Unmanned aerial vehicle-based system for livestock parasite amelioration

• US 9,943,387 B2
• Filed: 06/29/2016
• Issued: 04/17/2018
• Est. Priority Date: 06/29/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Fobi, Simone, Pickover, Clifford A., Weldemariam, Komminist Sisai
• Primary Examiner(s): Cass, Jean Paul
• Application Number:
  US15/197,310
• Publication Number:
  US 20180000575A1
• Time in Patent Office: 657 Days
• CPC Class Codes: A01K 11/006 Automatic identification systems for animals, e.g. electronic devices, transponders for animals identification systems for access to feeding pens A01K1/0209; ear tags with electronic identification means A01K11/004
• CPC Class Codes: A61B 90/36 Image-producing devices or illumination devices not otherwise provided for
• CPC Class Codes: A61D 7/00 Devices or methods for introducing solid, liquid, or gaseous remedies or other materials into or onto the bodies of animals for reproduction or fertilisation A61D19/00 ; devices for implanting pellets, radon seeds or the like A61M37/0069
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2101/45 for releasing liquids or powders in-flight, e.g. crop-dusting
• CPC Class Codes: B64U 2101/55 for life-saving or rescue operations; for medical use
• CPC Class Codes: B64U 2201/20 Remote controls

Abstract

Parasites are detected and ameliorative actions taken using unmanned aerial vehicles equipped with sensors and equipment for dispensing treatment materials. Physical characteristic data obtained by the sensors is supplemented using a risk management module that increases the confidence level that the diagnosis of a particular parasite on an animal is correct. The risk management module may further be used to assess additional factors, such as the potential harm in applying a selected treatment, in the decision of whether or not to take ameliorative action.

Claims

1. A method for addressing potential parasite infestations, comprising:

obtaining a first unmanned aerial vehicle including one or more sensors for detecting physical characteristics of an animal and/or parasites afflicting the animal;

launching the first unmanned aerial vehicle;

locating the first unmanned aerial vehicle in proximity to an animal;

obtaining physical characteristic data by sensing one or more physical characteristics of the animal and/or a parasite using the one or more sensors;

accessing a risk management module configured for assessing a plurality of factors that contribute to parasite infestation of animals;

assessing the plurality of factors that contribute to parasite infestation using the risk management module in combination with the physical characteristic data to identify a particular parasite, and

based on the assessed plurality of factors and the physical characteristic data, causing an ameliorative action addressing a parasitic infection of the animal by the particular parasite to be administered by one or more unmanned aerial vehicles,

wherein the one or more sensors include a visual image sensor,

wherein the risk management module is further configured to assess potential harm of one or more parasites to the animal, and wherein causing the ameliorative action is further based on the potential harm to the animal by the particular parasite,

wherein the risk management module is further configured to assess epidemic risk of one or more parasites to the animal, and wherein causing the ameliorative action is further based on the epidemic risk.

2. The method of claim 1, wherein the one or more sensors include an acoustic sensor.

3. The method of claim 1, wherein the plurality of factors include animal presence in a risk area and weather.

4. The method of claim 1, further including causing the first unmanned aerial vehicle to cause the ameliorative action.

5. The method of claim 1, wherein locating the first unmanned aerial vehicle in proximity to an animal further includes landing the first unmanned aerial vehicle on the animal.

6. A method for addressing potential parasite infestations, comprising:

electronically identifying an animal by an RFID transponder;

obtaining a first unmanned aerial vehicle including one or more sensors for detecting physical characteristics of the animal and/or parasites afflicting the animal;

launching the first unmanned aerial vehicle;

causing the first unmanned aerial vehicle to move into proximity with the animal based on the electronic identification of the animal by the first unmanned aerial vehicle;

obtaining physical characteristic data by sensing one or more physical characteristics of the animal and/or a parasite using the one or more sensors;

accessing a risk management module configured for assessing a plurality of factors that contribute to parasite infestation of animals;

assessing the plurality of factors that contribute to parasite infestation using the risk management module in combination with the physical characteristic data to identify a particular parasite, and

based on the assessed plurality of factors and the physical characteristic data, causing an ameliorative action addressing a parasitic infection of the animal by the particular parasite to be administered by one or more unmanned aerial vehicles.

7. A method for addressing potential parasite infestations, comprising:

affixing one or more parasite detectors and a transmitter to an animal, the transmitter being configured for transmitting signals responsive to input from the one or more parasite detectors;

obtaining a first unmanned aerial vehicle including one or more sensors for detecting physical characteristics of the animal and/or parasites afflicting the animal;

launching the first unmanned aerial vehicle, wherein launching the first unmanned aerial vehicle is responsive to signals from the transmitter;

locating the first unmanned aerial vehicle in proximity to the animal;

obtaining physical characteristic data by sensing one or more physical characteristics of the animal and/or a parasite using the one or more sensors;

accessing a risk management module configured for assessing a plurality of factors that contribute to parasite infestation of animals;

assessing the plurality of factors that contribute to parasite infestation using the risk management module in combination with the physical characteristic data to identify a particular parasite, and

based on the assessed plurality of factors and the physical characteristic data, causing an ameliorative action addressing a parasitic infection of the animal by the particular parasite to be administered by one or more unmanned aerial vehicles.

8. A system for detecting parasites on animals and providing ameliorative action for addressing detected parasites, comprising:

one or more parasite detectors worn by an animal;

a transmitter worn by the animal, connected in communication with the parasite detectors, and configured for transmitting signals responsive to input from the one or more parasite detectors;

a first unmanned aerial vehicle including one or more sensors for detecting physical characteristics of the animal and/or parasites afflicting the animal;

a risk management module configured for assessing a plurality of factors that contribute to parasite infestation of animals;

a processor configured for processing outputs from the one or more sensors and the risk management module and generating a parasite treatment decision output based on the outputs from the sensors and risk management module, the processor being configured for processing the signals from the transmitter, launching the first unmanned aerial vehicle in response to the signals from the transmitter, and generating the parasite treatment decision output based in part on the signals from the transmitter, and

one or more additional unmanned aerial vehicles configured for taking parasite-ameliorating action with respect to the animal.

9. The system of claim 8, wherein the one or more unmanned aerial vehicles are further configured to dispense parasite-ameliorating material in response to the treatment decision output generated by the processor.

10. The system of claim 9, wherein the one or more unmanned aerial vehicles include the first unmanned aerial vehicle.

11. The system of claim 10, wherein the one or more sensors include a visual sensor for obtaining digital images.

12. The system of claim of claim 8, wherein the plurality of factors include animal presence in a risk area and weather.

13. The system of claim 8, wherein the one or more sensors include a visual sensor for obtaining digital images.

14. The system of claim 13, wherein the risk management module is further configured for assessing potential harm by a diagnosed parasite to the animal and generating the parasite treatment decision output based in part on the assessed potential harm by the diagnosed parasite.

15. The system of claim 13, wherein the processor is further configured to process outputs from the one or more sensors using a neural network configured to identify parasites.

16. The system of claim 8, wherein the first unmanned aerial vehicle includes the risk management module and the processor and is further configured to dispense parasite-ameliorating material in response to the treatment decision output generated by the processor.