BRN Discussion Ongoing
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- Start date
Slymeat
Move on, nothing to see.
It’s good seeing other paid members have finally worked out how to edit their “custom title”.
Nvidia use 16-bit or 32-bit weights/actuations.
3rd Generation Tensor Cores and Sparsity NVIDIA Tensor cores provide the performance necessary to accelerate next generation AI applications. Tensor cores are programmable fused matrix-multiply-and-accumulate units that execute concurrently alongside the CUDA cores. Tensor cores implement floating point HMMA (HalfPrecision Matrix Multiply and Accumulate) and IMMA (Integer Matrix Multiple and Accumulate) instructions for accelerating dense linear algebra computations, signal processing, and deep learning inference
They do try to fudge a bit of sparsity by ignoring zeros if 2 out of every 4 bits are non-zero (or do they mean if 2 out of every 4 bits are zero?). Anyhow, they have to count the bits (fine-tuning weights), and add the address (value) of the non-zero bits (non-zero indices, ie, is its value 1, 2, 4, 8, 16, 32, ...?). Rather inelegant!
https://developer.nvidia.com/blog/nvidia-jetson-agx-xavier-32-teraops-ai-robotics/
The latest generation of NVIDIA’s industry-leading Jetson AGX family of embedded Linux high-performance computers, Jetson AGX Xavier delivers GPU workstation class performance with an unparalleled 32 TeraOPS (TOPS) of peak compute and 750Gbps of high-speed I/O in a compact 100x87mm form-factor. Users can configure operating modes at 10W, 15W, and 30W as needed for their applications. Jetson AGX Xavier sets a new bar for compute density, energy efficiency, and AI inferencing capabilities deployable to the edge, enabling next-level intelligent machines with end-to-end autonomous capabilities.
There is an opportunity to plug Akida in in place of the Vision Accelerator in the green Xavier SoC box - but they have Watts to burn.
So, on the disclosed information ...
I'm there on the "empty vessels" principle.
Boab
I wish I could paint like Vincent
Thanks for that. We can all have a bit of fun
Rise from the ashes
Regular
The worm has turned back in the day it was all about max power now it's all about efficiency.
Rise from the ashes
Regular
I still do a double take every now and then when I see your profile picture.
GStocks123
Regular
Very interesting release on Professor Hossam Haicks progress
www.israel21c.org
Why scent is the next frontier for technology - ISRAEL21c
Scientists and entrepreneurs are increasingly turning to scent to help detect disease, boost memory, entertain, and protect people from food allergies.
www.israel21c.org
Rise from the ashes
Regular
So they are trying to reopen the ozone layer again.
thelittleshort
Top Bloke
Internet of Medical Things security issue Akida can solve by processing data on the device?
blogs.cisco.com
As Internet-Connected Medical Devices Multiply, So Do Challenges
As internet-connected medical devices become more prevalent, so do security challenges for health care organizations.
blogs.cisco.com
Food4 thought
Regular
I have see big billboards in Taylor square for apple
Advertising that iPhone is privacy
Just made me think I wonder if the new phones are going to work on chip more in the future.
Just a thought
thelittleshort
Top Bloke
Can’t get much more ubiquitous than smart clothing
www.sentinelofsafety.com
Over the couple of decades, we've witnessed the evolution of wearables from a gimmick straight out of science fiction into a practical technology embraced by the mainstream. From fitness to healthcare to worker safety, more and more people are turning to wearables to provide real-time physiological data. In fact, Cisco Systems recently predicted that the number of wearable devices connected to networks will likely top a billion (with a b) by the end of 2022.
The technology itself is constantly evolving as well. The Fitbit (introduced in 2009) paved the way for smart watch monitors and smart rings. But now there's a new wearable technology on the block--smart fabric. And it looks to be a game changer.
While the need for heat- and light-sensitive fabric was originally driven by the sportswear market, the technology is rapidly expanding to other sectors.
