward active environmental modification, how visible technology integrates with or disrupts traditional garment aesthetics, and how design innovation serves fundamental human needs for comfort, agency, and environmental adaptation in an era of increasing climate variability and energy consciousness.

Press Kit

Unique Properties
ChromaHeat AI is an intelligent heating jacket that integrates AI-driven temperature regulation with thermochromic yarn, providing adaptive warmth and real-time color-changing temperature feedback. The self-trained AI system adjusts heating based on age, gender, and environmental factors, optimizing thermal comfort across varying temperatures, humidity levels, and wind speeds. Designed for everyday use, its energy-efficient control makes it ideal for healthcare technology.
Dimensions & Packaging
Materials: Silver-coated conductive yarn, thermochromic yarn, polymeric optical fiber, cotton.
Technology: AI-driven regulation, ANN model, Bluetooth, thermocouples MAX6675, ambient sensors BME680, FS3000.
Color Transitions: Pale purple to hot pink at 30 degrees Celsius in lit conditions; blue to yellow to red from 30 to 40 degrees Celsius and above in dark conditions.
Dimensions: International Male M (Chest: 970 mm, Length: 680 mm, Sleeve: 630 mm).
Tags
intelligent textile, heating textile, temperature control, thermochromic textile and healthcare
Production Technology
ChromaHeat AI is fabricated using woven and embroidered thermochromic yarn and polymeric optical fiber, combined with silver-coated conductive heating yarn, enabling real-time temperature visualization with high brightness in both lit and dark environments. It features a self-trained ANN-driven system, utilizing data from 50 wearability test subjects to determine optimal heating temperatures for intelligent temperature regulation across diverse users.
Design Challenge
The biggest challenge was training the AI model from scratch, as no publicly available datasets existed on optimal heating temperatures for thermal comfort across different users. To validate the concept, we recruited 50 subjects to test heating levels from 40 degree celsius to 60 degree celsius, identifying their preferred comfort temperatures. Additionally, constraints on age groups and testing conditions posed limitations, requiring careful data collection to ensure accuracy and applicability.
Project Duration
The project began in January 2021 and was completed in December 2024 in Hong Kong. The first prototype was exhibited at Sensory Stitches, Intelligent, Intuitive, Illuminative at Tai Kwun, Hong Kong, China, from September 8 to 13, 2022.
Operation Flow
ChromaHeat AI intuitively adjusts its heating levels using an AI-driven system that responds to the wearer's age, gender, and surroundings. Once worn, built-in sensors track environmental conditions and send data to the intelligent model, which fine-tunes warmth for maximum comfort and efficiency . Its color-changing and light-emitting features provide instant visual feedback , helping users monitor temperature shifts in real time, ensuring safety and ease of use in daily life.
Research
This research developed AI-driven heating e-textiles for personalized thermal comfort and healthcare safety through real-time temperature visualization. Data from 50 participants was collected to train an ANN model, which determines optimal heating temperatures from 40 to 50 degrees Celsius with a mean squared error of 5.083, demonstrating a high correlation between predicted and actual comfort levels. The results confirm enhanced thermal comfort and benefits for healthcare applications.
Inspiration
Existing heating e-textiles, such as Bluetooth-controlled systems, have advanced textile technology but still lack intelligent adaptation, requiring manual operation to adjust heating levels. They offer limited heat indication, typically displayed on small switches, making it difficult for users to monitor temperature changes. ChromaHeat AI was developed to address these limitations, aiming to enhance human well-being through smart heating textiles that improve comfort, safety, and efficiency.
Image Credits
Main Image: Photographer Henry Yeung – Heating position on the upper back of the body, 2024.
Optional Image #1: Photographer Chun Hei Lee – Integrated sensors in pocket with a small size, 2024.
Optional Image #2: Photographer Chun Hei Lee – Illuminative effect in a dark environment, 2022.
Optional Image #3: Photographer Chun Hei Lee – Jacket providing thermal comfort, 2024.
Optional Image #4: Photographer Chun Hei Lee – Minimalist and sporty design , 2024.
Patents
Patent Filed. Patent Application No. 2308943HK01. Lee, C., Tan, J., & Tan, J. J. 2023. China National Intellectual Property Administration. Jurisdiction: China. Filed on 10 October 2023.

