Patent Application
20210389080
The present invention relates, generally, to the field of firearms and, more particularly, to sensor systems used in connection with rifles and other such firearms.
Recent years have seen a number of significant advances in the field of firearm technology, driven primarily by improvements in the speed, size, and cost of computer hardware and software. Such advances relate not only to the firearms themselves, but also to peripheral systems such as weather meters, smart-scopes, electronic target systems, shooting chronographs, and other such external systems.
Despite the availability of shooting range data, currently known firearm intelligence systems are unsatisfactory in a number of respects. For example, prior art systems do not provide an easy way to acquire a wide array of information regarding the state of a firearm before, during, and after firing. Furthermore, known systems are not able to provide convenient methods for acquisition, integration, and data fusion of disparate streams of firearm related data.
Rifle intelligence systems and methods are therefore needed that overcome these and other limitations of the prior art.
Various embodiments of the present invention relate to systems and methods for, inter alia: i) a sensor module including an enclosure configured to be removably secured to a firearm (e.g., the stock of the firearm), a processor, and a plurality of sensors disposed within the module enclosure for generating shot attribute data associated with operation of the firearm, wherein the shot attribute data is wirelessly transmitted to a mobile computing device for further processing and visualization; ii) a rifle intelligence system incorporating a sensor module as above that is configured to communicate with one or more peripheral systems, such as weather meters, scopes, electronic target systems, shooting chronographs, or the like; iii) a rifle intelligence system as above in which the peripheral systems are configured to communicate directly with the mobile computing device; and iv) a distributed rifle intelligence system as described above in which the shot attribute data is further processed and stored within a cloud computing environment for access by subscribers.
The present invention will hereinafter be described in conjunction with the appended drawing figures, wherein like numerals denote like elements, and:
The present subject matter relates to improved rifle intelligence systems and methods. Specifically, a sensor module mounted to a firearm and paired with a mobile device is able to gather and display a wide range of useful information, such as shot detection and counting, shot mapping, orientation (heading, cant, and inclination), barrel temperature, environmental and weather data, recoil measurements, and rifle lifespan/maintenance metrics. In that regard, the following detailed description is merely exemplary in nature and is not intended to limit the inventions or the application and uses of the inventions described herein. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description. In the interest of brevity, conventional techniques and components related to the firing, design, and operation of firearms, the operation of accelerometers and other dynamic sensors, the nature of machine learning systems, and the operation of data communication protocols may not be described in detail herein. Furthermore, the term “rifle” is used herein without loss of generality. That is, the present invention is not limited to rifles or other long guns, and may be adapted for use with a wide variety of firearms and weapons, ranging from various types of bows used in archery (e.g., recurve bows, compound bows, and the like), to large military weapons.
Referring first to the conceptual block diagram shown in
Computing device 120 may be a desktop computer, stand-alone server, smartphone, a tablet computer, a laptop, a smart-watch, or any other device that, as described in further detail below, receives, processes, and, in some cases, displays (in conjunction with other available data) the shot attribute data received from sensor module 150. In addition to displaying information, computing device 120 and an optional associated application user interface (UI) 122 may also be used to enter information regarding the firearm, such as firearm model, type of ammunition used, etc. Computing device 120 may also be used to register the module to a particular individual, enter user preferences, and search/filter shot data based on parameters (date, time, location, stock-type, ammo-type). Computing device 120 may also be used to provide updates relevant to the user's activities, such as hunting registration deadlines, the location of nearby shooting ranges, the location of land closed due to wildfires, or the like. The software of the present system may also interact with other software on device 120—e.g., to allow voice commands, text-to-voice announcements, etc.
In some embodiments, computing device 120 is an integrated display (e.g., a heads-up-device, or “HUD”) that is suitably fixed to firearm 110 so that it can be easily accessed and viewed during a shooting session.
With continued reference to
A remote server 190 may be communicatively coupled to mobile device 120 (and/or directly to sensor module 150) via network 125 (e.g., the Internet) for receiving and processing the shot attribute data—e.g., via database 195 and data analysis module 192. Subscribers 180 (e.g., firearm manufacturers 181, ammunition manufacturers 182, firearm owners, and other interested parties) may be provided suitable credentials allowing access to a portion of the data housed within database 195. Such data may be anonymized, pseudonymized, or otherwise processed (e.g., via differential security techniques) to remove any information that might allow a threat-actor to determine the identity of individuals associated with the shot attribute data.