Imagine an employee uniform that's capable of capturing relevant health and safety signals--location, movement, biological reads, environmental conditions--and relaying them to an inspector or spotter. Or gloves that measure real-time vibration exposure to help workers avoid HAVS (hand-arm vibration syndrome).
For example, getting an EKG reading from a wearable is currently problematic. Watches and other devices can measure EKG, but they require the user to actively touch it to activate the scan. For continuous EKG monitoring without user intervention, healthcare providers have to rely on adhesive patches.
A shirt or a pair of pants made from e-textiles could provide continuous, real-time biometrics that would, in turn, help physicians to provide a more accurate diagnosis and treatment options.
While current monitors can readily track real-time physiological, performance, and safety readings, e-textiles have the potential to provide data that's even more granular and specific. The ability to continuously monitor an athlete's posture and body movement could be vital to improving technique *and* avoiding future injuries.
Here at Sentinel, we're really excited about the potential of this new technology and you can bet we'll be looking for ways to integrate it with our current line of products as it develops.
"Global Smart Wearable Market - Market to Grow by 19.48% from 2021 - 2026" - Business Wire
"Smart Safety Wear" - Health & Safety International Magazine
"Smart Fabrics for Sports and Fitness Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022-2027)" -Mordor Intelligence
"'Smart Clothes' Can Conduct Bluetooth and Wi-Fi to Link All Your Tech at Once, and Can Boost Battery Life by 1,000" - Business Insider
Smart Fabric and the Next Generation of Wearables - VigiLife
Smart fabric (a.k.a. intelligent textiles and e-textiles) look to be game-changers in the worker safety, health & wellness, and physical performance industries. Read on to learn more about smart fabric and its impact on wearable sensors.
www.sentinelofsafety.com
How Will Electronic Textiles Impact the future of Wearable Sensors?
Over the couple of decades, we've witnessed the evolution of wearables from a gimmick straight out of science fiction into a practical technology embraced by the mainstream. From fitness to healthcare to worker safety, more and more people are turning to wearables to provide real-time physiological data. In fact, Cisco Systems recently predicted that the number of wearable devices connected to networks will likely top a billion (with a b) by the end of 2022.
The technology itself is constantly evolving as well. The Fitbit (introduced in 2009) paved the way for smart watch monitors and smart rings. But now there's a new wearable technology on the block--smart fabric. And it looks to be a game changer.
What Is Smart Fabric?
Smart fabrics are textiles that look and feel like standard fabrics but contain sensors and other tech components that give it the ability to sense and respond to environmental conditions. This technology is also known as intelligent textiles, electronic textiles, or e-textiles.While the need for heat- and light-sensitive fabric was originally driven by the sportswear market, the technology is rapidly expanding to other sectors.
Worker Safety
Wearable devices with sensors are already being used to protect workers from heat, exhaustion, and injury. But with smart fabric, these sensors will become even more unobtrusive than the current generation of smart watches, heart rate monitors, and gas sensors.Imagine an employee uniform that's capable of capturing relevant health and safety signals--location, movement, biological reads, environmental conditions--and relaying them to an inspector or spotter. Or gloves that measure real-time vibration exposure to help workers avoid HAVS (hand-arm vibration syndrome).
Health and Wellness
Smart textiles can also revolutionize the way providers monitor and care for patients. By integrating discrete biosensors and chemical sensors into clothing, physicians can get a more accurate view of a patient's health.For example, getting an EKG reading from a wearable is currently problematic. Watches and other devices can measure EKG, but they require the user to actively touch it to activate the scan. For continuous EKG monitoring without user intervention, healthcare providers have to rely on adhesive patches.
A shirt or a pair of pants made from e-textiles could provide continuous, real-time biometrics that would, in turn, help physicians to provide a more accurate diagnosis and treatment options.
Physical Performance
Sports and fitness is a major driver of smart fabric technology as companies and trainers continue to look for ways to improve the performance of athletes. According to report from Mordor Intelligence, the market for smart fabrics in sports and fitness was valued at $680 million in 2020 and is expected to hit $2.85 billion by the end of 2026.While current monitors can readily track real-time physiological, performance, and safety readings, e-textiles have the potential to provide data that's even more granular and specific. The ability to continuously monitor an athlete's posture and body movement could be vital to improving technique *and* avoiding future injuries.
