# US 2023/0276151 A1 · Personal protective equipment (ppe) with analytical stream processing for safety event detection > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0276151 A1 - Document ID: US20230276151A1 - Status: Published application - Kind: A1 - Application number: 18/312,736 - Filed: 2023-05-05 - Published: 2023-08-31 - Earliest claimed: 2016-06-23 - Assignees: 3M Innovative Properties Company - Applicants: 3M Innovative Properties Company - Inventors: Steven T. Awiszus; Eric C. Lobner; Michael G. Wurm; Kiran S. Kanukurthy; Jia Hu; Matthew J. Blackford; Keith G. Mattson; Ronald D. Jesme; Nathan J. Anderson - Web page: https://patentgrep.com/patent/US20230276151A1 ## CPC - H04Q 9/00: Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom - A61F 9/06: Masks, shields or hoods for welders - A62B 9/00: Component parts for respiratory or breathing apparatus (A62B19/00, A62B21/00, A62B23/00 take precedence) - A62B 18/00: Breathing masks or helmets, e.g. affording protection against chemical agents or for use at high altitudes {or incorporating a pump or compressor for reducing the inhalation effort}(A62B17/00 takes precedence; anaesthetic masks A61M16/06) - A62B 27/00: Methods or devices for testing respiratory or breathing apparatus {for high altitudes}(apparatus for testing gastightness in general G01M) - A62B 99/00: Subject matter not provided for in other groups of this subclass - G06F 16/24568: {Data stream processing; Continuous queries} - H04Q: SELECTING (switches, relays, selectors H01H; wireless communication networks H04W) - A61F: FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS (dental prosthetics A61C) - A62B: DEVICES, APPARATUS OR METHODS FOR LIFE-SAVING (valves specially adapted for medical use A61M39/00; life-saving devices, apparatus or methods specially adapted for use in water B63C9/00; divers' equipment B63C11/00; specially adopted for use with aircraft, e.g. parachutes, ejector seats, {B64D17/00, B64D25/10}; rescue devices peculiar to mining E21F11/00) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract In some examples, a system includes an article of personal protective equipment (PPE) having at least one sensor configured to generate a stream of usage data; and an analytical stream processing component comprising: a communication component that receives the stream of usage data; a memory configured to store at least a portion of the stream of usage data and at least one model for detecting a safety event signature, wherein the at least one model is trained based as least in part on a set of usage data generated by one or more other articles of PPE of a same type as the article of PPE; and one or more computer processors configured to: detect the safety event signature in the stream of usage data based on processing the stream of usage data with the model, and generate an output in response to detecting the safety event signature. ## Claims ### Claim 1 A system comprising: an article of personal protective equipment (PPE) including at least a self-contained breathing apparatus and having at least one sensor configured to generate usage data, the at least one sensor being of a type selected from the following group of sensors: extension sensor, tension sensor, accelerometer, location sensor, position sensor, and altimeter; a communication component that receives the usage data from the at least one sensor of the article of PPE; a memory configured to store at least a portion of the usage data and at least one model for detecting a safety event signature indicative of an occurrence of a safety event, wherein the at least one model is based at least in part on a set of usage data generated, prior to receiving the usage data from the at least one sensor, by one or more other articles of PPE of a same type as the article of PPE; and one or more computer processors configured to: detect the safety event signature indicative of the occurrence of the safety event in the usage data based on processing the usage data with the model, and perform at least one operation in response to detecting the safety event signature. ### Claim 2 (depends on 1) The system of claim 1, wherein the one or more computer processors: select a training set comprising a set of training instances, each training instance comprising an association between respective usage data over a defined time duration and a respective safety event, wherein the respective usage data comprise one or more metrics that characterize at least one of a user, a work environment, or one or more articles of PPE; and for each training instance in the training set, modify, based on particular usage data over the defined time duration and a particular safety event of the training instance, the model to change a likelihood predicted by the model for the particular safety event signature associated with the particular safety event in response to subsequent usage data over the defined time duration applied to the model. ### Claim 3 (depends on 2) The system of claim 2, wherein one or more training instances of the set of training instances are generated from use of one or more articles of PPE after the one or more computer processors detect the safety event signature. ### Claim 4 (depends on 1) The system of claim 1, wherein the safety event signature comprises at least one of an anomaly in the usage data from the at least one sensor, a pattern in the usage data from the at least one sensor, a particular set of occurrences of particular events over a defined period of time, a particular set of types of particular events over a defined period of time, a particular set of magnitudes of particular events over a defined period of time, or a value that satisfies a threshold. ### Claim 5 (depends on 1) The system of claim 1, wherein the safety event signature is mapped to a safety