System and method for indoor tag localization and identification
A system and method for indoor tag localization and identification are disclosed. The system includes one or more environment-specific tags positioned at known locations within an indoor environment and a user-associated imaging device (UAID) carried by or attached to a user. The UAID includes a camera configured to capture images of the environment and a user tag for external identification. An image-tag processing system (ITPS) executes one or more trained convolutional neural network (CNN) models to identify environment tags, determine a location and orientation of the UAID relative to the tags, and identify the UAID and its associated user. The ITPS may also process motion or physiological sensor data and generate alerts or map updates. The system enables accurate, real-time indoor localization, user identification, and event detection within facilities such as hospitals, care centers, or industrial environments.
1 . A system for indoor tag localization and identification, comprising:
an environment-specific tag disposed at a predetermined position within an indoor environment, the environment-specific tag comprising a unique identifier associated with a corresponding indoor environment location;
a user-associated imaging device (UAID) including a UAID processor, a UAID memory, UAID camera and a UAID tag, wherein:
the UAID is configured to be carried by, attached to, or positioned proximate to a user of the UAID;
the UAID camera is configured to be directed outward from the user of the UAID and capture images of the indoor environment location including the environment-specific tag; and
the UAID tag is coupled to or associated with the UAID for external identification, wherein the UAID is configured to associate the UAID tag with a UAID identifier and a user identifier, wherein the UAID identifier is associated with the UAID, and the user identifier is associated with a user of the UAID;
a fixed camera positioned within the indoor environment and configured to capture images of the UAID tag; and
an image tag processing system (ITPS) comprising an ITPS processor, an ITPS memory, and one or more trained convolutional neural network (CNN) models, wherein the ITPS is operatively connected to an output device and configured to:
receive environment-tag image data from the UAID, and execute at least one of the one or more trained CNN models to predict the indoor environment location of the UAID and a distance of the UAID from the environment-specific tag based on outputs of the one or more trained CNN models;
receive UAID-tag image data from the fixed camera and execute at least one of the one or more trained CNN models to predict the UAID identifier and the user identifier of the UAID based on the UAID-tag image data; and
output, on the output device, information selected from the group consisting of: the UAID identifier, the user identifier, the indoor environment location of the UAID, the distance of the UAID from the environment-specific tag, and combinations thereof.
2 . The system of claim 1 , wherein the UAID further comprises an inertial measurement unit (IMU) configured to measure linear acceleration and angular velocity, and wherein the ITPS is configured to receive data regarding the linear acceleration and angular velocity from the UAID.
3 . The system of claim 2 , wherein the ITPS is configured to detect a fall or abnormal movement pattern based on data from the IMU and to generate an alert message via the output device, the alert message being selected from the group consisting of: a visual indication, an audible signal, a haptic or tactile signal, a wireless transmission to a remote computing device or network server, and combinations thereof.
4 . The system of claim 3 , wherein the alert message includes information selected from the group consisting of: the UAID identifier, the user identifier, the indoor environment location of the UAID, the distance of the UAID from the environment-specific tag, and combinations thereof.
5 . The system of claim 2 , wherein the UAID is a smartwatch or smart bracelet.
6 . The system of claim 1 , wherein the UAID comprises at least one physiological sensor configured to measure at least one physiological parameter of the user of the UAID.
7 . The system of claim 6 , wherein the at least one physiological parameter is selected from the group consisting of: heart rate, blood oxygen level, body temperature, blood pressure, and combinations thereof.
8 . The system of claim 1 , wherein the UAID is mounted to a mobile platform selected from the group consisting of: a wheelchair, bed, cart, or walker.
9 . The system of claim 1 , wherein the ITPS is further configured to determine a pose vector of the UAID relative to the environment-specific tag based on the environment-tag image data received from the UAID.
10 . The system of claim 1 , wherein the output device produces an output from the group consisting of: a visual display, an audible message, a haptic or tactile signal, a wireless transmission to a remote computing device or network server, and combinations thereof.
11 . A method for indoor tag localization and identification, comprising:
disposing an environment-specific tag at a predetermined position within an indoor environment, the environment-specific tag having a unique identifier associated with a corresponding indoor environment location;
providing a user-associated imaging device (UAID) including a UAID processor, UAID memory, UAID camera, and UAID tag, wherein the UAID is configured to be carried by or attached to a user and the UAID camera is directed outward from the user;
capturing, by the UAID camera, one or more images of the indoor environment including the environment-specific tag;
capturing, by a fixed camera positioned within the indoor environment, one or more images of the UAID tag;
receiving, at an image-tag processing system (ITPS), environment-tag image data from the UAID and UAID-tag image data from the fixed camera;
executing, by the ITPS, one or more trained convolutional neural network (CNN) models to:
predict an indoor environment location of the UAID and a distance of the UAID from the environment-specific tag based on the environment-tag image data;
predict a UAID identifier and a user identifier based on the UAID-tag image data; and
outputting, via an output device operatively connected to the ITPS, information selected from the group consisting of: the UAID identifier, the user identifier, the indoor environment location of the UAID, the distance of the UAID from the environment-specific tag, and combinations thereof.
12 . The method of claim 11 , further comprising receiving inertial measurement data from an inertial measurement unit (IMU) of the UAID, the inertial measurement data including linear acceleration and angular velocity.
13 . The method of claim 12 , further comprising detecting a fall or abnormal movement pattern based on the inertial measurement data and, in response, generating and outputting an alert message via the output device, the alert message being selected from the group consisting of: a visual indication, an audible signal, a haptic or tactile signal, a wireless transmission to a remote computing device or network server, and combinations thereof.
14 . The method of claim 12 , wherein the alert message includes information selected from the group consisting of: the UAID identifier, the user identifier, the indoor environment location of the UAID, the distance of the UAID from the environment-specific tag, and combinations thereof.
15 . The method of claim 11 , wherein the UAID is a smartwatch or smart bracelet.
16 . The method of claim 11 , further comprising measuring, by the UAID, at least one physiological parameter of the user using at least one physiological sensor.
17 . The method of claim 16 , wherein the at least one physiological parameter is selected from the group consisting of: heart rate, blood oxygen level, body temperature, blood pressure, and combinations thereof.
18 . The method of claim 11 , wherein the UAID is mounted to a mobile platform selected from the group consisting of: a wheelchair, bed, cart, or walker.
19 . The method of claim 11 , further comprising determining a pose vector of the UAID relative to the environment-specific tag based on geometric distortion of the environment-specific tag in the captured images.
20 . The method of claim 11 , wherein the output device produces an output selected from the group consisting of: a visual display, an audible message, a haptic or tactile signal, a wireless transmission to a remote computing device or network server, and combinations thereof.