System based on IOMT and operating method of the same

Patent metadata

Field	Value
Publication number	US-12411725-B2
Application number	US-202318466210-A
Country	US
Kind code	B2
Filing date	Sep 13, 2023
Priority date	Sep 30, 2022
Publication date	Sep 9, 2025
Grant date	Sep 9, 2025

Abstract

Proposed is a system based on the Internet of Media Things (IoMT). The system may include at least one first sensor configured to perform a predetermined function in a target space or region, and a second sensor based on at least one of video or audio. The system may also include a first analysis processor configured to generate first analysis data of a set mission within the target space or region based on first data sensed by the first sensor. The system may further include a second analysis processor configured to generate second analysis data for a set mission within the target space or region based on second data sensed by the second sensor. The system may further include storage configured to store the sensed first data and second data and the first and second analysis data based on the identifier.

First claim

What is claimed is:

1. A system based on an Internet of Media Things (IoMT), comprising:
at least one first sensor configured to sense at least one of temperature, humidity, or illuminance in a target space or region and obtain first data related to the at least one of temperature, humidity, or illuminance;
a second sensor configured to take images of crops in the target space or region, each of the images includes at least one of leaf, fruit, or flower bud of the crops and generate second data;
storage configured to store the first data and the second data; and
at least one analysis processor configured to:
package the first data and the second data by time units with identifiers for storing the first data and the second data as packaged first data and packaged second data,
process the second data of the crops to determine abnormality of the crops within the target space or region,
in response to determining the abnormality of the crops, process the first data to analyze cause of the abnormality of the crops, and
control, based on the cause of the abnormality of the crops in the target space or region, at least one of supplying liquid, draining liquid, heating, or increasing sunlight illumination,

in response to determining the abnormality, the at least one analysis processor configured to:
identify an identifier corresponding to the second data of the crops used for determining the abnormality,
retrieve the first data having the same identifier to analyze the cause of the abnormality,
generate a control signal for driving one or more actuators installed in the target space or region, based on the first data and the analyzed cause of the abnormality, and
drive the one or more actuators based on the control signal.

2. The system of claim 1 , wherein: the at least one analysis processor is configured to analyze whether the abnormality is present based on the first data.

3. The system of claim 1 , wherein:
the storage is configured to store the packaged first and second data by matching the packaged first and second data so that the packaged first and second data correspond to each other in a first time unit of the time units.

4. The system of claim 1 , wherein the at least one analysis processor is configured to:
sum and calculate a time corresponding to the first data determined to be abnormal with respect to a time range set by a user,
generate division time intervals by dividing the set time range by the summed and calculated time, and
set a division time interval in which a number of first data detected to be abnormal in each division time interval is a minimum detection number or more as a top-priority analysis target interval for analyzing cause of the abnormality.

5. The system of claim 1 , wherein the one or more actuators comprise a plurality of actuators respectively installed at a plurality of crop cultivation regions of the target space or region, and wherein the at least one analysis processor is configured to simultaneously drive all of the plurality of actuators installed the plurality of crop cultivation regions.

6. The system of claim 1 , wherein the one or more actuators comprise a plurality of actuators respectively installed at a plurality of crop cultivation regions of the target space or region, and wherein the at least one analysis processor is configured to individually drive the plurality of actuators.

7. A system for managing a smart farm based on the Internet of Media Things (IoMT), the system comprising:
at least one first sensor configured to sense at least one of temperature, humidity, or illuminance in a smart farm space obtain sensing data related to the at least one of temperature, humidity, or illuminance;
a second sensor configured to is configured to take images of crops in smart farm, each of the images includes at least one of leaf, fruit, or flower bud of the crops and generate image data;
storage configured to store the sensing data of the at least one first sensor and the image data of the second sensor based on a-file identifiers; and
at least one analysis processor configured to:
package the sensing data and the image data by time units with the file identifiers,
process the image data of the crops to determine abnormality of the crops within the smart farm,
in response to determining the abnormality of the crops, process the sensing data to analyze cause of the abnormality of the crops, and
control, based on the cause of the abnormality of the crops in the smart farm, at least one of supplying liquid, draining liquid, heating, or increasing sunlight illumination,

wherein, in response to determining the abnormality, the at least one analysis processor is configured to:
identify an identifier corresponding to the image data of the crops used for determining the abnormality,
retrieve the sensing data having the same identifier to analyze the cause of the abnormality,
generate a control signal for driving one or more actuators installed in the smart farm, based on the first data and the analyzed cause of the abnormality, and
drive the one or more actuators based on the control signal.

8. The system of claim 7 , wherein:
the second sensor is configured to obtain individual fruit images of all crops within the smart farm space as the image data, and
the at least one analysis processor is configured to:
calculate a maximum value and minimum value of ripening of fruits within the smart farm by inputting fruit images of all of the crops to a pre-trained artificial intelligence algorithm,
divide the fruit images for each ripening grade set based on the maximum value and the minimum value, and
determine that the ripening of a corresponding crop is abnormal when a fruit image having a predetermined ripening grade or less based on a relative or absolute criterion is present.

9. The system of claim 7 , wherein:
the second sensor is configured to obtain leaf images of all crops within the smart farm as the image data, and
the at least one analysis processor is configured to set an interested region for an individual leaf image based on a pre-trained artificial intelligence algorithm and detect whether a burnt leaf is present with respect to each crop or all of the crops by detecting an edge region of a leaf within the interested region.

10. The system of claim 9 , wherein the at least one analysis processor is configured to:
calculate a number of burnt leaves detected within an initial region set with respect to each crop,
calculate a burnt leaf average value for each crop based on the number of detected burnt leaves with respect to all of the crops, and
determine that a crop set as the initial region is abnormal when the number of burnt leaves within the initial region is equal to or greater than the burnt leaf average value for each crop.

11. The system of claim 9 , wherein the at least one analysis processor is configured to:
detect and set all crop regions based on the image data obtained by the second sensor,
add a region in which a burnt leaf detected based on each leaf image is present within all of the crop regions and define the region as a burnt leaf presence region, and
determine that a crop present in a corresponding region range is abnormal when the burnt leaf presence region within a preset region range based on each leaf image including the burnt leaf has a preset threshold value or more.

12. The system of claim 7 , wherein:
the second sensor is configured to obtain flower bud images of all crops within the smart farm space as the image data,
the at least one analysis processor is configured to:
calculate an average value of flower bud differentiation grades within

Assignees

• Korea Electronics Technology

Inventors

• Moon Jaewon
• Kum Seung Woo
• Oh Seungtaek
• Park Sung Joo

Classifications

• G05B2219/45106

  Used in agriculture, tree trimmer, pruner · CPC title

• G16Y10/05

  Agriculture · CPC title

• A01B79/02

  combined with other agricultural processing, e.g. fertilising, planting · CPC title

• G06F11/0709

  in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems · CPC title

• G06F11/079 Primary

  Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36) · CPC title