The Future of Smart Fabric
Although widespread adoption of smart fabric is still years away, there have already been a number ofimpressive innovations, such as Wi-Fi/Bluetooth connectivity and amazing power efficiency. Plus, most smart fabric garments can be laundered like any normal clothing.Here at Sentinel, we're really excited about the potential of this new technology and you can bet we'll be looking for ways to integrate it with our current line of products as it develops.
References
"Smart Fabric - An Overview" - ScienceDirect"Global Smart Wearable Market - Market to Grow by 19.48% from 2021 - 2026" - Business Wire
"Smart Safety Wear" - Health & Safety International Magazine
"Smart Fabrics for Sports and Fitness Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022-2027)" -Mordor Intelligence
"'Smart Clothes' Can Conduct Bluetooth and Wi-Fi to Link All Your Tech at Once, and Can Boost Battery Life by 1,000" - Business Insider
thelittleshort
Top Bloke
Remote Healthcare and the Internet of Medical Things
Learn more about the internet of medical things or IoT, its history, challenges, and how medical technologies today, adopt cloud-based software and wearables into medical practice.
www.sentinelofsafety.com
Remote Healthcare and the Internet of Medical Things
Learn more about the internet of medical things or IoT, its history, challenges, and how medical technologies today, adopt cloud-based software and wearables into medical practice.
The Evolution of Remote Monitoring and the IoMT
The idea of the Internet of Things (or IoT) isn't exactly a new one. The term first cropped up in 1985when Peter T. Lewis was addressing the Congressional Black Caucus Foundation. He referred to the Internet of Things as "the integration of people, processes, and technology with connectable devices and sensors to enable remote monitoring, status, manipulation, and evaluation of trends of such devices."
The past decade has seen the development of a specialized medical IoT (also known as the Internet of Medical Things, or IoMT), which uses wearable sensors and integrated applications for healthcare monitoring needs. When paired with artificial intelligence, the IoMT can offer enhanced versions of standard medical devices--such as smart inhalers and insulin pumps--that collect patient data and, when necessary, adjust dosages.
According to this report from Research and Markets, the global market for IoMT devices is projected to reach USD 94.2 billion by 2026.
Remote Monitoring
One of the most important innovations in the healthcare industry has been the advances in wearable sensor technology. These devices are unobtrusive by design, which means patients can go about their lives without being tethered to monitoring equipment. These wearables allow caregivers to remotely monitor the condition of their patients, reducing the need for in-person care while offering peace of mind.IoMT Challenges
With the healthcare industry trending towards the IoMT, there are still a number of challenges that need to be overcome.- Integration. Getting all of the "things" in the Internet of Medical Things to communicate can be problematic. Although a lot devices still use their own proprietary communication protocol, many manufacturers have moved to a brand-agnostic integration that allows various brands to work together seamlessly.
- Connectivity. Wireless communication can be disrupted by a number of factors, from inclement weather to sparse WiFi coverage. Manufacturers have addressed this issue to some degree with redundant networks and robust buffering, ensuring the data gets through no matter how spotty the connection.
- Security. The wireless transmission of personal and healthcare data naturally raises serious concerns about security and privacy. Most manufacturers go to great lengths to protect their software, design protocols, and firmware from hacking or reverse engineering. Similarly, healthcare providers run tightly controlled inventories of the devices connected to their networks to prevent unauthorized devices from being deployed. An ideal remote monitoring solution will have comprehensive end-to-end security controls in place from day one of its product life cycle through its approval by regulatory agencies and its deployment for patient use.
The IoMT age is ripe with opportunities for remote healthcare, but general trust in cloud data and security is still evolving. The technology has come a long way and will continue to improve in the years ahead as investment and funding increase.
