返回
In-Sensor Computing: Materials, Devices, and Integration Technologies
DOI:10.1002/adma.202203830.png)
摘要
En 中文
The number of sensor nodes in the Internet of Things is growing rapidly, leading to a large volume of data generated at sensory terminals. Frequent data transfer between the sensors and computing units causes severe limitations on the system performance in terms of energy efficiency, speed, and security. To efficiently process a substantial amount of sensory data, a novel computation paradigm that can integrate computing functions into sensor networks should be developed. The in-sensor computing paradigm reduces data transfer and also decreases the high computing complexity by processing data locally. Here, the hardware implementation of the in-sensor computing paradigm at the device and array levels is discussed. The physical mechanisms that lead to unique sensory response characteristics and their corresponding computing functions are illustrated. In particular, bioinspired device characteristics enable the implementation of the functionalities of neuromorphic computation. The integration technology is also discussed and the perspective on the future development of in-sensor computing is provided.
Keyword:
bioinspired devices
in-sensor computing
near-sensor computing
optoelectronic devices
vision sensors
期刊
IF:
26.8
论文数:
3.5W
被引数:
46.0W
机构
引用论文
Comparison of centrifugation, dissolved air flotation and drum filtration techniques for harvesting sewage-grown algae
Biomass
IF0
The effects of training and overeducation on career mobility in a segmented labour market在细分的劳动力市场中,培训和过度教育对职业流动的影响
An organic transistor with light intensity-dependent active photoadaptation具有依赖于光强度的主动光适应的有机晶体管
NATURE ELECTRONICS
IF40.9
Mimicking Neuroplasticity in a Hybrid Biopolymer Transistor by Dual Modes Modulation通过双模式调制模拟混合生物聚合物晶体管中的神经可塑性
Fully photon modulated heterostructure for neuromorphic computing用于神经形态计算的全光子调制异质结构
NANO ENERGY
IF17.1