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Design Interview about Chromaheat AI Heating Textile

The main principle behind my design is human-centered innovation —creating solutions that enhance comfort, usability, and well-being by integrating design with advanced technology. The core idea of my work is to bridge design and science , particularly through smart textiles that respond to real-life needs.

My inspiration often comes from scientific systems and natural processes . For example, the concept behind ChromaHeat AI was inspired by fuzzy logic-based temperature control systems used in air conditioners. This led me to explore how similar principles, enhanced by AI, could be applied to e-textiles to improve personal thermal comfort. By combining data-driven decision-making with responsive materials, I aim to design products that are both intelligent and empathetic—capable of adapting to people and their environments.

The main focus in designing ChromaHeat AI was to develop a smart, responsive textile system that can intelligently regulate temperature based on both environmental conditions and individual user profiles. Our goal was to achieve personalized thermal comfort through the integration of artificial intelligence, conductive materials, and woven fabric structures.

What we wanted to achieve with this work was a functional, user-centered solution that goes beyond traditional textile applications—something that adapts in real-time, improves well-being, and reflects the future of wearable technology. We aimed to bridge the gap between research and real-life use by creating a system that is not only technically advanced but also wearable, functional, and accessible.

Our future plans for the ChromaHeat AI design focus on enhancing its functionality and bringing it closer to market readiness . We aim to expand and diversify the dataset used to train the AI model, which will improve its ability to provide personalized thermal regulation for a wider range of users.

In addition, we are currently exploring the development of a cooling function , so the system can offer both heating and cooling capabilities —creating a comprehensive temperature-regulating solution for e-textiles. Our long-term goal is to finalize the product and commercialize it , making intelligent thermal-wear a practical and impactful option for everyday use in fashion, healthcare, and outdoor applications.

The design and development of ChromaHeat AI took approximately four years from concept to working prototype. This included extensive phases of research, material testing, textile fabrication, performance evaluation , and AI model development . The entire process was iterative, involving countless refinements to ensure the system was not only technically effective but also user-centered and wearable.

This design has not been commissioned—it is currently a prototype and a concept our team pursued, inspired by my academic research and interest in human-centered smart textiles. During my PhD studies, I saw a gap in how personal thermal comfort could be intelligently managed through wearable technology. Drawing inspiration from fuzzy logic systems used in air-conditioning, I wanted to explore how AI-driven temperature regulation could be applied to e-textiles .

The idea behind ChromaHeat AI came from a desire to create a solution that would combine functionality, adaptability, and comfort , while also pushing the boundaries of what textiles can do. It was a pursuit of innovation driven by curiosity, research, and a strong belief in the possibilities of design and technology working together to improve daily life.

At this stage, the design is in the advanced prototyping phase , and we are actively working on enhancing its functionality to prepare it for market release. We are open to exploring partnerships or licensing opportunities with companies that share our vision for innovative, human-centered smart textiles. Whether through direct production or strategic collaboration, our goal is to bring ChromaHeat AI to applications in healthcare , and other industries where intelligent thermal comfort can make a meaningful difference.

What inspired me to design this particular type of work was the desire to improve personal thermal comfort through intelligent, human-centered solutions. During my time working with flexible heating systems and through my academic research, I realized that existing thermal wearables often lacked adaptability and user specificity.

I saw an opportunity to bridge the fields of textile design, artificial intelligence, and material science to create an advanced system that could respond dynamically to individual needs and environmental changes. The concept behind ChromaHeat AI emerged from this realization—combining woven textile structures , conductive materials , and machine learning to design a product that not only functions effectively but also aligns with the growing expectations for smart, responsive, and wearable technologies.

Ultimately, it was the intersection of science, compassion, and innovation that drove me to create this work.

Yes, there were several influences that helped shape the design of ChromaHeat AI . One of the most significant was Professor Jeanne Tan , whose pioneering work in polymeric optical fiber-based illuminative textiles deeply inspired my approach to smart fabric integration. Her vision of blending technology with design for applications in fashion, interior, and rehabilitation has greatly influenced my thinking.

