A Rambus VLSI Symposium paper on lensless smart sensor (LSS) technology has been cited in Solid State Circuits Magazine.
“In an invited paper, Rambus presented an overview of lensless smart sensors that rely on phase-modulated diffraction gratings above a conventional imaging array. Compared to a lens, this More-than-Moore diffraction grating, seen in Figure 6, can be designed for wide wavelength bands and has a lower profile for thinner sensors,” the publication stated.
“Results were presented in the context of point range finding, eye tracking and occupancy detection applications. While the raw images appear incomprehensible to the human eye, image reconstruction is possible, but the end application information can also be derived directly from the raw data itself, using the known point-spread function.”
As we’ve previously discussed on Rambus Press, lensless smart sensors enable a new approach to optical sensing that delivers on package, power and price by replacing traditional lenses with tiny diffractive optics. In addition, LSS operates in visible and thermal wavelengths, offering significant size and cost advantages versus standard thermal imaging modules. With the addition of these new capabilities, LSS can replace traditional thermal lenses with optical gratings that are significantly less expensive, enabling adoption of LSS thermal and visible sensing into a broad range of IoT applications including automotive, virtual and augmented reality and smart home use cases.
In terms of the latter category, smart buildings and homes are steadily moving beyond traditional structures and evolving into complex, connected systems designed to optimize efficiency, productivity, comfort and safety for their occupants. With its tiny form factor, low power, low cost and wide field of view, LSS is an ideal sensing solution for building automation systems and can be easily integrated into smart LED bulbs, commercial light fixtures, or an unobtrusive discrete sensor pack to feed.
Moreover, LSS is capable of detecting and interpreting activity within a space at a size and performance previously unattainable with existing building sensing technologies, all without compromising privacy. The data about the general activity and number of occupants in the area can be used to intelligently trigger environmental systems, monitor traffic flows and optimize area usage, reducing the environmental impact, along with operating and maintenance costs.