Medication Verification via Cloud ML and Imaging
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Solution Overview
Problem
Current medication verification systems require complex devices with extensive processing resources and are limited to analyzing only the medication, not the container or its seal, necessitating the development of a more efficient and accurate method for identifying and verifying medication within containers.
Innovation Solution
A medication device equipped with a camera and weighing system that sends image and weight data to a platform for identification using machine learning models, allowing for verification of both the medication and the integrity of its container seal, reducing the need for elaborate components and processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex devices with extensive processing resources are used for medication verification, then verification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent introduces a cloud-based machine learning platform as an intermediary between the simple medication verification device and the verification process. The device captures images and transmits them to the cloud platform, which performs complex analysis using trained machine learning models. This allows the device to maintain simplicity while achieving high verification accuracy through the intermediary's computational power.
Solution Approach 2:
The patent replaces complex mechanical verification systems with an optical imaging system combined with machine learning algorithms. Instead of using elaborate physical components and mechanical processing, the system uses a camera to capture images and machine learning models to analyze them, substituting mechanical complexity with computational intelligence that can be centralized in the cloud.
2Measurement precision
If complex devices are used for medication verification, then verification capability is improved, but processing resources required increase
Solution Approach 1:
The cloud-based machine learning platform serves as an intermediary that handles all computationally intensive processing. The medication verification device itself requires minimal processing resources, only capturing images and transmitting data. The energy-consuming machine learning inference and model training occur remotely in the cloud, allowing the device to maintain low power consumption while achieving high verification capability.
3Measurement precision
If traditional verification systems are used, then medication analysis is performed, but container seal integrity cannot be assessed
Solution Approach 1:
The patent makes the verification system universal by enabling it to perform multiple functions: identifying medication type, verifying dosage, and assessing container seal integrity. The machine learning models are trained to recognize multiple aspects of medication containers simultaneously, allowing a single system to handle diverse verification tasks that traditional specialized systems could not perform together.
Data Source
AI summary
A device obtains prescription information relating to a medication in a container. The device causes a camera device of the device to obtain image data relating to the medication and a weighing device of the device to obtain weight data relating the medication. The device sends the prescription information, the image data, and the weight data to a different device to cause the different device to verify the medication using a machine learning model. The device receives information concerning the medication and automatically generates, based on the information concerning the medication, a message concerning the medication, wherein the message includes instructions on how much of the medication a user of the device is to take. The device causes the device or an additional device to present the message.