The evolution of artificial intelligence of things (AIoT)
drastically
facilitates the development of a smart city via comprehensive
perception and seamless communication. As a foundation, various AIoT
nodes are experiencing low integration and poor sustainability issues.
Herein, a cubic-designed intelligent piezoelectric AIoT node iCUPE
is presented, which integrates a high-performance energy harvesting
and self-powered sensing module via a micromachined
lead zirconate titanate (PZT) thick-film-based high-frequency (HF)-piezoelectric
generator (PEG) and poly(vinylidene fluoride-co-trifluoroethylene)
(P(VDF-TrFE)) nanofiber thin-film-based low-frequency (LF)-PEGs, respectively.
The LF-PEG and HF-PEG with specific frequency up-conversion (FUC)
mechanism ensures continuous power supply over a wide range of 10–46
Hz, with a record high power density of 17 mW/cm3 at 1
g acceleration. The cubic design allows for orthogonal placement of
the three FUC-PEGs to ensure a wide range of response to vibrational
energy sources from different directions. The self-powered triaxial
piezoelectric sensor (TPS) combined with machine learning (ML) assisted
three orthogonal piezoelectric sensing units by using three LF-PEGs
to achieve high-precision multifunctional vibration recognition with
resolutions of 0.01 g, 0.01 Hz, and 2° for acceleration, frequency,
and tilting angle, respectively, providing a high recognition accuracy
of 98%–100%. This work proves the feasibility of developing
a ML-based intelligent sensor for accelerometer and gyroscope functions
at resonant frequencies. The proposed sustainable iCUPE is highly
scalable to explore multifunctional sensing and energy harvesting
capabilities under diverse environments, which is essential for AIoT
implementation.