References
- Global IoT Medical Devices Markets, 2021-2026 - Rising Focus on Active Patient Engagement and Patient-Centric Care Delivery -- Research and Markets
thelittleshort
Top Bloke
Nothing we don’t already know, but still so great to read as an investor in BrainChip
www.linkedin.com
MACHINE LEARNING, EMBEDDED DEVICES
Sheena Patel
2 June 2022
Digital transformation as it relates to cloud computing has been in full force over the last couple of years but very few are prepared for the upcoming shift to edge computing. Truly innovative leaders in industrial, automotive, and consumer organizations have already begun to recognize the impact of edge computing — as seen in Gartner’s “Hype Cycle for Edge Computing” from August 2021, shown below.
Edge computing as a whole is quite broad.
While certain categories like edge servers, IoT gateways, and 5G are generally known and have been made a part of deployment initiatives like Factory 4.0 or other digital transformation focus areas, other subsets of “edge” like edge AI hardware or tinyML (tiny machine learning) are on the cusp of innovation.
Companies like Google, Amazon, and Apple are already putting machine learning algorithms into smaller, constrained hardware for smart home and consumer applications like wake words and glass break detection. Cell phone manufacturers have been doing this for years. In the next shift of edge computing, machine learning will go into real-time applications in industrial environments for applications such as quality control, predictive maintenance, and augmenting human-in-the loop operations.
As the number of connected devices in industrial environments begins to exponentially grow, organizations will struggle to keep up with large amounts of raw data that must be analyzed and leveraged to derive useful insights.
As Cardinal Peak says, more applications will require real-time decision making and the cloud will struggle to keep up due to its latency in providing back intelligence to the end user or operator.
Gartner goes so far as to say that more than 75% of enterprise data will be created and processed outside of the data center or cloud over the next 5 years.
The reality will likely be that most companies need to adopt and execute on a hybrid edge to cloud strategy, if they have not already. Some intelligence and compute-related tasks will make sense to keep in the cloud, especially big data related problems such as analyzing financial transactions or monitoring cybersecurity related activities.
Other operational challenges will require real-time insights, like developing audio-based AI algorithms to detect a piece of obstructed or damaged machinery, which can be used to shut the machine off.
But executing an edge to cloud strategy is multi-faceted and will need to account for the various emerging yet rapidly growing trends such as tinyML, edge machine learning, and edge AI hardware.
If business leaders focus only on checking a box, and are content with simply purchasing and deploying edge compute platforms like gateways or local server environments for processing data outside of the cloud, they will rapidly fall behind competition over the next few years.
Those leaders who recognize the criticality of a full edge to cloud strategy will be the leaders whose companies will have the most efficient manufacturing operations, the most innovative new products on the market, and the most secure edge-to-cloud IT infrastructure.
The leaders who dismiss edge as all hype, while failing to recognize the diversity of edge computing applications, such as edge data management, edge AI or tinyML, will be the ones left scratching their heads at where they went wrong.
#edgecomputing #edgetocloud #tinyml | Sheena Patel
Business leaders at industrial and automotive companies need to start thinking about a full edge computing strategy, including areas like edge machine learning and tinyML, if they want to stay one step ahead of the competition. #edgecomputing #edgetocloud #tinyml
Why a Complete Edge Strategy Will Help Business Leaders Win
MACHINE LEARNING, EMBEDDED DEVICES
Sheena Patel
2 June 2022
Digital transformation as it relates to cloud computing has been in full force over the last couple of years but very few are prepared for the upcoming shift to edge computing. Truly innovative leaders in industrial, automotive, and consumer organizations have already begun to recognize the impact of edge computing — as seen in Gartner’s “Hype Cycle for Edge Computing” from August 2021, shown below.
Edge computing as a whole is quite broad.
While certain categories like edge servers, IoT gateways, and 5G are generally known and have been made a part of deployment initiatives like Factory 4.0 or other digital transformation focus areas, other subsets of “edge” like edge AI hardware or tinyML (tiny machine learning) are on the cusp of innovation.
