10 results about "Activity sensing" patented technology

Clock enable signals are collected and summed. The number of simultaneously enabled clock enable signals can represent switching activity within a system and can be used as an indicator for power management, noise management, etc. of such a system. Digital switching activity sensing include performance of an operation to sum a quantity of open clock gates associated with a plurality of latches that are grouped into multiple subsets of latches. An activity indication is generated based, at least in part, on a result of the operation to sum the quantity of open clock gates associated with the plurality of latches.

The application discloses a kind of based on surface acoustic wave's red blood cell activity evaluation device and method.Device includes injection pump, syringe, silica gel hose, red blood cell activity sensing platform, power signal generator, amplitude phase measurement circuit.Red blood cell activity sensing platform is three-layer structure, from top to bottom respectively microchannel layer, piezoelectric layer and temperature control layer.Temperature control layer uses indium tin oxide conductive glass, and realizes the stable control of temperature by designing corresponding circuit pattern.Lithium niobate is used as piezoelectric layer, and surface acoustic wave is generated.Surface acoustic wave acts on red blood cell in microchannel layer, and judges by measuring the amplitude of output surface acoustic wave to evaluate the activity of red blood cell.

This utility model discloses a multifunctional ceiling-mounted lighting device, relating to the field of intelligent lighting technology. It includes: a mounting body for connection to a wall and / or ceiling; a first slot at the first end of the mounting body and a second slot at the second end; the first slot, the second slot, and the mounting body together form an embedded mounting cavity; a lighting component connected to the mounting body; and a sensing component disposed within the mounting cavity. The sensing component includes an air quality sensor, an ambient light sensor, and an activity detection sensor, with the ambient light sensor connected to the lighting component; and a linkage control module connected to both the lighting component and the sensing component. By integrating the sensing component into the embedded mounting cavity, installation efficiency is improved and maintenance costs are reduced, achieving an integrated design of architectural decorative lines and functional modules. By incorporating the air quality sensor and the activity detection sensor, environmental monitoring and human activity sensing functions are simultaneously realized.

The invention relates to the technical field of air conditioning, in particular to a fresh air system of an on-duty platform and a fresh air control method. The system comprises an environment parameter collecting module, a personnel activity sensing module, a control module and a fresh air adjusting module. The environment parameter acquisition module monitors the space environment quality index in the on-duty platform, the personnel activity sensing module obtains the personnel existence state and activity intensity information, and the control module dynamically calculates the fresh air demand value through a built-in control algorithm according to the data and generates a control signal. The fresh air adjusting module responds to the control signal to adjust the fresh air inlet air volume. The control method comprises the steps of collecting environment parameters and personnel activity data, executing multivariable analysis to calculate the target fresh air volume, driving the fresh air execution unit to adjust the air volume and the like. The dynamic demand model is constructed through multi-source data fusion, the model parameters are optimized through an online learning mechanism, and the environment control precision and the energy utilization efficiency are improved through self-adaptive fresh air regulation and control according to the actual use condition of the on-duty platform.

Neuroimaging and / or brain activity sensing machines, such as MEG and OPM machines use a helmet-like or head covering device that includes sensors for acquiring information from a participant's brain activity. The machine is operated while the participant undergoes tests, which can include a need for sight. People with glasses, therefore, need access to their glasses, but the glasses need to be non-ferromagnetic. In addition, due to the shape of the helmet-like objects and the need to have the sensors as close to the participant's head as possible, having glasses that include a contour that closely matches the shape of the helmet will improve the information obtained by the machine.

