I
am reposting these 2 articles from Nanowerk. Just from a breath sensor
your behaviors can be accurately monitored. And AI can now 3 D print
your food. Welcome to Technocracy. Are you keeping up or are you
experiencing Future Shock?
Nanostructured humidity sensor achieves 96% accuracy in identifying human behaviors through breath analysis
(Nanowerk Spotlight)
Each exhaled breath carries distinct signatures of human activity -
quick and shallow during exercise, deep and regular in sleep, irregular
while speaking. These breathing patterns provide a window into behavior,
but capturing and interpreting these subtle respiratory variations has
challenged scientists and engineers. Camera systems can track physical
movements but miss physiological nuances. Wearable devices require
multiple sensors that increase bulk and complexity. Traditional humidity
sensors, while promising for breath detection, lack the sensitivity and
response speed (around 2.2 seconds for recovery in this sensor)
required to capture rapid moisture changes in exhaled air. The technical
challenge lies in detecting minute humidity variations quickly enough
to map them to specific behaviors. Chinese researchers have engineered a
solution: a humidity sensor that uses microscopic "nanoforests" to
detect subtle changes in breath moisture. Published in Microsystems & Nanoengineering ("An intelligent humidity sensing system for human behavior recognition"),
their system combines these specialized structures with precise
temperature control to achieve 96.2% accuracy in distinguishing between
nine different human behaviors. The sensor's nanoforests create an
extensive surface area covered in hydrophilic groups - molecular
structures that readily interact with water molecules. Elevated
operating temperatures further increase the activity and diffusion speed
of these molecules, significantly boosting sensor sensitivity. When a
person exhales, water vapor from their breath adheres to these surfaces
through hydrogen bonding, forming initial chemical bonds. As humidity
increases, additional water molecules stack onto this first layer
through weaker physical bonds, creating multiple layers that the sensor
can detect.
A
built-in micro-heater maintains the sensor at 57.1°C, increasing its
sensitivity by nearly six times compared to room temperature operation.
This enhancement allows detection of even slight variations in breath
moisture. An integrated thermistor continuously monitors temperature,
providing additional data about breathing patterns. The system processes
this combined humidity and temperature data through a machine learning
algorithm that converts the measurements into two-dimensional maps.
These maps serve as input for a neural network trained to recognize
specific behaviors. The researchers tested the system's
ability to identify nine distinct states: working, speaking, walking,
playing electronic games, sleeping, sighing, breath holding, jumping,
and exercising. The results demonstrated perfect recognition of five
behaviors - working, walking, sleeping, sighing, and breath holding. The
system occasionally confused similar activities, such as misclassifying
jumping as exercise due to comparable breathing patterns. Speaking was
sometimes mistaken for gaming activity, likely due to overlapping
respiratory characteristics. The sensor maintained consistent
performance through more than 1,000 consecutive breathing cycles,
demonstrating robust stability. It also showed high selectivity for
water vapor compared to other breath components like oxygen, carbon
dioxide, and nitrogen, ensuring accurate humidity measurements even in
complex respiratory environments. The researchers
integrated their sensor into a face mask that wirelessly transmits
breathing data to smartphones or computers for real-time analysis. This
implementation enables continuous behavior monitoring without requiring
multiple devices or complex setups.
The
technology offers particular utility in healthcare settings, where
automated behavior tracking could help monitor patient activity levels
and sleep patterns. In smart homes, the system could adjust
environmental controls based on detected behaviors. The
non-invasive nature of humidity sensing preserves privacy while
providing detailed insights into physical and physiological states. The
sensor's ability to extract behavioral information from breath moisture
represents a shift in human activity monitoring. By focusing on this
single, information-rich parameter, the system achieves sophisticated
behavior recognition without the complexity of multiple sensor types or
the privacy concerns of video monitoring. The research demonstrates how
precise measurement of a fundamental physiological process - breathing -
can reveal complex patterns of human behavior. This
technical advancement brings automated behavior recognition closer to
practical implementation in healthcare and daily life applications.