Companies like Google, Amazon, and Apple are already putting machine learning algorithms into smaller, constrained hardware for smart home and consumer applications like wake words and glass break detection. Cell phone manufacturers have been doing this for years. In the next shift of edge computing, machine learning will go into real-time applications in industrial environments for applications such as quality control, predictive maintenance, and augmenting human-in-the loop operations.
As the number of connected devices in industrial environments begins to exponentially grow, organizations will struggle to keep up with large amounts of raw data that must be analyzed and leveraged to derive useful insights.
As Cardinal Peak says, more applications will require real-time decision making and the cloud will struggle to keep up due to its latency in providing back intelligence to the end user or operator.
Gartner goes so far as to say that more than 75% of enterprise data will be created and processed outside of the data center or cloud over the next 5 years.
The reality will likely be that most companies need to adopt and execute on a hybrid edge to cloud strategy, if they have not already. Some intelligence and compute-related tasks will make sense to keep in the cloud, especially big data related problems such as analyzing financial transactions or monitoring cybersecurity related activities.
Other operational challenges will require real-time insights, like developing audio-based AI algorithms to detect a piece of obstructed or damaged machinery, which can be used to shut the machine off.
But executing an edge to cloud strategy is multi-faceted and will need to account for the various emerging yet rapidly growing trends such as tinyML, edge machine learning, and edge AI hardware.
If business leaders focus only on checking a box, and are content with simply purchasing and deploying edge compute platforms like gateways or local server environments for processing data outside of the cloud, they will rapidly fall behind competition over the next few years.
Those leaders who recognize the criticality of a full edge to cloud strategy will be the leaders whose companies will have the most efficient manufacturing operations, the most innovative new products on the market, and the most secure edge-to-cloud IT infrastructure.
The leaders who dismiss edge as all hype, while failing to recognize the diversity of edge computing applications, such as edge data management, edge AI or tinyML, will be the ones left scratching their heads at where they went wrong.
MDhere
Top 20
Seems Magik-eye is still alive and well, apologies if already posted but found this Japanese article about Magik-eye. 
Looks like "Shikino" "knows" a few things or two And just when i thought Magik-eye was in sleepy town, sneeky find
www.dreamnews.jp
Accelerating the development of camera modules targeting the growing 3D sensing market
Shikino High Tech Co., Ltd. (hereinafter, Shikino High Tech) is a part of MagikEye Inc. (Headquarters: Connecticut, USA, Magic Eye),
which possesses advanced technology for 3D sensing. On June 7, 2022, we announced that we
have acquired shares and signed an MOU for joint development of camera modules that utilize this technology . This alliance is the first step towards future collaboration between the two companies developing products and technologies , especially with regard to the commercialization of cameras for 3D sensing, which is growing rapidly in the sensing camera market, where demand has been increasing in recent years . After discussions between the two companies, we plan to conclude a joint development agreement for commercialization. Takeo Miyazawa, CEO of MagikEye Inc., said: "We have developed a unique 3D measurement algorithm: ILT (Invertible Light Technology) (registered trademark). Simply add an ultra-compact laser projector designed with this technology to an existing camera module to achieve up to 600fps. It can achieve higher speed and lower delay response within 2ms at the shortest. It does not require major changes or additional resources to the CPU or SoC. By advancing, we are confident that we will be able to market the 3D sensor products required by various businesses at the fastest speed. ” Shikino Hi-Tech has introduced Magic Eye technology to commercialize advanced and high-performance 3D cameras. Aim
Looks like "Shikino" "knows" a few things or two
And just when i thought Magik-eye was in sleepy town, sneeky find 3Dセンシングに先進的な技術を保有するMagikEye Incとの資本業務提携のお知らせ
Announcement of capital and business alliance with Magik Eye Inc, which owns advanced technology for 3D sensing
Accelerating the development of camera modules targeting the growing 3D sensing market
Shikino High Tech Co., Ltd. (hereinafter, Shikino High Tech) is a part of MagikEye Inc. (Headquarters: Connecticut, USA, Magic Eye),
which possesses advanced technology for 3D sensing. On June 7, 2022, we announced that we
