Neuromorphic Computing for Smart Agriculture

Agriculture, Год журнала: 2024, Номер 14(11), С. 1977 - 1977

Опубликована: Ноя. 4, 2024

Neuromorphic computing has received more and attention recently since it can process information interact with the world like human brain. Agriculture is a complex system that includes many processes of planting, breeding, harvesting, processing, storage, logistics, consumption. Smart devices in association artificial intelligence (AI) robots Internet Things (IoT) systems have been used also need to be improved accommodate growth computing. great potential promote development smart agriculture. The aim this paper describe current principles neuromorphic technology, explore examples applications agriculture, consider future route synapses, neurons, neural networks (ANNs). A expected improve agricultural production efficiency ensure food quality safety for nutrition health agriculture future.

Язык: Английский

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Enhancing Assistive Technologies With Neuromorphic Computing

Advances in computational intelligence and robotics book series, Год журнала: 2024, Номер unknown, С. 207 - 232

Опубликована: Окт. 4, 2024

The development of intelligent neuroprosthetics, which promise to augment human brain function is vital for augmentative assistive technologies. Neuromorphic sensors and processors are particularly adept at mimicking the brain's efficient sensory processing, offering devices an advanced capability perceive interpret complex environmental stimuli. application these technologies in computer interfaces suggests a future where transformative advancements not only possible but imminent, facilitating novel methods human-computer interaction providing insights into intricate workings through AI machine learning techniques. This paper explores integration neuromorphic with brain-computer (BCIs), highlighting potential enhance revolutionize communication healthcare. However, realization computing's full within BCIs contingent upon overcoming significant technological ethical challenges.

Язык: Английский

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High-performance metal oxide TFTs for flexible displays: materials, fabrication, architecture, and applications

Soft Science, Год журнала: 2025, Номер 5(1)

Опубликована: Янв. 10, 2025

Flexible display technology is actively explored as a cornerstone of the next generation wearables and soft electronics, set to revolutionize devices with its potential for lightweight, thin, mechanically flexible features. thin-film transistors (TFTs) utilizing promising materials such amorphous silicon (a-Si), low-temperature polysilicon (LTPS), metal oxides (MOs), organic semiconductors are essential enable platforms. Among these, MO stand out displays due their high carrier mobility, low processing temperature requirements, excellent electrical uniformity, transparency visible light, cost-effectiveness. Furthermore, maturity TFT in existing industry compatibility complementary-metal-oxide-semiconductor (CMOS) processes driving active research toward integrated circuits wearable electronics beyond applications. Specifically, achieving both mechanical flexibility performance TFTs crucial implementing complex microprocessors backplanes ultra-high resolution augmented reality (AR)/virtual (VR) displays. Therefore, this review provides recent advances high-mobility TFTs, focusing on materials, fabrication processes, device architecture engineering methods substrates, well strategies reduce impact stress TFTs. Next, TFT-based circuit applications next-generation stretchable introduced discussed. Finally, concludes an outlook achievements prospects development technologies.

Язык: Английский

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Neuromorphic Hardware for Artificial Sensory Systems: A Review

Journal of Electronic Materials, Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Abstract Senses are crucial for an organism’s survival, and there have been numerous efforts to artificially replicate sensory perception elicit desired responses specific stimuli. Recent research is increasingly focused on developing artificial nervous systems based the unsupervised learning capabilities of neural networks (ANNs) using unstructured data. However, future ANNs, which require precise sensing in complex environments, must be capable processing a large number signals real time, ideally from continuous domains. This need massive data driving evolution hardware systems, leading development devices specifically designed (ASSs) at level. To address this challenge, sensor not only detect target substances but also enable computational functions by utilizing their inherent material properties. Research neuromorphic sensors advancing towards integration with next-generation effectively addressing scenarios we aim identify. review offers perspectives human-like computing these challenges. It examines progress implementing five representative senses device level, explores methods integrating them into ASS, provides comprehensive overview potential applications. In particular, emphasize approaches cognitively utilize discussed as neurons synapses, enabling inputs. We offer nerve future.

Язык: Английский

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Implementation of Multiply Accumulate Operation and Convolutional Neural Network Based on Ferroelectric Tunnel Junction Memristors

ACS Applied Materials & Interfaces, Год журнала: 2025, Номер unknown

Опубликована: Март 31, 2025

In the era of big data, traditional Von Neumann computers suffer from inefficiencies in terms energy consumption and speed associated with data transfer between storage processing. In-memory computing using ferroelectric tunnel junction (FTJ) memristors offers a potential solution to this challenge. Here, Hf0.5Zr0.5O2-based FTJs on silicon substrate are fabricated, which demonstrates 32 conductance states (5-bit), low cycle-to-cycle variation (1.6%) highly linear (nonlinearity <1) manipulation. Based an FTJ array multiple devices, custom-designed board field programmable gate is utilized perform accurate multiply accumulate operations for image processing as various convolution operators. Notably, devices convolutional layer, neural network achieves high accuracy 92.5% handwritten digit recognition, exhibits orders magnitude better efficiency compared CPU GPU implementations. These findings highlight promising realizing in-memory at hardware level.

Язык: Английский

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Rational Design and Application of Breath Sensors for Healthcare Monitoring

ACS Sensors, Год журнала: 2024, Номер unknown

Опубликована: Дек. 31, 2024

Biomarkers contained in human exhaled breath are closely related to certain diseases. As a noninvasive, portable, and efficient health diagnosis method, the sensor has received considerable attention recent years for early disease screening prevention due its user-friendly easy-accessible features. Although some key challenges have been addressed, capability precisely monitor specific biomarkers of interest physiological relevance metrics is still be ascertained. In this context, we analyzed rational design advance sensors healthcare monitoring. This review begins with an introduction their sensing technologies, such as chemoresistive, humidity-sensitive, electrochemical, colorimetric principles. Then, systematic overview emerging applications screening, drunk driving inspection, apnea monitoring, condensate analysis demonstrated. Finally, discuss opportunities noninvasive With ongoing research efforts, continuous breakthrough attractive foreseeable future.

Язык: Английский

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Room-temperature gas sensors based on low-dimensional nanomaterials

Journal of Materials Chemistry C, Год журнала: 2024, Номер 12(46), С. 18609 - 18627

Опубликована: Янв. 1, 2024

We provide a roadmap for room-temperature operable low-dimensional semiconductor-type gas sensors, along with recent trends in their application fields comprehensive overview.

Язык: Английский

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