IP Library › Granted Patent US 12,329,146
Granted Patent B2
US 12,329,146 · App. 18/306,879 · Granted Jun 17, 2025

Pest repelling device

Inventors: Scott Connell (Jacksonville, FL); Raymond Connell (Merewether Heights, AU)
Assignee: Scopat Properties, LLC
A01M29/24F24F11/30G05B15/02G05D23/1927F24F2110/10F24F2110/40
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Quick Facts
Patent No.
US 12,329,146
App. No.
18/306,879
Granted
Jun 17, 2025
Kind
B2
Abstract

Apparatus and associated methods relate to a pest repelling magnetic field generating device (PRD) having a temperature sensor to detect the temperature of a solenoid coil during operation. The detected temperature to be used to ensure that the PRD operates within an ideal temperature range. Additionally, a fan is oriented within a housing of the PRD to force the flow of air from inside a housing of the PRD to outside a housing the PRD. In an illustrative example, the PRD may shut off if the temperature of the solenoid coil moves outside the ideal temperature range. By operating the PRD within an ideal temperature range, the service life of the PRD may be extended. Further, the fan may mitigate dust collection within the housing of the pest repelling magnetic field generating device.

Claims (30)

1. A pest control system, comprising:

a plurality of pest monitoring devices, each comprising a pest repelling magnetic field generating device, a pest detection device, and a pest trapping device, wherein the pest repelling magnetic field generating device comprises a fan oriented to force air to flow through at least 10 one aperture of the pest magnetic field generating device from an inside of the pest magnetic field generating device to the outside of the pest magnetic field generating device; and,

a computer system operably coupled to the plurality of pest monitoring devices and configured to remotely control the plurality of pest monitoring devices, the computer system comprising:

a processor; and,

a tangible memory storage device containing a program of instructions that, when executed by the processor, cause the processor to perform operations to remotely control one or more remotely connected pest monitoring device based on user status information and a pest activity profile, the operations comprising:

receive a remote communication signal from the plurality of pest monitoring devices;

retrieve an account standing associated with the plurality of pest monitoring devices;

if the account standing does not meet a predetermined criterion for operating the plurality of pest monitoring devices, then generate control signals to deactivate the plurality of pest monitoring devices; and,

if the account standing meets a predetermined criterion for operating the plurality of pest monitoring devices, then, based on a machine learning model, generate control signals to configure the plurality of pest monitoring devices, wherein the machine learning model is trained on a statistical model of pest activity, historical configurations of the plurality of pest monitoring devices, and a current configuration of the plurality of pest monitoring devices to generate an updated configuration of the plurality of pest monitoring devices, wherein the statistical model of pest activity is generated by processing raw data received from the pest detection device, such that the pest control system is configured to actively reduce pests.

2. The pest control system of claim 1 , wherein the operations further comprising generate and display a recommendations and report display based on the statistical model of pest activity.

3. The pest control system of claim 2 , wherein the recommendations and report comprises a heatmap of pest activities.

4. The pest control system of claim 2 , wherein the recommendations and report comprises a pest repelling score generated based on a placement configuration of the plurality of pest monitoring devices.

5. The pest control system of claim 1 , wherein the detection device comprises a night vision camera.

6. The pest control system of claim 5 , wherein the operations further comprising identify a type of pest detected based on data received from the night vision camera.

7. The pest control system of claim 1 , wherein the pest trapping device comprises a smart trap door, wherein the control signals comprise activating the sliding door to capture a target pest.

8. A computer system configured to remotely control a plurality of pest monitoring devices, the computer system comprising:

a processor; and,

a tangible memory storage device containing a program of instructions that, when executed by the processor, cause the processor to perform operations to remotely control one or more remotely connected pest monitoring device based on user status information and a pest activity profile, the operations comprising:

receive a remote communication signal from the plurality of pest monitoring devices;

retrieve an account standing associated with the plurality of pest monitoring devices;

if the account standing does not meet a predetermined criterion for operating the plurality of pest monitoring devices, then generate control signals to deactivate the plurality of pest monitoring devices; and, if the account standing meets a predetermined criterion for operating the plurality of pest monitoring devices, then, based on a machine learning model, generate control signals to configure the plurality of pest monitoring devices, wherein the machine learning model is trained on a statistical model of pest activity, historical configurations of the plurality of pest monitoring devices, and a current configuration of the plurality of pest monitoring devices to generate an updated configuration of the plurality of pest monitoring devices, such that the pest control system is configured to actively reduce pests.

