A Sustainable Future with Eco-Friendly Wirelessly Powered IoT Sensors

 

 

About Topic In Short:
	Who: King Abdullah University of Science and Technology (KAUST) | KAUST-led international team including Kalaivanan Loganathan and Thomas Anthopoulos.
	What: Wirelessly powered electronics using alternative semiconductor materials for a more sustainable Internet of Things (IoT).
	How: The IoT's growth demands energy-efficient and environmentally friendly power sources. The team explored large-area electronics with energy harvesters like photovoltaic cells and RF energy harvesters, eliminating battery reliance.

 

Introduction

The realm of the Internet of Things (IoT) is evolving rapidly, promising a profound impact on daily life and diverse industries. However, the surge in IoT devices and their reliance on battery technology pose environmental challenges related to waste and depletion of resources. In response, a pioneering international team of researchers led by KAUST explores an innovative solution to develop eco-friendly, wirelessly powered IoT sensors, with a vision for a more sustainable future.

 

The Expanding Influence of IoT

The Internet of Things constitutes an interconnected network of smart objects serving various purposes, from home security systems to self-driving cars and industrial machinery. As the IoT continues to grow, projections indicate that it will encompass trillions of devices in the coming decade, demanding energy-efficient and sustainable power solutions to drive these devices.

 

Challenges with Traditional Battery-Powered Sensors

The current approach to powering IoT devices heavily relies on battery technology, presenting several concerns. The regular replacement of batteries incurs significant costs and contributes to environmental harm through electronic waste generation. Additionally, the soaring demand for battery materials like lithium may outpace global production capacities, further exacerbating resource scarcity.

 

Wireless IoT Sensors: A Greener Paradigm

The KAUST research team introduces an alternative approach to tackle these challenges: wirelessly powered IoT sensors. Leveraging energy harvesters like photovoltaic cells and radio-frequency (RF) energy harvesters, these sensors draw energy from the environment, eliminating the need for batteries and reducing electronic waste. Large-area electronics play a pivotal role in enabling this technology, offering eco-friendly solutions printable on flexible, biodegradable substrates like paper.

 

Pioneering Endeavors at KAUST Solar Center

KAUST alumnus Kalaivanan Loganathan conducted groundbreaking research in Thomas Anthopoulos' lab at the KAUST Solar Center. Loganathan's study focused on large-area nanogap patterning using adhesion lithography, showcasing the potential of nanogap devices across various applications. Presently, Loganathan serves as an R&D Project Engineer at High NA Lab in Belgium, contributing to the advancement of environmentally friendly technologies.

 

Evaluating Large-Area Electronic Technologies

KAUST alumni Kalaivanan Loganathan, alongside Professor Thomas Anthopoulos and researchers from the KAUST Solar Center, assessed the feasibility of diverse large-area electronic technologies to develop eco-friendly, wirelessly powered IoT sensors. Notably, significant strides in solution-based processing facilitated easier printing of devices and circuits on flexible, large-area substrates, offering a more sustainable alternative to conventional silicon-based technologies.

 

The Role of RF Electronic Components

The KAUST team's research has led to the creation of RF electronic components, encompassing metal-oxide and organic polymer-based semiconductor devices known as Schottky diodes. These components play a pivotal role in wireless energy harvesters, significantly influencing the performance and cost of the sensor nodes.

 

Envisioning a Sustainable Tomorrow

The team's endeavors encompass scalable methodologies to manufacture RF diodes capable of harvesting energy within the 5G/6G frequency range, providing essential building blocks to power billions of sensor nodes sustainably. At present, the team explores the seamless integration of these low-power devices with antennas and sensors, presenting their true potential.

 

Thus Speak Authors/Experts

According to the visionary researchers involved in this groundbreaking study, wirelessly powered large-area electronics pave the way for a sustainable Internet of Things. This proposed technology not only curtails electronic waste and reduces the environmental impact of battery production but also offers scalable and cost-effective solutions to power the ever-expanding world of interconnected IoT devices.

