Patent Application
20250067533
Target shooting has always been a popular way to use firearms in a safe and controlled manner that allows for a person to analyze and hone their shooting skills. Target shooting can be done on a gun range or out in an open area. The problem with analyzing target shooting is that the feedback is either delayed, hard to judge as the accuracy of the shots and the shooter's actions, or both. In target shooting, there is usually an object that the shooter is aiming for, such as a paper, wood or metal target. The shooter has to retrieve the target after they are done with their target practice. This doesn't allow for instant feedback that would allow for a shooter to adjust their aim between shots based on the feedback as they won't know how well they shot until after they are done shooting multiple rounds.
One way to overcome this lack of feedback has been to use acoustics to trigger a monitoring system. While this is accurate to track a single shooter, it becomes an issue with shooting on a range where multiple people are shooting. The additional sounds of gunfire can quickly overwhelm an acoustic sensor as gunfire is loud and echos. Another way to trigger a monitoring system is to use a recoil sensor either on the firearm or on the person's body. The problem with this solution is that it either requires something that attaches to the firearm that could change the shooters aim, or they are too large and when attached to a person's body they can get in the way of the person's shooting, or be cumbersome to wear.
U.S. Pat. No. 10,663,259 discloses a gun monitoring system that tracks the motion of the firearm. While the patent discloses a sensor that attaches to a gun to sense motion, the system does not disclose measuring the recoil that happens when a firearm is fired. Instead the system measures the recoil anticipation which is the motion of the user's hand while holding the firearm before the firearm is fired. Recoil anticipation happens when an inexperienced person tries to fire a firearm, they jerk their hand before they shoot in anticipation of the expected recoil. This invention is meant for measuring the recoil of the firearm that occurs when the firearm is fired, which triggers the other sensor systems.
The overall scope of the invention is to provide a person with a system for accurately tracking and analyzing their shooting in real time. The system would include a recoil detection device that is small enough to be attached to a shooter's finger, but could also be placed on a wrist or arm, or even the firearm itself. The recoil detection device is small enough so that it wouldn't impact the shooters accuracy or be cumbersome to wear.
The recoil detection device contains an accelerometer, a gyroscope, and a magnetometer to detect when the shooter pulls the trigger and firearm discharges a bullet. While the device is small, it also needs to be rugged enough to withstand the recoil of the firearm, all types of weather conditions, and have enough battery life to last for an entire shooting session.
The recoil detection device contains wireless connectivity to connect it to a smartphone, tablet, computer, or any type of wireless computing device. This connectivity is used by the device to send and receive information to and from the computing device. The connectivity could also be used to communicate with other sensors, such as a video or still camera, and a timer device. When these devices are used in unison, they aggregate the information from the various sensors and provide the shooter with instant feedback as to their shooting performance including but not limited to target feedback, video/image feedback, timing information, wind speed, humidity, and temperature.
To protect the shooter's information the communication is encrypted between the sensor devices and the computing device. This prevents nearby shooters using the same system for interfering with the shooter's feedback. While it is preferable for all of the sensor devices to be used in unison, any number or combination of sensor devices could be used along with the recoil detector to give the shooter any feedback they require.
The recoil detection device would ideally be a 1.4″×1″ form factor, but any size, shape, or weight could be used as long as the device's size, shape, and weight do not interfere with the user's ability to shoot. The device is made of a hardened plastic that allows for the device to weather the repeated firings, snow, rain, sleet, hail, wind, heat, or any other extreme conditions that the user is likely to experience. The device would be low in weight, without sacrificing the functionality of the device.
The recoil detection device would include sensors that provide data to an onboard processor using an algorithm to detect when the user's fires a firearm while the device is attached. The algorithm uses the sensor data, that includes but isn't limited to, data from an accelerometer(s), a gyroscope(s), and a magnetometer(s) to detect shot waveforms and accurately detect when a firearm is shot. The movement detected by the sensors would be in three dimensions. The sensitivity of the device could be adjusted by the user's phone, using an app to adjust the device for different types of firearms and/or ammunition. The shot information is preferably sent from the device to a user's phone via a Bluetooth connection, but any type of connection could be used, including but not limited to. Wifi, an adhoc network, NFC. RFID, and a wired connection, The device includes an input that include, but is not limited to, a physical button, a switch, a touch screen, and a dial, for changing settings and/or manually triggering a shot detection start event.
