We present a design of a contact lens display, which features an array of collimated light-emitting diodes and a contact lens, for the augmented reality. By building the infrastructure directly on top of the eye, eye is allowed to move or rotate freely without the need of exit pupil expansion nor eye tracking. The resolution of light-emitting diodes is foveated to match with the density of cones on the retina. In this manner, the total number of pixels as well as the latency of image processing can be significantly reduced. Based on the simulation, the device performance is quantitatively analyzed. For the real image, modulation transfer functions is 0.669757 at 30 cycle/degree, contrast ratio is 5, and distortion is 10%. For the virtual image, the field of view is 82°, best angular resolution is 0.38′, modulation transfer function is above 0.999999 at 30 cycle/degree, contrast ratio is 4988, and distortion is 6%.

We present a near-eye display featuring a triple-channel waveguide with chiral liquid crystal gratings. Our triple-channel waveguide is capable of dividing one field of view into three through both the polarization orthogonality and angular separation. To illustrate its principle, a k-space diagram, which takes into account the aspect ratio of field of view, is depicted. Our results demonstrate that its diagonal field of view reaches 90°, eye relief is 10 mm, exit pupil is 4.9 × 4.9 mm², transmittance is 4.9%, and uniformity is 89%.

We propose a design of a retinal-scanning-based near-eye display for augmented reality. Our solution is highlighted by a laser scanning projector, a diffractive optical element, and a moist eye with gradient refractive indices. The working principles related to each component are comprehensively studied. Its key performance is summarized as follows. The field of view is 122°, angular resolution is 8.09′, diffraction efficiency is 57.6%, transmittance is 80.6%, uniformity is 0.91, luminance is 323 cd/m², modulation transfer functions are above 0.99999 at 3.71 cycle/degree, contrast ratio is 4878, and distortion is less than 24%.

Modern education has undergone tremendous progress, and a large number of advanced devices and technologies have been introduced into the teaching process. We explore the application of artificial intelligence to education, using AI devices for classroom behavior analysis. Embedded systems are special-purpose computer systems tailored to an application. Embedded system hardware for wearable devices is often characterized by low computing power and small storage, and it cannot run complex models. We apply lightweight models to embedded devices to achieve real-time emotion recognition. When teachers teach in the classroom, embedded portable devices can collect images in real-time and identify and count students’ emotions. Teachers can adjust teaching methods and obtain better teaching results through feedback on students’ learning status. Our optimized lightweight model PIDM runs on low-computing embedded devices with fast response times and reliable accuracy, which can be effectively used in the classroom. Compared with traditional post-class analysis, our method is real-time and gives teachers timely feedback during teaching. The experiments in the control group showed that after using smart devices, the classroom teaching effect increased by 9.44%. Intelligent embedded devices can help teachers keep abreast of students’ learning status and promote the improvement of classroom teaching quality.

We propose a compact design of see-through near-eye display that is dedicated to presbyopia. Our solution is characterized by a plano-convex waveguide, which is essentially an integration of a corrective lens and two volume holograms. Its design rules are set forth in detail, followed by the results and discussion regarding the diffraction efficiency, field of view, modulation transfer function, distortion, and simulated imaging.