PATENT CLAIM ANALYSIS

Application Number: 16280451
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-06
Patent Classification: ["718", "102000"]

Abstract:
A dynamic, distributed directed activity network comprising a directed activity control program specifying tasks to be executed including required individual task inputs and outputs, the required order of task execution, and permitted parallelism in task execution; a plurality of task execution agents, individual of said agents having a set of dynamically changing agent attributes and capable of executing different required tasks in said activity control; a plurality of task execution controllers, each controller associated with one or more of the task execution agents with access to dynamically changing agent attributes; a directed activity controller for communicating with said task execution controllers for directing execution of said activity control program; a communications network capable of supporting communication between said directed activity controller and task execution controllers; and wherein said directed activity controller and task execution controllers communicate via said communication network to execute said directed activity control program using selected task execution agents.

Claim (Index 1):
A distributed directed activity control method comprising a cloud-based data processing and storage system and internet connected computers, data storage, controllers and task execution agents for directed activity control execution with at least one specialized computer machine including electronic artificial intelligence expert system decision making capability and further comprising:\n the step of connecting said task execution agents to the internet via task execution agent controllers; the step of creating graphic representation of multiple interconnected nodes for all or part of said directed activity control method wherein said nodes further comprise function nodes, analytic nodes and/or storage nodes with inputs and outputs; the step of storing in memory one or more of said directed activity control programs comprising digital workflow representations for control of execution of interrelated tasks including permitted parallelism in task execution; the step of storing in memory digital model history files comprising potentially dynamically changing task execution agent attributes describing task execution agent characteristic and operational status; the step of storing in memory digital task input and output object flow representations of said directed activities; the step of storing in memory artificial intelligence expert system specified workflow propositional logic rules defining task execution agent asset attribute ranges and defined threshold values for triggering activities depending on said task execution agent asset attribute values and said propositional logic rules; the step of electronically receiving from task execution agents messages providing task execution status, sensor derived information and potentially dynamically changing task execution agent attributes; the step of updating said digital model history files and statistical analysis of potentially dynamically changing task execution attributes stored in digital model history files based on information in said task execution agent received messages; the step of digital model artificial intelligence expert system analysis based on said workflow propositional logic rules; the step of designating a particular internet accessible task execution agent for executing a particular task with said digital model artificial intelligence expert system analysis and load balancing based on said task execution agent availability and utilization; the step of electronically transmitting by the one or more electronic programmable artificial intelligence control computer machines one or more control messages to at least one selected internet accessible contained distributed task execution agent to direct execution of particular tasks; and whereby improved resource utilization efficiency is achieved based on the use of artificial intelligence expert systems decision making in the execution of artificial intelligence expert system directed activity control program and sensor derived information.

Metadata:
- Claim Count in Document: 62.0
- Percentile: 99.0
- Lexical Diversity: 2.4697
- Patent Class: 718.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15979350', '15274635', '14489974', '10720893', '11044233']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4583353176180613
- 35 USC 102 Novelty (BERT): 0.5998957186347035
- Combined Prediction Score: 0.4724913577197256
- Mean Citation Score: 357.01718
- Max Citation Score: 491.63574000000006
- Similarity Product: 380.9072115518618

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