Human-Computer Interaction (HCI) raises demand of convenience, endurance, responsiveness and naturalness. This paper describes a design of a compact wearable low-power HCI equipment applied to gesture recognition. System combines multi-mode sense signals: the vision sense signal and the motion sense signal, and the equipment is equipped with the depth camera and the motion sensor. The dimension (40 mm × 30 mm) and structure is compact and portable after tight integration. System is built on a module layered framework, which contributes to real-time collection (60 fps), process and transmission via synchronous confusion with asynchronous concurrent collection and wireless Blue 4.0 transmission. To minimize equipment’s energy consumption, system makes use of low-power components, managing peripheral state dynamically, switching into idle mode intelligently, pulse-width modulation (PWM) of the NIR LEDs of the depth camera and algorithm optimization by the motion sensor. To test this equipment’s function and performance, a gesture recognition algorithm is applied to system. As the result presents, general energy consumption could be as low as 0.5 W.
Based on the energy-saving and safe-driving requirements of road lighting, a kind of energy-saving system is proposed for street lamps in this paper, which is handled by two controllers. At daybreak and dusk, the lamps are turned on or off according to local sunrise and sunset. And at night, it is controlled by a fuzzy controller. Traffic flow and its variation rate, the highest road speed limit are taken as the inputs of the controller, at the same time, the lighting comfort and the experience of driver are defined as the fuzzy sets and control rules. LED lamps are used in the system as illuminant. The numerical simulation in MATLAB and analysis on the practical measured data show that the system is effective in energy-saving for road lighting.