PATENT CLAIM ANALYSIS

Application Number: 16280419
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-08
Patent Classification: ["702", "003000"]

Abstract:
In an approach, a method for fusing point data with areal averages is performed by a computing system. The fusion procedure is coherent, in the sense that the computing system takes into account what the areal averages represent with respect to the point data. The overarching goal is to fit a model that takes into account the information derived from both data sets. The areal averages provide an estimate for what the integral of a model representing the behavior of the environmental variable should be over a particular district and the point values indicate the estimated value at particular locations. Thus, the integral of the fitted model over a district of the grid should approximate the value provided by the areal averages while also approximating the value provided by the point data for locations which are provided by the point data.

Claim (Index 1):
A method comprising:\n receiving, from one or more physical sensors in an area under observation, a set of observations of an environmental variable, wherein:\n the set of observations includes one or more point observations and one or more areal average observations; and \n each point observation of the one or more point observations specifies a mean and a variance of the environmental variable at a particular location of the area under observation and a time step of a set of time steps; \n defining a state-space model that maps the one or more point observations and the one or more areal average observations onto a set of latent Gaussian processes and describes how the set of latent Gaussian processes evolves over time; setting an initial mean and an initial variance for each Gaussian process of the set of latent Gaussian processes in the state-space model based on observations of the set of observations; starting with an initial time step of the set of time steps and ending at a final time step of the set of time steps, fitting the state-space model to the set of observations; for each Gaussian process of the set of latent Gaussian processes:\n receiving a location and a time step for which to predict a mean and a variance of the environmental variable; and \n estimating the mean and the variance of the environmental variable based on the state-space model.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 2.0411
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15153392', '16240610', '15066958', '14681886', '10672598']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1982411868818694
- 35 USC 102 Novelty (BERT): 0.54733360768303
- Combined Prediction Score: 0.2331504289619854
- Mean Citation Score: 272.249522
- Max Citation Score: 415.5181
- Similarity Product: 328.3766282890916

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