Furthermore, information from various third-party data sources or APIs 170 may be retrieved and combined with the shot attribute data and peripheral data. Such third-party data sources may include weather APIs, ammunition databases, firearm databases, map databases (e.g., Google Maps), or the like. This data may be available to the device itself (i.e., using the native maps and weather apps on device 120), or may be requested by server 190.
Regardless of the various data sources used, the results of the analysis are suitably provided to the user in a convenient form using an easy-to-use graphical user interface (“UI”) 122—e.g., an application running on mobile device 120. As described in further detail below, UI 122 can be configured to provide information regarding an individual shot taken during a shooting session (e.g., cant, attitude, and general orientation, ambient temperature, wind speed, geographical location, ammunition type) as well as cumulative statistics and prediction models (e.g., how long before firearm 110 requires maintenance, etc.).
While
Server system 190 may itself be part of a larger network, such as a social network of like-minded gun owners who can compare their shot data (e.g., via a leaderboard) and otherwise interact on an associated social network platform. In such cases, gun-related advertisements (which may not be welcome on other social networking sites) may be presented to the user (on an opt-in basis) such that the ads relate to their use of the module 150 (e.g., gun types, ammunition, firing range locations, etc.)
In some embodiment, server system 190 is coupled to a distribution system that monitors the flow of arms and/or ammunition. For example, a scanning system may be provided for scanning and tracking ammunition boxes. This allows an entity to identify the type of ammo used, which in turn enables that entity to deliver ammunition attributes to the user. The system may also count the scanned ammunition as it is received, then count it as it goes out (or gets shot). This allows the entity to suggest and facilitate purchases of ammunition once a user has reached a minimum threshold, which may be user-configurable.
Referring now to
A wide variety of sensors 200 may be incorporated into module 150. In the illustrated embodiment, for example, module 150 includes an inertial measurement unit (IMU) 201 for measuring specific force (i.e., acceleration), angular rate, and orientation of module 150 and/or a discrete accelerometer 202. Regardless of which sensor is used, module 150 is preferably configured such that one axis is aligned with bore axis 114 (intersecting muzzle 113). In this way, the acceleration parallel to bore axis 114 during a shot can be recorded. Sensor module 150 may also include a temperature sensor 203 (e.g., an infrared thermal sensor, thermocouple, or the like) for measuring barrel temperature, a microphone or other audio sensor 204 for recording the sound profile during a shot. Other possible sensors 200 include on-board weather sensors (humidity, barometric pressure), gesture or proximity sensors (for buttonless interactions or knowing when a user is looking through the scope), ambient light sensors for determining overall light conditions, including for example the sun's position during a shot. Controller 210 is generally configured to run software stored within storage component 220, as is known in the art. The software (which may be implemented using any suitable language) is designed to perform the functions described herein, such as acquiring the sensor data from one or more of the sensors 200, processing that data, transmitting the data via a wired or wireless interface 250, and interacting with UI components 240. Controller 210 may provide a range of additional functionality, such as calibration, inactivity time-out, remote shutdown, etc.
Sensor module 350, in this example, includes a body portion 351 (which will generally be mounted topmost and adjacent to the barrel when installed), and a base portion 352. As described in further detail below, body portion 351 and base portion 352 can be removably attached to each other in such a way that they effectively “clamp” on to a properly configured opening in a stock. As shown in
Referring to
As shown, when body portion 351 and base portion 352 are secured together via fasteners 371, 372, the resulting structure has a notch-shaped perimeter 353 that can be secured to a suitably configured opening in a rifle stock.
Referring to
The shot attribute data as well as any analytics based on that data may be presented to the user in a variety of ways.