 

Conclusion

Embracing eco-friendly, wirelessly powered sensors holds the key to the future of IoT, extracting energy from the environment and reducing reliance on conventional batteries, thus mitigating electronic waste. The KAUST-led international research team's trailblazing efforts forge a path towards a sustainable and eco-conscious Internet of Things, contributing to a brighter and greener future.

 

Image Gallery

Wirelessly powered electronics developed by KAUST researchers could help to make internet of things technology more environmentally friendly. Graphic: 2022 KAUST / Heno Hwang

While in Thomas Anthopoulos' lab in the KAUST Solar Center, KAUST alumnus Kalaivanan Loganathan studied large-area nanogap patterning based on adhesion lithography and the use of nanogap devices for various applications. Loganathan now works as an R&D Project Engineer at High NA Lab in Belgium.  Photo: KAUST

All Images Credit: from References/Resources sites [Internet]

 

Hashtag/Keyword/Labels List:

#GreenerIoT #WirelesslyPoweredElectronics #EcofriendlySensors #KAUSTResearch #SustainableFuture #EnergyHarvesters

 

References/Resources List

1.       https://www.discountmags.com/magazine/electronics-for-you-february-2023-digital-m/in-this-issue/hiRRo1jyO1675419030104

2.       https://www.sustainabilitymenews.com/technology/a-greener-internet-of-things-with-no-wires-attached

3.       https://www.industrytap.com/researchers-discover-new-approach-to-eco-friendly-iot/65205

4.       https://www.theengineer.co.uk/content/news/iot-could-go-green-with-large-area-electronic-technologies

5.       https://www.kaust.edu.sa/en/news/a-greener-internet-of-things-with-no-wires-attached

 

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Discovering the Potential of Wireless Earbuds as Affordable Hearing Aids

 

 

About Topic In Short:
	Who: Institute Name and Authors: Cell Press, - Heng-Yu Haley Lin, - Hoi-Shan Lai, - Chii-Yuan Huang, - Chih-Hao Chen, - Shang-Liang Wu, - Yuan-Chia Chu, - Yu-Fu Chen, - Ying-Hui Lai, - Yen-Fu Cheng.
	What: Some commercial earbuds, specifically Apple's AirPods Pro, can perform comparably to traditional hearing aids in certain scenarios, offering a potential cost-effective solution for individuals with hearing loss.
	How: The researchers compared AirPods 2 and AirPods Pro with premium and basic hearing aids. They tested these devices on 21 participants with mild to moderate hearing loss. The participants were asked to repeat a sentence while wearing the devices, and the results were analyzed.

  

Introduction:

An extraordinary study, published on November 15, 2022, in the esteemed journal iScience, conducted by researchers from Cell Press, has unveiled the remarkable capability of certain commercial earbuds to match the performance of traditional hearing aids. This groundbreaking revelation holds promise in addressing a significant hurdle faced by individuals with hearing loss, offering the potential for more affordable and easily accessible sound amplification devices. The research delves into the viability of employing widely available wireless earphones, notably Apple's AirPods, as a cost-effective alternative to conventional hearing aids.

 

Background and Predicament:

The implications of hearing loss on an individual's overall health and well-being are vast and profound. Nevertheless, the expense associated with traditional hearing aids, coupled with the need for multiple visits to medical professionals for fine-tuning, creates substantial barriers for those seeking assistance. Astonishingly, nearly 75% of individuals with hearing loss in the United States forgo the use of hearing aids, largely due to the high cost and the social stigma surrounding them.

 

Approach and Objective of the Researchers:

In response to the challenges faced by individuals with hearing loss, Yen-fu Cheng, an otolaryngologist at Taipei Veterans General Hospital, along with his dedicated team, embarked on an exploration of alternative and more accessible solutions. Their focus honed in on Apple's "Live Listen" feature, introduced in 2016, which empowers users to amplify sounds through their wireless earphones and iPhones. The researchers sought to ascertain whether AirPods, equipped with the "Live Listen" feature, could effectively supplant traditional hearing aids.

