Distributed activity control systems for artificial intelligence task execution direction including task adjacency and reachability analysis

Patent metadata

Field	Value
Publication number	US-12354019-B2
Application number	US-202418770567-A
Country	US
Kind code	B2
Filing date	Jul 11, 2024
Priority date	Sep 18, 2014
Publication date	Jul 8, 2025
Grant date	Jul 8, 2025

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, permitted parallelism in task execution, task adjacency to subsequent tasks, and reachability from each task to other tasks; 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; 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; and, a communications network supporting communication between said directed activity controller and task execution controllers for directing execution of said directed activity control program using selected task execution agents.

First claim

The embodiments of the invention in which an exclusive property or privilege is claimed are defined as follows:

1. A method for Artificial Intelligence (AI) controlling execution of interrelated distributed tasks comprising a remote or cloud-based data processing and storage system and internet connected computers, data storage, task execution agents, and associated task execution controllers wherein said task execution agents comprise computer equipment, communication equipment, transportation equipment, manufacturing equipment, and persons, and further comprising:
transporting people and/or goods via said task execution agent transportation equipment comprising motor vehicles;
communicating between said motor vehicles and other task execution agents via network cellular transceivers, data transceivers, optical transceivers, Bluetooth transceivers, Wi-Fi transceivers, satellites, or the world-wide-web;
communicating between said motor vehicles and network computing equipment including cloud computing, storage equipment, and databases;
communicating between said motor vehicles and said persons;
communicating between said motor vehicles and infrastructure sensors or cameras for monitoring selected objects or scenes for critical situations affecting operations of said method;
identifying said motor vehicles with RFID identification tags and RFID infrastructure RFID identification tag readers;
monitoring the location with infrastructure location measurement equipment of one or more of said motor vehicles, computer equipment, communication equipment, other transportation equipment, manufacturing equipment, and persons;
storing in memory one or more interrelated distributed task control programs comprising digital workflow instructions for control of execution of interrelated tasks including task precedence requirements and permitted parallelism in task execution;
storing in memory artificial intelligence expert system specified workflow propositional logic rules defining attributes and defined threshold values ranges for said motor vehicles for triggering activities depending on attribute values and said propositional logic rules;
electronically receiving from said motor vehicles messages providing task execution status, sensor derived information and/or potentially dynamically changing motor vehicle attributes;
artificial intelligence digital model expert system analysis based on said workflow propositional logic rules;
designating a particular internet accessible motor vehicle for executing a particular task with said digital model artificial intelligence expert system analysis including load balancing based on said motor vehicle status comprising task execution agent availability and utilization;
electronically transmitting by the one or more electronic programmable artificial intelligence control computers one or more control messages to at least one selected Internet accessible motor vehicle to direct execution of particular tasks; and,
whereby improved resource utilization efficiency is achieved based on said motor vehicle execution status message information and artificial intelligence expert systems derived decisions directing the execution of said interrelated distributed tasks.

2. The method of claim 1 wherein said communications equipment comprises internet connections.

3. The method of claim 1 wherein said communications equipment comprises switching systems and wireless communication devices.

4. The method of claim 1 wherein said communications equipment comprises special purpose controllers with communication capabilities.

5. The method of claim 1 further comprising monitoring traffic congestion encountered by said motor vehicles.

6. The method of claim 1 further comprising said motor vehicles capturing images for monitoring congestion, natural disasters, fires, violence, or other events with transmission of such images to remote destinations for analysis.

7. The method of claim 1 further comprising selecting motor vehicles for task execution based on GPS determination of the locations of said motor vehicles.

8. The method of claim 1 further comprising selecting said motor vehicles for task execution based on said motor vehicle capability.

9. The method of claim 1 further comprising selecting said motor vehicles for task execution based on motor vehicle cost.

10. The method of claim 1 further comprising selecting said motor vehicle for task execution based on said motor vehicle availability.

11. The method of claim 1 further comprising the step of selecting task execution agents for task execution based on task execution agent capacity.

12. The method of claim 1 further comprising selecting said motor vehicles for task execution based on said motor vehicle utilization.

13. The method of claim 1 further comprising selecting said motor vehicles for task execution based on said motor vehicle task execution time.

14. The method of claim 1 further comprising selecting said motor vehicles for task execution based on monitoring weather conditions.

15. The method of claim 1 further comprising execution of interrelated distributed tasks based on dates or times of the occurrence of predetermined events.

16. The method of claim 15 wherein predetermined events comprise the completion of other of said control programs.

17. The method of claim 1 , wherein selection of a particular task for execution from a queue of waiting tasks is made based on artificial intelligence evaluation of each such task importance in minimizing the total execution time for all interrelated tasks defined in said control program.

18. The method of claim 1 wherein said interrelated distributed task input and output object workflows comprise material flows between and among said tasks.

19. The method of claim 1 wherein said interrelated distributed task control programs comprise artificial intelligence expert system defined ranges of said potentially dynamically changing task execution agent parameters with expert system decisions based at least in part on parameter memberships in defined ranges.

20. The method of claim 1 comprising multiple interrelated distributed task control programs for independent, sequential, or parallel execution depending on said interrelated distributed task control program requirements.

Assignees

• Pedersen Robert D

Inventors

• Pedersen Robert D

Classifications

• G06F9/5027

  the resource being a machine, e.g. CPUs, Servers, Terminals · CPC title

• H04L67/10 Primary

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• G06F9/4843

  by program, e.g. task dispatcher, supervisor, operating system · CPC title

• G06N5/02 Primary

  Knowledge representation; Symbolic representation · CPC title