In addition, I also drew inspiration from intelligent control systems used in industrial design—particularly fuzzy logic-based temperature regulation in air conditioners. This concept showed me how environmental responsiveness could be translated into personal wearables through an AI-powered textile interface.

While ChromaHeat AI is an original concept developed by our team, it's built on the foundation of interdisciplinary innovation and influenced by both design mentors and real-world technological systems that prioritize user adaptability and functionality.

The target customers for the illuminative textiles include fashion designers and interior designers who are looking to integrate smart, responsive textile technologies into their creative projects.

What sets ChromaHeat AI apart from other similar concepts is its integration of artificial intelligence to deliver personalized, real-time thermal regulation through a woven textile system . Unlike traditional heated garments that offer limited, manual temperature settings, ChromaHeat AI uses an AI-powered predictive model —trained on user profiles and environmental data—to automatically adjust heating levels for optimal thermal comfort .

Additionally, ChromaHeat AI incorporates illuminative functionality , enabling the textile to change color in response to heating, which provides not only a visual indicator of the system’s operation but also an aesthetic enhancement. The use of woven conductive yarns and polymeric optical fibers makes the fabric flexible, durable, and suitable for real-life applications in fashion, interiors, and rehabilitation.

This holistic approach—merging data-driven intelligence, user-centered design, visual interactivity, and advanced textile engineering—is what truly distinguishes ChromaHeat AI from other smart textile products.

The name ChromaHeat AI was carefully chosen to reflect the core functions and innovation behind the design. 'Chroma' refers to the color-changing feature of the fabric, which visually indicates thermal activity through integrated illuminative fibers. 'Heat' highlights the temperature-regulating function of the e-textile, which delivers warmth in response to environmental and user-specific conditions. Finally, 'AI' signifies the use of artificial intelligence to personalize and automate temperature control based on real-time data and predictive modeling.

Together, ChromaHeat AI represents an intelligent textile system that combines heat, color, and smart adaptability —merging aesthetics and function in a wearable, data-driven solution.

For the development of ChromaHeat AI , we utilized a combination of textile design tools , hardware systems , and software platforms . To design and produce the woven structure, we used the CCI/SL7900 Rapier Sample Loom , which allowed us to integrate conductive yarns and optical fibers precisely into the fabric.

To evaluate heating efficiency, we used an infrared camera , which helped us visualize and analyze temperature distribution across different textile structures. For the AI component, we employed the Scikit-learn Machine Learning library in Python to develop and train an Artificial Neural Network (ANN) model that predicts and adjusts heating levels based on user and environmental data.

These tools together supported a research-driven, iterative design process , allowing us to fine-tune both the material properties and intelligent control system of the textile.

The most unique aspect of ChromaHeat AI is its ability to intelligently regulate temperature through a woven textile system , powered by an AI-driven predictive model . What truly sets it apart is the integration of personalized thermal comfort —the system adapts in real time based on a user’s physiological profile and changing environmental conditions.

In addition, the textile’s color-changing illuminative effect adds a visual and interactive dimension, making the experience not only functional but also emotionally engaging. This fusion of smart materials, artificial intelligence, and woven craftsmanship creates a design that is both technologically advanced and wearable, which is a rare combination in the current landscape of smart textiles.

Yes, ChromaHeat AI was developed through interdisciplinary collaboration with experts from both design and technical backgrounds. I worked closely with my PhD supervisor, Professor Jeanne Tan from the School of Fashion and Textiles at The Hong Kong Polytechnic University, who provided expertise in intelligent textile design and polymeric optical fiber integration .

I also collaborated with engineer Jun Jong Tan , who contributed specialized knowledge in system development and hardware integration , particularly in embedding functional components like heating elements, sensors, and developing the control system.

This project would not have been possible without this cross-disciplinary teamwork , bringing together design creativity, textile engineering, and AI technology to create a truly innovative and functional smart textile system.

Technology plays a central role in ChromaHeat AI , serving as the foundation for its functionality and innovation. The design incorporates artificial intelligence to enable personalized, real-time temperature regulation based on individual user profiles and environmental conditions. Using a trained Artificial Neural Network (ANN) , the system predicts and adjusts the heating levels intelligently.