 

Methodology and Key Findings of the Research:

The research team conducted a comparative analysis between two AirPods models, AirPods 2 and AirPods Pro (the latter boasting noise-canceling capabilities), and both premium and basic hearing aids. Premium hearing aids were priced at $10,000, while basic ones cost $1,500. Remarkably, the AirPods models proved significantly more cost-effective, with AirPods 2 priced at $129 and AirPods Pro at $249. Notably, AirPods Pro adhered to four out of five technology standards for hearing aids, indicating their potential candidacy for sound amplification.

 

The researchers enlisted 21 participants with mild to moderate hearing loss and asked them to repeat a brief sentence while wearing the devices, subsequently analyzing the results. In quiet settings, AirPods Pro exhibited similar efficacy to basic hearing aids, slightly trailing premium hearing aids. Despite ranking the lowest among the four devices, AirPods 2 still exhibited an improvement in hearing compared to no hearing aids.

 

However, in noisy environments, AirPods Pro displayed comparable performance to premium hearing aids when the noise emanated from the side of the participant. Regrettably, both AirPods models struggled to enhance hearing when noise originated from the front.

 

Potential Reasons and Future Implications:

The disparity in performance between the two scenarios could potentially be attributed to soundwave trajectories and the advanced signal processing algorithms inherent in premium hearing aids. This revelation paves the way for future advancements in hearing aid and personal sound amplification product design, emphasizing heightened sensitivity to specific directions.

 

The researchers' findings carry substantial implications for the rapidly growing wireless earphone market worldwide. This research may inspire companies to explore the concept of crafting earbuds with sound amplification capabilities to cater to the needs of individuals with hearing loss.

 

Expert Insights:

Ying-Hui Lai, a co-author of the study and a bioengineer at National Yang Ming Chiao Tung University in Taipei, fervently emphasized the profound impact of their findings on the development of more sensitive hearing aids and personal sound amplification products. The team's work underscores the viability of wireless earbuds as hearing aids, signifying a momentous stride in making sound amplification devices more accessible and cost-effective.

 

Conclusion:

In conclusion, the study establishes that select commercial earbuds, particularly AirPods Pro, possess comparable potential to traditional hearing aids in specific scenarios. This discovery heralds the advent of more economical and widely accessible sound amplification options for individuals with hearing loss. While wireless earbuds do not serve as perfect substitutes for professional hearing aids, they undeniably offer a promising starting point to enhance the quality of life for countless individuals currently lacking access to such devices. The study stands as a collaborative effort supported by Veterans General Hospitals and the University System of Taiwan Joint Research Program, along with the Ministry of Science and Technology.

 

Image Gallery

All Images Credit: from References/Resources sites [Internet]

 

Hashtag/Keyword/Labels list:

#WirelessEarphones #HearingAids #SoundAmplification #HearingLoss #AffordableDevices #AirPodsPro #Research #iScience #CellPress

 

References/Resources:

1.       https://www.pressreader.com/india/electronics-for-you-express/20230203/282815015392808

2.       https://www.sciencedaily.com/releases/2022/11/221115113924.htm

3.       https://www.healthline.com/health-news/how-apple-airpods-and-other-wireless-earbuds-can-be-used-as-hearing-aids#What-are-PSAPs?

 

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Discovering New Avenues: Ultrasonic Waves as the Key to Object Steering

 

 

About Topic In Short:
	Who: University of Minnesota Twin Cities, Ognjen Ilic (senior author), Matthew Stein (first author).
	What: Researchers discovered a novel method using ultrasound waves for contactless manipulation, enabling movement of objects without the need for a built-in power source, with applications in manufacturing and robotics.
	How: By employing metamaterial physics and placing a metamaterial pattern on an object's surface, researchers steer it in a desired direction using sound waves, without physical contact.