have acquired shares and signed an MOU for joint development of camera modules that utilize this technology . This alliance is the first step towards future collaboration between the two companies developing products and technologies , especially with regard to the commercialization of cameras for 3D sensing, which is growing rapidly in the sensing camera market, where demand has been increasing in recent years . After discussions between the two companies, we plan to conclude a joint development agreement for commercialization. Takeo Miyazawa, CEO of MagikEye Inc., said: "We have developed a unique 3D measurement algorithm: ILT (Invertible Light Technology) (registered trademark). Simply add an ultra-compact laser projector designed with this technology to an existing camera module to achieve up to 600fps. It can achieve higher speed and lower delay response within 2ms at the shortest. It does not require major changes or additional resources to the CPU or SoC. By advancing, we are confident that we will be able to market the 3D sensor products required by various businesses at the fastest speed. ” Shikino Hi-Tech has introduced Magic Eye technology to commercialize advanced and high-performance 3D cameras. Aim
Nothing we don’t already know, but still so great to read as an investor in BrainChip
View attachment 10278
#edgecomputing #edgetocloud #tinyml | Sheena Patel
Business leaders at industrial and automotive companies need to start thinking about a full edge computing strategy, including areas like edge machine learning and tinyML, if they want to stay one step ahead of the competition. #edgecomputing #edgetocloud #tinyml
Why a Complete Edge Strategy Will Help Business Leaders Win
MACHINE LEARNING, EMBEDDED DEVICES
Sheena Patel
2 June 2022
Digital transformation as it relates to cloud computing has been in full force over the last couple of years but very few are prepared for the upcoming shift to edge computing. Truly innovative leaders in industrial, automotive, and consumer organizations have already begun to recognize the impact of edge computing — as seen in Gartner’s “Hype Cycle for Edge Computing” from August 2021, shown below.
Edge computing as a whole is quite broad.
While certain categories like edge servers, IoT gateways, and 5G are generally known and have been made a part of deployment initiatives like Factory 4.0 or other digital transformation focus areas, other subsets of “edge” like edge AI hardware or tinyML (tiny machine learning) are on the cusp of innovation.
Companies like Google, Amazon, and Apple are already putting machine learning algorithms into smaller, constrained hardware for smart home and consumer applications like wake words and glass break detection. Cell phone manufacturers have been doing this for years. In the next shift of edge computing, machine learning will go into real-time applications in industrial environments for applications such as quality control, predictive maintenance, and augmenting human-in-the loop operations.
As the number of connected devices in industrial environments begins to exponentially grow, organizations will struggle to keep up with large amounts of raw data that must be analyzed and leveraged to derive useful insights.
As Cardinal Peak says, more applications will require real-time decision making and the cloud will struggle to keep up due to its latency in providing back intelligence to the end user or operator.
Gartner goes so far as to say that more than 75% of enterprise data will be created and processed outside of the data center or cloud over the next 5 years.
The reality will likely be that most companies need to adopt and execute on a hybrid edge to cloud strategy, if they have not already. Some intelligence and compute-related tasks will make sense to keep in the cloud, especially big data related problems such as analyzing financial transactions or monitoring cybersecurity related activities.
Other operational challenges will require real-time insights, like developing audio-based AI algorithms to detect a piece of obstructed or damaged machinery, which can be used to shut the machine off.
But executing an edge to cloud strategy is multi-faceted and will need to account for the various emerging yet rapidly growing trends such as tinyML, edge machine learning, and edge AI hardware.
If business leaders focus only on checking a box, and are content with simply purchasing and deploying edge compute platforms like gateways or local server environments for processing data outside of the cloud, they will rapidly fall behind competition over the next few years.
Those leaders who recognize the criticality of a full edge to cloud strategy will be the leaders whose companies will have the most efficient manufacturing operations, the most innovative new products on the market, and the most secure edge-to-cloud IT infrastructure.
The leaders who dismiss edge as all hype, while failing to recognize the diversity of edge computing applications, such as edge data management, edge AI or tinyML, will be the ones left scratching their heads at where they went wrong.
