A monitoring system for obtaining a video related to medication adherence of a user, includes: a wireless communication device comprising a motion sensor, an ambient light sensor, a first transceiver transmitting data to an external device, and a first controller configured to control the motion sensor, the ambient light sensor, and the first transceiver, the wireless communication device having an attaching portion for being attached to an object containing a medication; and a wearable device including a camera, a second transceiver receiving a signal from the first transceiver, and a second controller configured to obtain video data through the camera based on the signal received through the second transceiver.

A method and system are proposed for the automatic counting of the number of insects in a trap. The method comprises acquiring, by means of an acquisition system, a plurality of spectral images of a trap or of a portion of the trap, wherein the spectral images are acquired for at least two different quasi-monochromatic spectral ranges after having sequentially illuminated the trap, or portion of the trap, with light at said two quasi-monochromatic spectral ranges. The trap, or portion of the trap, contains a series of objects adhered thereto, including insects, and optionally other particles. In addition, the method comprises counting, by means of a processor, the number of insects of a first type of said insects through the detection and differentiation of the insects of said first type taking the spectral and morphological parameters thereof into account.

Embodiments of work stations for use in a medical dose preparation management system are disclosed. A work station may include a camera stand. The camera stand may include a housing enclosing a camera and one or more light sources therein. As such, the camera and light sources may be directed at a medical dose preparation staging region to capture medical dose preparation images of the medical dose preparation staging region. The camera stand may include an adjustable support positionable in a plurality of positions to dispose the camera and light source relative to the medical dose preparation staging region. The work stations may facilitate improved image quality and record work flows carried out at the work station for preparation verification.

The present disclosure refers to a method for determining characteristics of particles of a bulk material such as fertilizer, seed or the like, comprising: providing a heap of particles of a bulk material to be distributed by a distribution machine; providing a measurement tool having an optical landmark on a front side in a measurement position in which the heaped particles of the bulk material are provided in proximity to the measurement tool; providing a camera device configured to detect images; detecting image data by the camera device, the image data indicative of an image of the front side of the measurement tool and the heaped particles provided in proximity to the measurement tool; and determining characteristics of the particles from image data analysis of the image data. Further, a measurement system for determining characteristics of particles of a bulk material is provided.

A drug inspection apparatus inspects drugs that are prepared based on prescription information and are packaged in a prescription bag. A drug database includes drug images of drugs that can be prepared. A comparison target selection section acquires drug images of drugs, which are prepared according to the prescription, and drugs similar thereto from the drug database. A first drug determination section compares captured images of prepared drugs with the drug images acquired from the drug database, and determines drugs present in the captured images and the number thereof. An inspection result determination section determines whether or not the prepared drugs and the number thereof match the prescription information based on the prescription information.

A drug inspection apparatus inspects drugs that are prepared based on prescription information and are packaged in a prescription bag. A drug database includes drug images of drugs that can be prepared. A comparison target selection section acquires drug images of drugs, which are prepared according to the prescription, and drugs similar thereto from the drug database. A first drug determination section compares captured images of prepared drugs with the drug images acquired from the drug database, and determines drugs present in the captured images and the number thereof. An inspection result determination section determines whether or not the prepared drugs and the number thereof match the prescription information based on the prescription information.

Databases storing digital fingerprints of physical objects enable enhanced security and collaborative authentication. Digital fingerprints enable reliable identification of an object without the need for attaching or associating physical tags, labels or other identifying materials with the object; and serialization for identification also is obviated. By combining digital fingerprinting and data collaboration in one process, parties to the data collaboration can gain a level of certainty that data attributed to an object by different parties or at different times is attributed to only that object and not erroneously attributed to an incorrect or counterfeit object. Collaborative authentication platforms and processes, combining digital fingerprint databases with associated incentive databases, contribute enhanced information to the authentication databases, and provide unparalleled reliability and enriched metadata to supply chain tracking, detecting counterfeit objects, and other applications.

Manually operated pipettors, widely used in clinical, forensics, pharmaceutical research, hospital and biotech laboratories to transfer small volumes of liquid, may be subject to positional errors, operator use errors and hidden performance degradation. Manual pipette performance cannot be accepted without monitoring and reporting. This invention concerns a computer controlled vision tracking and lighting system working in conjunction with a sensor controlled fluid dispensing device and controller to confirm pipette tip positional locations during aspiration and dispensing operations with automatic monitoring of liquids entering and leaving a pipette apparatus to digitally track a manual pipetting operation with a digital output file of validated liquid transfer results. The invention may also monitor possible error conditions and prevent improper liquid transfers during the manual process.

A drug list display method includes: obtaining a first image of drugs captured from one side of the drugs; clipping from the first image, areas where the respective drugs are displayed to obtain first clipped images; displaying the first clipped images in a list form in a certain order in a first area on a display in such a manner that one or more of the first clipped images may be designated; determining correct drugs for first clipped images designated by a user; and displaying information on the correct drugs determined for the respective first clipped images in a second area on the display different from the first area, wherein the first clipped images and the corresponding information on the correct drugs are displayed in association with each other.

Provided is a server for determining whether medication has been administered, the server including: a transceiver receiving a video recorded by a wearable device; a memory storing a detection model and a confirmation model, wherein the detection model is trained to output whether each of preset targets appears in an image, and the confirmation model is trained to output whether medication has been administered, wherein the preset targets include an object related to a medicine or a medicine container and a posture related to medication administration; and one or more processors configured to detect the preset targets by inputting image frames of the video to the detection model and to determine whether medication has been administered by inputting confirmation model input data to the confirmation model, the confirmation model input data generated based on a detection result of the detection model.