  

Introduction:

In the realm of contactless manipulation, a groundbreaking revelation emerges from the University of Minnesota Twin Cities researchers who harness the power of ultrasound waves to propel objects. This newfound technique unlocks vast possibilities for industries like manufacturing and robotics, enabling devices to move autonomously without the constraints of a built-in power source.

 

Background:

The research, unveiled in Nature Communications, unveils the art of object manipulation using the artistry of light and sound waves—a phenomenon known before. Yet, in previous cases, the confines of sound and light wavelengths limited the objects to diminutive scales, mere millimeters to nanometers in magnitude. Surmounting this challenge, the research team delves into the complexities of metamaterial physics, transcending boundaries to manipulate grander entities.

 

Metamaterials and Contactless Manipulation:

Metamaterials, ingeniously designed materials engrossed in wave interactions, emerge as the heart of this study. Implementing a metamaterial pattern upon an object's surface, researchers steer it with sound waves, all devoid of any physical contact.

 

Key Discoveries:

The study's esteemed author, Ognjen Ilic, a professor in the College of Science and Engineering, stresses the distinctiveness of their research, wielding prowess to manipulate and ensnare more substantial entities through the marvel of "metasurfaces." By rendering an object's surface a metamaterial sanctuary, they achieve wondrous feats in object manipulation.

 

Contactless Actuation and Future Prospects:

The research pioneers a novel approach to contactless actuation, furnishing unmatched advantages over existing methods. Its implications reverberate throughout industries demanding precision and hands-free dexterity. The realm of possibilities evokes echoes of science fiction sagas, wherein objects advance and gravitate towards predetermined sources, akin to the wondrous tractor-beam technologies heralded in Star Trek's narratives.

 

Future Research and Implications:

Though the study primarily demonstrates the concept, a vibrant trajectory lies ahead as researchers venture into the realm of higher wave frequencies and diverse materials and object scales. The unfurling research promises a future wherein contactless manipulation becomes an inseparable constituent of numerous industries.

 

Insights from the Experts:

Ognjen Ilic, the study's venerable senior author, reverberates the groundbreaking essence of their work, illuminating the potency of sound and light in manipulating more substantial entities—a revelation that engenders novel mechanisms for contactless operations. Matthew Stein, the paper's first author and an erudite graduate student in the College of Science and Engineering, emphasizes the burgeoning domain of contactless manipulation in the realm of optics and electromagnetism. Their groundbreaking approach transcends conventional methods, unveiling an auspicious pathway for deeper exploration.

 

Conclusion:

The research illuminates a captivating horizon, with ultrasound waves as the conduit for contactless object manipulation, catapulting the University of Minnesota Twin Cities researchers into the vanguard of scientific breakthroughs. Embracing the complexities of metamaterial physics, they demonstrate the astonishing ability to maneuver objects of unprecedented scale. In the churning cauldron of innovation, the technique's potential cascades across industries, engendering a future replete with possibilities for contactless manipulation.

 

Image Gallery

College of Science and Engineering students with metamaterial object. Credit: University of Minnesota

By placing a metamaterial pattern on the surface of an object, the University of Minnesota researchers were able to use sound to steer it in a certain direction without physically touching it. (CREDIT: Olivia Hultgren)

All Images Credit: from References/Resources sites [Internet]

Video credit: Laboratory for Nano Optics and Mechanics, University of Minnesota

Hashtag/Keyword/Labels:

#UltrasoundWaves #ContactlessManipulation #MetamaterialPhysics #ScienceAndEngineering #Robotics #Manufacturing #Research #UniversityOfMinnesota

 

References/Resources:

1. University of Minnesota News Release: "Researchers use ultrasound waves to move objects hands-free" (Link: https://twin-cities.umn.edu/news-events/researchers-use-ultrasound-waves-move-objects-hands-free)

2. Nature Communications Journal: "Study on contactless manipulation using metamaterial physics" (Link: https://www.nature.com/ncomms)

 

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An Innovative System for Enhanced Deep Learning: Utilizing Memristor Crossbars for Efficient and Sustainable AI

 

 

About Topic In Short:
	Who: Texas A&M University, Rain Neuromorphics, and Sandia National Laboratories. Authors: Suhas Kumar, Suin Yi, Jack Kendall, Stanley Williams.
	What: A memristor crossbar-based learning system for scalable and energy-efficient AI.
	How: The system reduces the carbon footprint and costs associated with AI training by using new hardware (memristor crossbars) and innovative algorithms, leading to power-efficient AI training.