I reckon the Slope of enlightenment will be a hockey stick.
Rise from the ashes
Regular
Brainchip dude likes this.
Rise from the ashes
Regular
I'd call that SpywearCan’t get much more ubiquitous than smart clothing
Smart Fabric and the Next Generation of Wearables - VigiLife
Smart fabric (a.k.a. intelligent textiles and e-textiles) look to be game-changers in the worker safety, health & wellness, and physical performance industries. Read on to learn more about smart fabric and its impact on wearable sensors.
How Will Electronic Textiles Impact the future of Wearable Sensors?
Over the couple of decades, we've witnessed the evolution of wearables from a gimmick straight out of science fiction into a practical technology embraced by the mainstream. From fitness to healthcare to worker safety, more and more people are turning to wearables to provide real-time physiological data. In fact, Cisco Systems recently predicted that the number of wearable devices connected to networks will likely top a billion (with a b) by the end of 2022.
The technology itself is constantly evolving as well. The Fitbit (introduced in 2009) paved the way for smart watch monitors and smart rings. But now there's a new wearable technology on the block--smart fabric. And it looks to be a game changer.
What Is Smart Fabric?
Smart fabrics are textiles that look and feel like standard fabrics but contain sensors and other tech components that give it the ability to sense and respond to environmental conditions. This technology is also known as intelligent textiles, electronic textiles, or e-textiles.
While the need for heat- and light-sensitive fabric was originally driven by the sportswear market, the technology is rapidly expanding to other sectors.
Worker Safety
Wearable devices with sensors are already being used to protect workers from heat, exhaustion, and injury. But with smart fabric, these sensors will become even more unobtrusive than the current generation of smart watches, heart rate monitors, and gas sensors.
Imagine an employee uniform that's capable of capturing relevant health and safety signals--location, movement, biological reads, environmental conditions--and relaying them to an inspector or spotter. Or gloves that measure real-time vibration exposure to help workers avoid HAVS (hand-arm vibration syndrome).
Health and Wellness
Smart textiles can also revolutionize the way providers monitor and care for patients. By integrating discrete biosensors and chemical sensors into clothing, physicians can get a more accurate view of a patient's health.
For example, getting an EKG reading from a wearable is currently problematic. Watches and other devices can measure EKG, but they require the user to actively touch it to activate the scan. For continuous EKG monitoring without user intervention, healthcare providers have to rely on adhesive patches.
A shirt or a pair of pants made from e-textiles could provide continuous, real-time biometrics that would, in turn, help physicians to provide a more accurate diagnosis and treatment options.
Physical Performance
Sports and fitness is a major driver of smart fabric technology as companies and trainers continue to look for ways to improve the performance of athletes. According to report from Mordor Intelligence, the market for smart fabrics in sports and fitness was valued at $680 million in 2020 and is expected to hit $2.85 billion by the end of 2026.
While current monitors can readily track real-time physiological, performance, and safety readings, e-textiles have the potential to provide data that's even more granular and specific. The ability to continuously monitor an athlete's posture and body movement could be vital to improving technique *and* avoiding future injuries.
The Future of Smart Fabric
Although widespread adoption of smart fabric is still years away, there have already been a number ofimpressive innovations, such as Wi-Fi/Bluetooth connectivity and amazing power efficiency. Plus, most smart fabric garments can be laundered like any normal clothing.
Here at Sentinel, we're really excited about the potential of this new technology and you can bet we'll be looking for ways to integrate it with our current line of products as it develops.
References
"Smart Fabric - An Overview" - ScienceDirect
"Global Smart Wearable Market - Market to Grow by 19.48% from 2021 - 2026" - Business Wire
"Smart Safety Wear" - Health & Safety International Magazine
"Smart Fabrics for Sports and Fitness Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022-2027)" -Mordor Intelligence
"'Smart Clothes' Can Conduct Bluetooth and Wi-Fi to Link All Your Tech at Once, and Can Boost Battery Life by 1,000" - Business Insider
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