TinyML for ultra-low power AI and large scale IoT deployments: A systematic review

N Schizas, A Karras, C Karras, S Sioutas - Future Internet, 2022 - mdpi.com
The rapid emergence of low-power embedded devices and modern machine learning (ML)
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …

Wireless and battery-free technologies for neuroengineering

SM Won, L Cai, P Gutruf, JA Rogers - Nature Biomedical Engineering, 2023 - nature.com
Tethered and battery-powered devices that interface with neural tissues can restrict natural
motions and prevent social interactions in animal models, thereby limiting the utility of these …

Tensorflow lite micro: Embedded machine learning for tinyml systems

R David, J Duke, A Jain… - Proceedings of …, 2021 - proceedings.mlsys.org
Abstract We introduce TensorFlow (TF) Micro, an open-source machine learning inference
framework for running deep-learning models on embedded systems. TF Micro tackles the …

Electronically integrated, mass-manufactured, microscopic robots

MZ Miskin, AJ Cortese, K Dorsey, EP Esposito… - Nature, 2020 - nature.com
Fifty years of Moore's law scaling in microelectronics have brought remarkable opportunities
for the rapidly evolving field of microscopic robotics,,,–. Electronic, magnetic and optical …

Colloidal robotics

AT Liu, M Hempel, JF Yang, AM Brooks, A Pervan… - Nature materials, 2023 - nature.com
Robots have components that work together to accomplish a task. Colloids are particles,
usually less than 100 µm, that are small enough that they do not settle out of solution …

High energy density picoliter-scale zinc-air microbatteries for colloidal robotics

G Zhang, S Yang, JF Yang, D Gonzalez-Medrano… - Science Robotics, 2024 - science.org
The recent interest in microscopic autonomous systems, including microrobots, colloidal
state machines, and smart dust, has created a need for microscale energy storage and …

On-chip integration of a covalent organic framework-based catalyst into a miniaturized Zn–air battery with high energy density

H Zhang, Z Qu, H Tang, X Wang, R Koehler… - ACS Energy …, 2021 - ACS Publications
Advances in microelectronics have led to the development of on-chip intelligent
microsystems that can digitalize the physical world, offering functions of sensing, data …

[HTML][HTML] Mesoporous silica-based materials for electronics-oriented applications

Ł Laskowski, M Laskowska, N Vila, M Schabikowski… - Molecules, 2019 - mdpi.com
Electronics, and nanoelectronics in particular, represent one of the most promising branches
of technology. The search for novel and more efficient materials seems to be natural here …

A 0.065-mm3 Monolithically-Integrated Ultrasonic Wireless Sensing Mote for Real-Time Physiological Temperature Monitoring

C Shi, T Costa, J Elloian, Y Zhang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Accurate monitoring of physiological temperature is important for many biomedical
applications, including monitoring of core body temperature, detecting tissue pathologies …

26.9 A 0.19×0.17mm2 Wireless Neural Recording IC for Motor Prediction with Near-Infrared-Based Power and Data Telemetry

J Lim, E Moon, M Barrow, SR Nason… - … Solid-State Circuits …, 2020 - ieeexplore.ieee.org
Brain machine interfaces using neural recording systems 1–4 can enable motor prediction 5–
6 for accurate arm and hand control in paralyzed or severely injured individuals. However …