PATENT CLAIM ANALYSIS

Application Number: 15973202
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-11
Patent Classification: ["709", "221000"]

Abstract:
The present disclosure discloses a system that automatically identifies the most efficient times to upgrade software associated with an IoT device. The system employs machine-learning mechanisms to precisely identify the specific time interval where there will be the least impact on the functionality of the IoT device or a cluster of IoT devices.

Claim (Index 13):
A non-transitory computer readable medium encoded with instructions, the instructions executable by a computing device, comprising:\n obtaining first data from at least one Internet of Things (\u201cIoT\u201d) device of a plurality of IoT devices included in a distributed network, each said IoT device of the plurality of IoT devices comprising software; generating a machine trained model that specifies at least one consistent pattern or consistent change in the first data obtained from the at least one IoT device of the plurality of IoT devices; receiving, from the at least one IoT device, second data comprising sensor data; using the machine trained model and the second data to predict time intervals during which sensed data associated with the at least one IoT device will be constant or predictable; identifying a specific time interval from the predicted time intervals during which a software upgrade would result in at least possible impact on a functionality of the at least one IoT device; and receiving an indication that the at least one IoT device will be upgraded during the specific time interval.

Metadata:
- Claim Count in Document: 21.0
- Percentile: 93.0
- Lexical Diversity: 1.30952
- Patent Class: 709.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14187102', '15413158', '15625029', '15645784', '15921684']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2304408284735652
- 35 USC 102 Novelty (BERT): 0.4720869976471152
- Combined Prediction Score: 0.2546054453909202
- Mean Citation Score: 118.676619
- Max Citation Score: 129.32709
- Similarity Product: 85.52704992897034

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test