Industrial livestock management leveraging digital twin computing
View Patent ↗An approach for maintaining industrial livestock infrastructure is disclosed. The approach utilizes digital twin computing to create a digital copy of biological and non-biological assets of a livestock production unit/facility (e.g., aquaculture, sericulture, dairy industry, meat industry, etc.) to improve the efficiency and reduce cost associated with the production of livestock. The usage of digital twins removes fundamental constraints concerning place, time, and human observation. Instead of control based on direct observation of physical objects, which requires physical proximity, digital twins enable remote control of livestock operations coupled with IoT sensors. This allows for the decoupling of physical flows from information aspects of farm operations.
1. A computer-implemented method for maintaining aquaculture infrastructure, the computer-implemented method comprising:
receiving historical data associated with a aquaculture infrastructure;
generating a digital twin copy of the aquaculture infrastructure based on the received-historical data;
simulating, by using AI (artificial intelligence) technology, one or more aquaculture scenarios associated with the digital twin copy;
generating aquaculture result data based on simulating the one or more aquaculture scenarios;
analyzing the aquaculture result data;
generating authenticity tracking for harvesting from the aquaculture infrastructure based on blockchain technology;
creating an action plan based on analysis; and
outputting the action plan.
2. The computer-implemented method of claim 1 , wherein the received historical data further comprises of the aquaculture infrastructure data, aquaculture farming device and IoT sensors.
3. The computer-implemented method of claim 1 , simulating the one or more aquaculture scenarios further comprises:
creating the one or more livestock scenarios based on the digital twin copy of the aquaculture infrastructure, the received historical data and real-time IOT data.
4. The computer-implemented method of claim 1 , wherein the one or more aquaculture scenarios further comprises of, reducing aquaculture risk, and determining optimal condition for aquaculture farming.
5. The computer-implemented method of claim 1 , wherein the aquaculture result data further comprises of real-time status of the aquaculture infrastructure.
6. The computer-implemented method of claim 1 , wherein the action plan further comprises of recommend adjust food source composition and recommend spraying and maintaining a clean the areas of aquaculture.
7. The computer-implemented method of claim 1 , wherein outputting the action plan further comprises:
sending a farming device to clean the aquaculture infrastructure.
8. A computer-implemented method for managing products derived from livestock, the computer-implemented method comprising:
receiving data associated with a livestock infrastructure;
generating a digital twin copy of the livestock infrastructure based on the received data;
simulating, by using AI (artificial intelligence) technology, one or more livestock scenarios on the digital twin copy, wherein the one or more livestock scenarios are associated with the products derived from the livestock;
generating livestock products result data based on simulating the one or more livestock scenarios;
analyzing the livestock products result data;
generating authenticity tracking for the products derived from the livestock by using blockchain technology;
creating an action plan based on analysis of the livestock products result data; and
outputting the action plan.
9. The computer-implemented method of claim 8 , wherein the received data further comprises of the livestock infrastructure data, farming device and IoT sensors.
10. The computer-implemented method of claim 8 , wherein the product derived from the livestock comprises of, wool, fur/hide, eggs, honey and silk.
11. A computer-implemented method of claim 8 , wherein the one or more livestock scenarios further comprises of, determining how to increase yield, quality and variety of silks, determining how to increase yield, productivity and quality of honey, determining how to increase efficiency and quality for wool and fur/hide.
12. The computer-implemented method of claim 8 , wherein the authenticity tracking for the products derived from the livestock includes determining the authenticity of lambs wool, merino wool, Shetland wool, mohair, cashmere and angora.
13. The computer-implemented method of claim 8 , wherein the action plan further comprises of recommendation of adjusting food source composition, such as flower and vegetation for bees to vary honey production and mulberry leaves, silkworm chow for silkworm to vary the silk production.
14. The computer-implemented method of claim 8 , wherein the authenticity tracking for the products derived from the livestock includes determining the authenticity of camel hair, qiviut, alpaca and vicuna; and
activate a smart UV laser/light to de-contaminate living and eating quarter of livestock.
15. A computer system for maintaining aquaculture infrastructure, the computer system comprising:
one or more computer processors;
one or more computer readable storage media;
program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising:
program instructions to receive historical data associated with a aquaculture infrastructure;
program instructions to generate a digital twin copy of the aquaculture infrastructure based on the received historical data;
program instructions to simulate, by using AI (artificial intelligence) technology, one or more aquaculture scenarios associated with the digital twin copy;
program instructions to generate aquaculture result data based on simulating the one or more aquaculture scenarios;
program instructions to analyze the aquaculture result data;
program instructions to generate authenticity tracking for harvesting from the aquaculture infrastructure based on blockchain technology;
program instructions to create an action plan based on analysis; and
program instructions to output the action plan.
16. The computer system of claim 15 , wherein received historical data further comprises of the aquaculture infrastructure data, aquaculture farming device and IoT sensors.
17. The computer system of claim 15 , wherein the one or more aquaculture scenarios further comprises of, reducing aquaculture risk, and determining optimal condition for aquaculture farming.
18. The computer system of claim 15 , wherein the aquaculture result data further comprises of real-time status of the aquaculture infrastructure.
19. The computer system of claim 15 , wherein the action plan further comprises of recommend adjust food source composition and recommend spraying and maintaining a clean the areas of aquaculture.
20. The computer system of claim 15 , wherein outputting the action plan further comprises:
program instructions to send a farming device to clean the aquaculture infrastructure.