9. The computer system of claim 8 , wherein the plurality of pest monitoring devices comprises a pest repelling magnetic field generating device, wherein the pest repelling magnetic field generating device comprises a fan oriented to force air to flow through at least one aperture of the pest magnetic field generating device from an inside of the pest magnetic field generating device to the outside of the pest magnetic field generating device.

10. The computer system of claim 9 , wherein the operations further comprise receive, via a temperature sensor of the pest repelling magnetic field generation device, status information concerning the temperature of a solenoid coil disposed within the pest magnetic field generating device.

11. The computer system of claim 8 , wherein the operations further comprising generate and display a recommendations and report display based on the statistical model of pest activity.

12. The computer system of claim 11 , wherein the recommendations and report comprises a heatmap of pest activities.

13. The computer system of claim 11 , wherein the recommendations and report comprises a pest repelling score generated based on a placement configuration of the plurality of pest monitoring devices.

14. The computer system of claim 8 , wherein the plurality of pest monitoring devices comprises a pest detection device, wherein the statistical model of pest activity is generated by processing raw data received from the detection device.

15. The computer system of claim 14 , wherein the pest detection device comprises a night vision camera.

16. The computer system of claim 15 , wherein the operations further comprising identify a type of pest detected based on data received from the night vision camera.

17. The computer system of claim 8 , wherein the pest trapping device comprises a smart trap door, wherein the control signals comprise activating the sliding door to capture a target pest.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2025
From: CONNELL, RAYMOND; WIROJWATANAKUL, WIRASACK; JINTANAWASON, SURASAK
To: PLUG IN PEST FREE AUSTRALIA
Reel/Frame 070957/0927 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2025
From: ISPYTRONICS PTY LTD
To: SCOPAT PROPERTIES, LLC
Reel/Frame 070958/0229 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2025
From: PLUG IN PEST FREE AUSTRALIA
To: ISPYTRONICS PTY LTD
Reel/Frame 071084/0924 →
Continuity (8)
Continuation 17161196 · Jan 28, 2021
Continuation 16736575 · Jan 7, 2020
Continuation 16128222 · Sep 11, 2018
Continuation 15011162 · Jan 29, 2016
Provisional Application 63477138 · Dec 23, 2022
Provisional Application 63370616 · Aug 5, 2022
Provisional Application 63364301 · May 6, 2022
Related Publication 20230404059A1 · Dec 21, 2023
References Cited (21)
US 4097838A · Fiala · 1978 [cited by applicant]
US 4178578A · Hall · 1979 [cited by applicant]
US 4215429A · Riach · 1980 [cited by applicant]
US 4338593A · Mills · 1982 [cited by applicant]
US 4414653A · Pettinger · 1983 [cited by applicant]
US 4802057A · Patterson et al. · 1989 [cited by applicant]
US 4870779A · Johnson et al. · 1989 [cited by applicant]
US 5473836A · Liu · 1995 [cited by applicant]
US 5930946A · Mah · 1999 [cited by applicant]
US 6111514A · Cossins et al. · 2000 [cited by applicant]
US 6208100B1 · Griesemer et al. · 2001 [cited by applicant]
US 6249417B1 · Pippen · 2001 [cited by applicant]
US 6400995B1 · Patterson et al. · 2002 [cited by applicant]
US 10077916B2 · Connell et al. · 2018 [cited by applicant]
US 10563881B2 · Connell · 2020 [cited by applicant]
US 20120263021A1 · Connell · 2012 [cited by applicant]
US 20170281822A1 · Becker et al. · 2017 [cited by applicant]
AU 664508B2 · 1995 [cited by applicant]
AU 2010306413A1 · 2012 [cited by applicant]
AU 2015200650A1 · 2016 [cited by applicant]
WO 2011044635A1 · 2011 [cited by applicant]