Additionally, conductive yarns and polymeric optical fibers are woven into the textile to deliver both thermal response and visual feedback through a color-changing effect. The use of infrared imaging during development further allowed us to monitor and optimize performance.

Overall, technology transforms this textile from a passive material into an interactive, responsive, and adaptive system , redefining how garments and fabrics can support personal comfort and well-being.

Yes, ChromaHeat AI is deeply influenced by data and analytical research . The entire design process was built upon a research-driven framework, beginning with a comprehensive literature review on thermal comfort, smart textiles, and user-centered design. One key finding from the research was that the upper back torso is among the most thermally sensitive areas of the human body—this insight helped define the strategic placement of the heating zone.

We also conducted subject testing to collect physiological and environmental data—including user-specific factors such as age, gender, height, and weight , as well as variables like ambient temperature, humidity, and air velocity . This data was used to train an Artificial Neural Network (ANN) model via Scikit-learn in Python , allowing the textile system to intelligently predict the most suitable heating temperature for individual users.

In short, this design is a balance of creativity and technical accuracy , and it would not have been possible without an extensive process of data collection, pattern recognition, and applied machine learning to make informed, adaptive design decisions.

One of the main challenges in designing and realizing ChromaHeat AI was the integration of multiple complex systems —textile design, thermal regulation, and artificial intelligence—into a single cohesive and wearable product. Balancing flexibility, comfort, and functionality in a woven textile structure while embedding conductive yarns and optical fibers required extensive prototyping and material testing.

Another significant challenge was the lack of open-source data related to factors like user age, gender, body size, and environmental conditions in relation to thermal comfort. To overcome this, we conducted our own subject tests to gather the necessary data, which was then used to train the AI model. This process was time-consuming and demanded high precision to ensure the accuracy and reliability of the system.

Additionally, because Hong Kong doesn’t experience extreme cold weather, conducting outdoor performance tests for the heating textile was limited. To address this, we performed controlled indoor experiments to simulate a range of environmental conditions.

Despite these challenges, overcoming each hurdle helped refine the project into a truly innovative and user-responsive design.

I decided to submit ChromaHeat AI to an international design competition because I wanted to share our research-driven innovation with a global audience and receive professional recognition that extends beyond the academic and scientific community. The A’ Design Award, in particular, stood out as a respected platform that values interdisciplinary and socially impactful design —which aligns perfectly with the goals of this project.

Submitting to an international competition was also a strategic decision to validate our work , gain exposure , and build meaningful connections across industries , from tech and fashion to healthcare and interior design. It’s an opportunity to showcase how intelligent textiles can play a transformative role in daily life, and it helps open doors for future collaborations, funding, and commercialization .

Designing ChromaHeat AI was a transformative learning experience that allowed me to grow significantly as both a researcher and designer . One of the biggest lessons I learned was the importance of interdisciplinary collaboration —working closely with engineers, textile specialists, and AI developers taught me to communicate across technical boundaries and foster a shared vision.

I also deepened my understanding of user-centered design methods , especially when collecting and analyzing data to guide function and usability. Developing and applying an AI-powered control system not only expanded my technical skill set but also showed me the value of real-time adaptability in creating meaningful experiences for users.

Perhaps most importantly, this project taught me the value of iteration and resilience . There were many challenges, from material limitations to data collection hurdles, but each challenge pushed me to think creatively, refine my process, and remain flexible. As a result, I emerged more confident in integrating design with research, and better equipped to lead future innovations in smart textiles.

One additional point I’d like to highlight is the role of knowledge transfer and commercialization in our work. Following the development of ChromaHeat AI , our team established a spin-off company, GERI LIMITED , which focuses on the production and customization of illuminative fabrics . This step allows us to take our research beyond the lab and bring it into real-world applications across fashion, interior design, and healthcare.

We’re particularly passionate about creating accessible, human-centered smart textiles that not only serve functional needs but also open new creative possibilities for designers and industry professionals. We’re always looking for new collaborators and partners who share our vision of merging design, science, and technology in ways that improve daily life.

Finally, I’d like to express my gratitude for platforms like the A' Design Award that recognize interdisciplinary innovation. It’s through opportunities like these that researchers and designers can gain visibility, share knowledge, and inspire progress across global design communities.

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