This invention discloses an object activity sensing system, method, device, and storage medium. The system includes: an ultrasonic transmitting module for continuously transmitting ultrasonic signals; an ultrasonic receiving module for continuously receiving and processing spatially propagating sound wave signals to obtain multi-channel ultrasonic signals; an ultrasonic preprocessing module; an ultrasonic positioning module for calculating the motion trajectory of a moving object; an ultrasonic activity detection module for detecting whether there is a moving object within a specific range; and a decision module for determining whether there is an object within a given distance D1 and whether there is a moving object within a given distance D2, where D2>D1. This invention can simultaneously detect the presence of stationary objects at close range and moving objects at a distant distance. It is fast and convenient to implement, can directly use the audio hardware built into electronic devices without increasing hardware costs, and is highly efficient. It has significant application value and enormous economic value in fields such as smart homes and consumer electronics.

This utility model discloses an intelligent human activity sensing light system, including a control system power supply section, a control chip U1, a control chip U2, and an AC load terminal. The control system power supply section includes input voltage AC1 and input voltage AC2. Input voltage AC2 is connected in series with fuse F1 and connected to the first terminal of rectifier bridge BD1. Input voltage AC2 is connected to the third terminal of rectifier bridge BD1. The control chip U1 is used to convert AC current to DC12V, and the control chip U2 is used to convert DC12V to DC3.3V. The DC3.3V is used to power control chip U3 and a pyroelectric infrared sensor. The control chip U3 is also connected to a photoresistor CDS1. The first terminal of the AC load terminal is connected between TR1 and capacitor C2 and connected in series with capacitor C0. The second terminal of the AC load terminal is connected in series with AC2 after fuse F1. A relay RY1 and a resistor R10 are connected in series between the first and second terminals of the AC load terminal. The control chip U3 is used to control the on / off state of relay RY1.

The invention discloses a fish activity sensing method, device and equipment based on underwater distributed optical fiber sensing and a medium, and the method comprises the steps: obtaining a local disturbance signal in a target water area based on the Rayleigh scattering characteristic or Brillouin scattering characteristic of a distributed optical fiber; acquiring temperature data and flow field characteristic data corresponding to the local disturbance signal under the same time sequence; feature extraction is carried out on the local disturbance signals, the corresponding temperature data and the corresponding flow field characteristic data, corresponding multi-dimensional features are obtained, and the multi-dimensional features comprise time domain features, frequency domain features and time frequency features; and training a deep learning model based on the multi-dimensional features and the fish behaviors of the multi-dimensional feature pairs, and after training is completed, using the deep learning model to predict the fish behaviors. The invention belongs to the field of fish behavior prediction. According to the invention, accurate prediction of fish behaviors in a complex water body can be realized.

The invention discloses a multifunctional AI intelligent sensing lighting device, and belongs to the technical field of lighting. The device integrates a power supply module, a lighting module, a sensing module, a control module, a hinting acousto-optic module and a switch operation module, and has an autonomous mode, a long-time lighting mode and an emergency help seeking function at the same time. Ambient light perception, human body activity induction, AI intelligent control and emergency help seeking are achieved through the modules. The main functions of the device include that after a main lighting lamp is turned off, the device automatically and gradually brightens; brightness and lighting duration are intelligently predicted and adjusted according to human body activity information AI, and sensor detection sensitivity is autonomously adjusted to reduce false triggering; human-computer interaction functions such as power supply under-voltage prompt, trigger prompt and power-on self-test are realized; and an energy-saving optimization mechanism is provided in the operation process. According to the device, the LED light source with the specific color temperature is adopted, light is gradually brightened and darkened, and the user experience is improved; a special control circuit is arranged in the device, multi-mode intelligent switching and power supply energy-saving management are achieved, and the problems that an existing lighting device is single in function, insufficient in intelligent degree and poor in emergency capacity are effectively solved.

A method for identifying an event in a room using wireless signals includes pre-processing channel state information to determine one or more aspects a person in a room based on selected channel state information segments, and identifying, using a machine learning model, an event in the room based on the one or more aspects of the person in the room. The method also includes determining, using the machine learning model and based on the event in the room, one or more settings of a machine, and controlling, using the one or more settings, operation of the machine in response to identifying the event in the room.