I do maintain that CMOS on-chip motion is useful because adding a PIR sensor is prohibitive for some form factors and more importantly has a lower effective range. What I find even more interesting, from a power usage standpoint, is this recent research on Adaptive Video Subsampling for Energy-Efficient Object Detection[0]. This buys some space on the energy budget for running ML on the device. Although image sensor reading is energy intensive compared to read-write and processor ops by 3 orders of magnitude, as outlined in the second slide of [0] we can see that LTE comms are a further 3-5 orders of magnitude more expensive than image sensor reads. Topically, here is some research on real-time wake from ultra-low power sleep (~10nW) and lowered idle SRAM usage [1] as well as the proposal for no power IR sensing [2].
[0] https://www.tinyml.org/summit/posters/Jayasuriya,%20tinyML%2...
[1] https://ieeexplore.ieee.org/document/9063136
[2] https://eri-summit.darpa.mil/docs/ERIPoster_Applications_N-Z...
>Also, the growth in C++ is probably in the new standards,
This, especially since growth here means growth in queries.
Agreed! There are some novel remarks on that in the link under "[1]" in my reply to the parent comment.
Or see the following digest if paywalled: https://community.arm.com/developer/research/b/articles/post...