PATENT CLAIM ANALYSIS

Application Number: 16216210
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["382", "103000"]

Abstract:
An unauthorized visitor system collects an image of a person detected in a room of a patient. The system identifies reference points on the person's face, for example, points along the cheeks, jowls, and/or brow. The system may compare the reference points to reference points of images associated with registered visitors. The system then determines, based on the comparison, if the person is a registered visitor. One or more designated recipients may be alerted if the person is not a registered visitor or if the person breaches a patient identification zone established around a particular patient. The system may also register the person in a database of visitors.

Claim (Index 1):
A system for detecting unauthorized visitors, the system comprising:\n one or more 3D motion sensors located to provide the one or more 3D motion sensors with a view of a person and surrounding area to be monitored; and a computerized monitoring system communicatively coupled to the one or more 3D motion sensors, the computerized monitoring system configured to:\n utilize one or more images received from the one or more 3D motion sensors to identify the person being monitored; \n detect when a visitor enters the view of the one or more 3D motion sensors; \n using one or more images received from the one or more 3D motion sensors, determine whether the visitor is an unauthorized visitor by identifying a plurality of reference points on the face of the visitor to compare to a plurality of registered reference points on the faces of registered visitors; \n initiate an alert being sent to one or more designated recipients; and \n determine whether the unauthorized visitor made one or more corrective actions based on information received from the one or more 3D motion sensors after the alert is sent to one or more designated recipients.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 98.0
- Lexical Diversity: 1.95161
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15848621', '15395526', '15848730', '15395250', '16158729']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3741745488774306
- 35 USC 102 Novelty (BERT): 0.5575274517820543
- Combined Prediction Score: 0.392509839167893
- Mean Citation Score: 336.29908799999987
- Max Citation Score: 424.48364
- Similarity Product: 409.6331026702069

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test