AI-powered 3D printer cooks food in real-time, automating commercial food prep
(Nanowerk Spotlight)
A new 3D printer can cook food layer by layer as it prints, using
artificial intelligence to design complex edible structures. This
integrated system, developed at Hong Kong University of Science and
Technology, combines precision infrared heating with AI-driven design
tools to address key limitations in automated food production:
maintaining food safety during printing and creating intricate shapes
without requiring technical expertise. The findings have been reported
in Advanced Materials ("Advanced 3D Food Printing with Simultaneous Cooking and Generative AI Design").
Automated food production faces unique challenges compared to
manufacturing with traditional materials like plastics or metals. Food
must be heated properly to ensure safety, yet maintaining the intended
shape during cooking proves difficult. Current 3D food printers operate
in two separate steps - first printing cold food paste, then
transferring it to an oven or fryer. This approach often leads to
deformed shapes and increased contamination risks as the food moves
between machines. The new system integrates these steps using a
specialized infrared heater made from laser-treated polyimide film,
known as laser-induced graphene (LIG). This ultra-thin heating element
provides precise temperature control, with printed food layers reaching
137°C on the surface and maintaining at least 105°C on the sides
throughout the printing process, while using just 14 watts of power - a
fraction of the 1000-2000 watts consumed by conventional ovens and air
fryers.
The
researchers demonstrated their printer using starch-based cookie dough.
As each layer of dough emerges from the printing nozzle, the infrared
heater immediately cooks it, maintaining the exact printed shape while
killing harmful bacteria. This immediate cooking prevents the slumping
and deformation that typically occurs when printed food items wait to be
baked. Detailed analysis revealed superior results compared to
conventional cooking methods. Using scanning electron microscopy, the
team observed that infrared-cooked samples maintained consistent
internal structure without the dramatic swelling seen in oven-baked
items. X-ray imaging showed uniform porosity throughout the food,
indicating thorough cooking without compromising structural integrity.
Additionally, COMSOL simulations confirmed even heat distribution,
showing that heat penetrated only 1-2 mm from the top layer, preventing
overcooking of the lower layers. The system's food safety advantages
became clear through bacterial testing. While conventionally cooked
samples showed substantial bacterial growth after 48 hours,
infrared-treated items had only 0-6 bacterial colonies at 100°C,
compared to over 200 colonies in oven-baked and air-fried samples. This
improvement stems from the immediate high-temperature treatment of each
printed layer. The researchers also simplified the design process
through artificial intelligence. Instead of requiring users to master
complex 3D modeling software, their system accepts simple text
descriptions. These descriptions feed into the DALL-E AI system, which
generates appropriate 2D images. A custom Python script then converts
these images into STL 3D modeling files, making them ready for printing
without additional user intervention. A baker could type "gingerbread
man with detailed pattern" and receive a complete, printable design
within minutes. Testing demonstrated the system's versatility. The
printer successfully created items with intricate perforated patterns
and multiple layers while maintaining precise dimensional accuracy.
Beyond cookie dough, it handled various food materials, including
vegetable purees and protein-based ingredients, further validating the
system’s adaptability to different food types. The technology's
implications extend beyond simple food printing. The combination of AI
design tools and integrated cooking capabilities opens possibilities for
automated commercial food production. The system's energy efficiency
and compact size make it practical for restaurants and bakeries seeking
to offer customized food items without extensive technical training. The
researchers envision particular value in healthcare settings, where
precise control over ingredients and portions is crucial. The technology
could enable automated production of specialized diets while ensuring
consistent quality and safety. Their work also demonstrates broader
applications for integrated heating in 3D printing. The precise
temperature control and energy efficiency achieved through their LIG
heating system could benefit manufacturing processes beyond food
production. The integration of AI design capability with real-time
cooking represents a significant step toward accessible automated food
production. By addressing both the technical and usability challenges
that have limited adoption of 3D food printing, this system offers a
practical path toward more automated, customizable food service
operations while maintaining high standards for safety and quality. The
development signals a shift in how commercial kitchens might approach
personalized food production, suggesting a future where complex custom
food items can be created safely and efficiently without specialized
technical knowledge.
No comments:
Post a Comment