 

Introduction:

This fascinating article delves into a groundbreaking research study conducted by experts from Texas A&M University, Rain Neuromorphics, and Sandia National Laboratories. The study unveils a novel system designed to optimize the training of deep learning models, addressing the challenges posed by energy-intensive and costly conventional AI training practices. This cutting-edge approach synergizes advanced hardware, memristor crossbars, with brain-like efficient algorithms, leading to remarkable advancements in AI training.

 

Background:

Deep-learning models have proven exceptionally effective in real-world tasks, encompassing data analysis and predictive capabilities. Nevertheless, training these models in physical data centers demands substantial time and energy before they can be effectively deployed in devices like cell phones. The costs associated with AI model training in large data centers present considerable hurdles for scalability and long-term viability.

 

The New System:

To transcend the limitations of conventional AI training techniques, the researchers have devised a unique system that capitalizes on the power of memristor crossbar hardware and novel training algorithms. Memristor crossbars, a highly parallel alternative to GPUs, enable simultaneous execution of multiple operations, significantly improving efficiency. The crux of this system's success lies in the development of an innovative co-optimized learning algorithm, inspired by the brain's intricate neuronal activity, fostering error tolerance and the ability to learn from sparse and noisy information.

 

Implementation and Benefits:

Leveraging memristor crossbars and the pioneering learning algorithm, the research team achieved substantial enhancements in energy efficiency and scalability. Demonstrating remarkable potential for complex tasks, the system accurately reconstructed Braille representations of renowned computer scientists from heavily distorted inputs.

 

Thus Speak Authors/Experts:

Suhas Kumar, the esteemed senior author of the study, highlights the energy-intensive nature of AI training and the imperative to foster sustainable and cost-effective large-scale implementation. The amalgamation of advanced hardware and algorithms in this system unlocks highly power-efficient AI training.

 

Suin Yi, the distinguished lead author of the study, accentuates the significance of memristor crossbars, which seamlessly embed synaptic weight where computing takes place, minimizing data movement. This compatibility with analog hardware successfully surmounts the limitations of traditional backpropagation algorithms, ultimately facilitating more efficient AI training.

 

Jack Kendall, another esteemed author of the paper, passionately discusses the far-reaching implications of this approach. Enabling deployment of AI models even on smaller devices such as cellphones and smartwatches, this system allows on-the-fly learning, adapting to dynamic environments without compromising user data security by sending it to the cloud for training.

 

Conclusion:

The pioneering research introduces a memristor crossbar-based learning system that not only conquers the challenges of energy-intensive and costly AI training but also presents an exciting step towards a sustainable and accessible AI future. From untethered devices to reducing data center carbon footprints, the potential of this innovative approach promises to revolutionize AI implementation.

 

Image Gallery

A chip consisting of memristor crossbars was trained using a local on-chip learning algorithm. The team demonstrated that their approach could accurately reconstruct Braille representations of nine famous computer scientists from highly distorted inputs. Credit: Yi et al.

ll Images Credit: from References/Resources sites [Internet]

 

Hashtag/Keyword/Labels:

#AItraining #memristorcrossbar #energyefficientAI #scalableAI #deeplearning #hardwarealgorithm #edgeAI

 

References/Resources:

1.       https://www.pressreader.com/india/electronics-for-you-express/20230203/282789245589032

2.       https://www.electronicsforu.com/news/whats-new/memristor-crossbar-based-deep-learning-for-efficient-ai

3.       https://techxplore.com/news/2022-12-memristor-crossbar-based-scalable-energy-efficient-ai.html

 

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