Screen 601 also displays, in the middle region, various categories of information. For example,
In that regard,
Analysis module 192 and/or any of the various applications within mobile device 120 may be implemented using one or more machine learning models. As a preliminary matter, the phrase “machine learning” model is used without loss of generality to refer to any result of an analysis method that is designed to produce some form of prediction, such as predicting the state of a response variable, clustering variables (e.g., shot data), determining association rules, and performing anomaly detection (e.g., determining whether rifle 110 requires maintenance). Thus, for example, the term “machine learning” refers to models that undergo supervised, unsupervised, semi-supervised, and/or reinforcement learning. Such models may perform classification (e.g., binary or multiclass classification), regression, clustering, dimensionality reduction, and/or such tasks. Examples of such models include, without limitation, artificial neural networks (ANN) (such as a recurrent neural networks (RNN) and convolutional neural network (CNN)), decision tree models (such as classification and regression trees (CART)), ensemble learning models (such as boosting, bootstrapped aggregation, gradient boosting machines, and random forests), Bayesian network models (e.g., naive Bayes), principal component analysis (PCA), support vector machines (SVM), clustering models (such as K-nearest-neighbor, K-means, expectation maximization, hierarchical clustering, etc.), and linear discriminant analysis models.
In addition, the various components of
A variety of symmetrical and/or asymmetrical encryption schemes and standards may be employed to securely handle rifle intelligence data at rest (e.g., in database 195) and in motion (e.g., when being transferred between the various modules illustrated in
In summary, the present subject matter relates to various systems and methods for gathering and processing data associated with the operation of a firearm. In accordance with one embodiment, a sensor module for a rifle intelligence system includes an enclosure configured to be removably secured to a firearm, a processor disposed within the module enclosure, and a plurality of sensors disposed within the module enclosure. The plurality of sensors is communicatively coupled to the processor and are configured to generate shot attribute data associated with operation of the firearm and to wirelessly transmit the shot attribute data to a mobile computing device.
In one embodiment, the shot attribute data includes at least acceleration of the firearm along a bore axis and a temperature measurement of the barrel of the firearm. In others, the shot attribute data further includes the orientation of the barrel of the firearm and/or an audio signal associated with the firearm. In one embodiment, the temperature measurement is produced via an infrared thermal sensor adjacent to the barrel of the firearm.
In one embodiment, the processor is configured to transmit the shot attribute data to the mobile computing device a predetermined time after the firearm is fired.
In one embodiment, the enclosure is configured to be clamped to the stock of the firearm.
One embodiment further includes an interface configured to communicate with a plurality of peripheral systems, the peripheral systems selected from the group consisting of a weather meter, a scope mounted on the firearm, an electronic target system downrange of the firearm, and a shooting chronograph.
In one embodiment, at least a portion of the shot attribute data is wirelessly transmitted to the mobile computing device a predetermined time after the firearm is fired.
In one embodiment, a sensor module includes: an enclosure configured to be removably secured to a stock of a firearm; a processor disposed within the module enclosure; a plurality of sensors disposed within the module enclosure and communicatively coupled to the processor, the plurality of sensors configured to generate shot attribute data associated with operation of the firearm and to wirelessly transmit the shot attribute data to a mobile computing device; wherein the shot attribute data includes at least acceleration of the firearm along a bore axis, an infrared temperature measurement of the barrel of the firearm, an audio signal associated with the firearm, and orientation information associated with the firearm.
Rifle intelligence systems of the present disclosure may be described in terms of functional and/or logical block components and various processing steps (e.g.,
In addition, those skilled in the art will appreciate that embodiments of the present disclosure may be practiced in conjunction with any number of systems, and that the systems described herein are merely exemplary embodiments of the present disclosure. Further, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and/or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in an embodiment of the present disclosure.
As used herein, the terms “module” or “controller” refer to any hardware, software, firmware, electronic control component, processing logic, and/or processor device, individually or in any combination, including without limitation: application specific integrated circuits (ASICs), field-programmable gate-arrays (FPGAs), dedicated neural network devices (e.g., Google Tensor Processing Units), electronic circuits, processors (shared, dedicated, or group) configured to execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
As used herein, the word “exemplary” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other implementations, nor is it intended to be construed as a model that must be literally duplicated.
While the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing various embodiments of the invention, it should be appreciated that the particular embodiments described above are only examples, and are not intended to limit the scope, applicability, or configuration of the invention in any way. To the contrary, various changes may be made in the function and arrangement of elements described without departing from the scope of the invention.