The recoil detection device would process the sensor data and provide a shot detection every 50 milliseconds, which would allow for the user to fire the firearm repeatedly, but could be any length of time that is less than the intervals between firings. The device would be preferably be powered by a lithium ion battery with voltage regulation and status monitoring performed via a combination of hardware and software, but could be any type of battery that is used in portable devices. The communication between the phone and the device would be encrypted and the user's identify would be authenticated on the user's phone, to ensure that the user's privacy was preserved. While a phone has been used to describe the user device that collects the data from the recoil detection device, any type of computing device could be paired with the recoil detection device, including but not limited to a tablet, computer, laptop, desktop, watch, or any device able to collect and display information to a user. In one embodiment, the recoil detection device and the user device could be integrated in to a smart watch that can output information to the user, removing the requirement for multiple devices. The phone could be used to control settings of the recoil detection device via a user interface that is displayed via the app.
The accelerometer sensor could consist of three accelerometers for detecting linear acceleration forces. The gyroscope sensor could consist of three orthogonal gyroscopes for detecting angular rotational forces. The algorithm uses the data from the sensors for performing pattern recognition on the data to identify impulse waveforms amid background data to prevent false positives. The strap, band, clip, or any other type of connector used to attach the recoil detection device to the user would be adjustable to allow for use by every type of shooter. The device could also use an adjustable clip, band or threaded holes to allow for the device to be attached to and removed from any type of firearm. The device could be customized with different straps that are different colors, have images or patterns, or material so that the user could customize their device.
The shot tracking system uses all the information sent and received from/by the phone, recoil detection device, timer system, and the camera system to generate feedback for the user. This information could be aggregated by using AI or machine learning to learn the specifics of the user's shooting information and generate customized information to display to the user on the phone. The processing of the information could be performed locally on the phone or the phone could upload the information to a server to perform the processing, the information being sent from the server to the phone. The realtime feedback could be a numerical score using default scoring rules, customized rules inputted by the user, automatically generated by the phone, or any combination. The feedback could be sent to other user's phones that are using the same system to create a contest or leaderboard for all that are participating.
The camera system 201 would include a scope 203, with a lens or lenses, and a sensor 202. The sensor includes an eye piece that allows the user to aim the camera system at the target, but the camera system could also include an auto aiming feature where a motorized mount is used to hold the camera system, which would use image recognition to detect, focus, and aim at the target. The camera system uses edge detection, contour tracing, and shape matching for detecting when a bullet strikes the target. The phone could display new bullet strikes with a particular shape or color to differentiate them from the previous bullet strikes on the target. The camera system would also be able to determine when there is not a bullet strike, which would be outputted to the phone in the form of a miss alert and/or how far off target the bullet was from the target.
The shot timer system provides information indicating how long it takes the user to shoot. This information includes, but is not limited to, time to aim and shoot the firearm, time for the bullet to reach the target after the firearm was shot, the time it takes for the user to draw the weapon from a holster or other position, time between two or more shots, or any combination of these times. The feedback from the timer system would help a user work on their shooting speed, which combined with accuracy, would present to the user the most complete coaching information on the phone. The recoil system could use AI or Machine Learning to determine a pattern for the user's shooting style to enable the system to start the timer automatically when the user move's the firearm.
The shot tracking system provides the user with the ability to share the information on social network accounts, overlay data over the images, and connect the shooter to e-commerce sites to buy different firearms or accessories. The system could include a shooting coach feature that aggregates all the information from the various systems to provide the user with realtime adjustments to make to their stance, how the user holds the firearm, aim, and any other information that would help the user improve their shooting. Multiple camera systems could be used to capture multiple images of the target, including but not limited to, different angles in all three dimensions, an angle that shows the user, an angle that shows the user and the back of the target, angles that show the target from the sides, top or bottom. The shot tracking system could also use voice recognition software to allow for the user to control the system without taking their hand off of the firearm. The camera system could use any known and future type of image processing to enhance the images captured. The system could process the information locally or it could send and receive information from a cloud based system to reduce the processing requirements of the phone.
The recoil detection system could be used for personal shooting training, law enforcement or military training, teaching an inexperienced user how to shoot safely, or any other firearm related training. Information presented to the user on the phone could include, but is not limited to, ammunition tracking, video analysis, scenario based training, health warnings such as a warning about the user's hearing, maintenance reminders for the firearm, and in app purchases for adding software and/or hardware capabilities to the shot tracking system.
The devices mentioned above could be implemented using any type of processor architecture able to execute software including, but not limited to, x86, ENIAC, RISC, Pentium™, and Apple Silicon™. The software could be any type of code that is used to instruct a processor to perform instructions including, but not limited to, Python™, Java™, C+™, FORTRAN, and Assembly. The software could be stored on any type of non-transitory medium including, but not limited to, RAM, ROM, Flash Memory, Punch Cards, Plano Player Reels, Hard Drives, and physical servers.
