PATENT CLAIM ANALYSIS

Application Number: 16015344
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-12
Patent Classification: ["700", "275000"]

Abstract:
Methods, mediums, and systems include use of a system manger application in a data processing system for fault detection a building automation system using deep learning, to receive point data for a hardware being analyzed, where the received point data is contaminated data, train a deep learning model for the hardware being analyzed, generate predicted data based on the deep learning model, analyze the predicted data and the received point data, identify a fault in the hardware being analyzed according to the received point data and the predicted data, and produce a fault report according to the identified fault.

Claim (Index 5):
The method of  claim 1 , wherein analyzing the predicted data and the received point data includes include applying cumulative sum control chart (CUSUM) sequential analysis for summing, weighting, and change detection.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 94.0
- Lexical Diversity: 2.31915
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15188824', '15134787', '14919516', '15182580', '15182579']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4065910438905296
- 35 USC 102 Novelty (BERT): 0.4828251125711981
- Combined Prediction Score: 0.4142144507585964
- Mean Citation Score: 141.50243400000005
- Max Citation Score: 154.72191999999995
- Similarity Product: 97.38267963287348

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

Dataset: test