Methods and systems for activity monitoring include capturing an infrared image of an environment that comprises at least one patient being monitored and at least one infrared-emitting tag. A relationship between the patient being monitored and the at least one infrared-emitting tag is determined. An activity conducted by the patient being monitored is determined based on the relationship between the patient being monitored and the at least one infrared-emitting tag. A course of treatment for the patient being monitored is adjusted based on the determined activity.

A system for monitoring a patient in a patient area having one or more detection zones, the system comprising one or more cameras, a user interface, and a computing system configured to receive a chronological series of frames from the one or more cameras, identify liquid candidates by comparing a current frame with a plurality of previous frames of the chronological series, determine locations of the liquid candidates, identify thermal signatures of the liquid candidates, determine types of liquids of the liquid candidates based on the locations and thermal signatures of the liquid candidates, and generate an alert with the user interface corresponding to the determined types of liquids.

A system for monitoring a patient in a patient area having one or more detection zones, the system comprising one or more cameras, a user interface, and a computing system configured to receive a chronological series of frames from the one or more cameras, identify liquid candidates by comparing a current frame with a plurality of previous frames of the chronological series, determine locations of the liquid candidates, identify thermal signatures of the liquid candidates, determine types of liquids of the liquid candidates based on the locations and thermal signatures of the liquid candidates, and generate an alert with the user interface corresponding to the determined types of liquids.

A device for detecting energy beam is provided. The device comprises a carbon nanotube structure, a support structure and an infrared detector. The carbon nanotube structure comprises a plurality of carbon nanotubes, and an extending direction of each carbon nanotube is parallel to a direction of an energy beam to be detected. The support structure is configured to support the carbon nanotube structure, and make a portion of the carbon nanotube structure suspended in the air. The infrared detector is located below and spaced apart from the carbon nanotube structure. The infrared detector is configured to detect a temperature of a suspended portion of the carbon nanotube structure, and image according to a temperature distribution of the carbon nanotube structure. A method for detecting energy beam is also provided.

A device for detecting energy beam is provided. The device comprises a carbon nanotube structure, a support structure and an infrared detector. The carbon nanotube structure comprises a plurality of carbon nanotubes, and an extending direction of each carbon nanotube is parallel to a direction of an energy beam to be detected. The support structure is configured to support the carbon nanotube structure, and make a portion of the carbon nanotube structure suspended in the air. The infrared detector is located below and spaced apart from the carbon nanotube structure. The infrared detector is configured to detect a temperature of a suspended portion of the carbon nanotube structure, and image according to a temperature distribution of the carbon nanotube structure. A method for detecting energy beam is also provided.

A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

An unmanned aerial vehicle (UAV) logs first UAV information at a first frequency. The UAV triggers a camera associated with the UAV to capture an image. In response to triggering the camera to capture the image, the UAV logs second UAV information at a second frequency that is higher than the first frequency. A device that is separate from the UAV identifies a location of the UAV corresponding to the image based on a capture timestamp of the image received from the camera, the first UAV information, and the second UAV information. The device generates a geo-rectified imagery based on the image and the location of the UAV.

An unmanned aerial vehicle (UAV) logs first UAV information at a first frequency. The UAV triggers a camera associated with the UAV to capture an image. In response to triggering the camera to capture the image, the UAV logs second UAV information at a second frequency that is higher than the first frequency. A device that is separate from the UAV identifies a location of the UAV corresponding to the image based on a capture timestamp of the image received from the camera, the first UAV information, and the second UAV information. The device generates a geo-rectified imagery based on the image and the location of the UAV.

Methods of sensor readout and calibration and circuits for performing the methods are disclosed. In some embodiments, the methods include driving an active sensor at a voltage. In some embodiments, the methods include use of a calibration sensor, and the circuits include the calibration sensor. In some embodiments, the methods include use of a calibration current source and circuits include the calibration current source. In some embodiments, a sensor circuit includes a Sigma-Delta ADC. In some embodiments, a column of sensors is readout using first and second readout circuits during a same row time.