event, wherein the safety event is associated with at least one of a worker, the article of PPE, an article of personal protective equipment (PPE) other than the article of PPE, or a work environment. ### Claim 6 (depends on 1) The system of claim 1, wherein to perform the at least one operation, the one or more computer processors send a notification to at least one of the article of PPE, a hub associated with a user and configured to communicate with the article of PPE, or a remote computing device. ### Claim 7 (depends on 1) The system of claim 1, wherein to perform the at least one operation, the one or more computer processors output for display a user interface that indicates the safety event in association with at least one of a user, work environment, or the article of PPE. ### Claim 8 (depends on 1) The system of claim 1, wherein the one or more computer processors are included in the article of FPPPE. ### Claim 9 A computing device comprising: one or more computer processors that receive usage data from at least one sensor of an article of personal protective equipment including at least at least a self-contained breathing apparatus (PPE), wherein the article of PPE has the at least one sensor configured to generate the stream of usage data, the at least one sensor being of a type selected from the following group of sensors: extension sensor, tension sensor, accelerometer, location sensor, position sensor, and altimeter; a memory configured to store at least a portion of the usage data and at least one model for detecting a safety event signature indicative of an occurrence of a safety event, wherein the at least one model is based at least in part on a set of usage data generated, prior to receiving the usage data from the at least one sensor, by one or more other articles of PPE of a same type as the article of PPE; and one or more computer processors configured to: detect the safety event signature indicative of the occurrence of the safety event in the usage data based on processing the usage data with the model, and perform at least one operation in response to detecting the safety event signature. ### Claim 10 (depends on 9) The computing device of claim 9, wherein the one or more computer processors are configured to: select a training set comprising a set of training instances, each training instance comprising an association between respective usage data over a defined time duration and a respective safety event, wherein the respective usage data comprise one or more metrics that characterize at least one of a user, a work environment, or one or more articles of PPE; and for each training instance in the training set, modify, based on particular usage data over the defined time duration and a particular safety event of the training instance, the model to change a likelihood predicted by the model for the particular safety event signature associated with the particular safety event in response to subsequent usage data over the defined time duration applied to the model. ### Claim 11 (depends on 10) The computing device of claim 10, wherein one or more training instances of the set of training instances are generated from use of one or more articles of PPE after the one or more computer processors detect the safety event signature. ### Claim 12 (depends on 9) The computing device of claim 9, wherein the safety event signature comprises at least one of an anomaly in the usage data from the at least one sensor, a pattern in the usage data from the at least one sensor, a particular set of occurrences of particular events over a defined period of time, a particular set of types of particular events over a defined period of time, a particular set of magnitudes of particular events over a defined period of time, or a value that satisfies a threshold. ### Claim 13 (depends on 9) The computing device of claim 9, wherein the safety event signature is mapped to a safety event, wherein the safety event is associated with at least one of a worker, the article of PPE, an article of personal protective equipment (PPE) other than the article of PPE, or a work environment. ### Claim 14 (depends on 9) The computing device of claim 9, wherein to perform the at least one operation, the one or more computer processors send a notification to at least one of the article of PPE, a hub associated with a user and configured to communicate with the article of PPE, or a remote computing device. ### Claim 15 (depends on 9) The computing device of claim 9, wherein to perform the at least one operation, the one or more computer processors output for display a user interface that indicates the safety event in association with at least one of a user, work environment, or the article of PPE. ### Claim 16 (depends on 9) The computing device of claim 9, wherein the one or more computer processors are included in the article of PPE. ### Claim 17 A non-transitory computer-readable storage medium encoded with instructions that, when executed, cause at least one processor of a computing device to: receive usage data from at least one sensor of an article of personal protective equipment that at least includes a self-contained breathing apparatus (PPE), wherein the article of PPE has the at least one sensor configured to generate the stream of usage data, the at least one sensor being of a type selected from the following group of sensors: extension sensor, tension sensor, accelerometer, location sensor, position sensor, and altimeter; store at least a portion of the usage data and at least one model for detecting a safety event signature indicative of an occurrence of a safety event, wherein the at least one model is based at least in part on a set of usage data generated, prior to receiving the usage data from the at least one sensor, by one or more other articles of PPE of a same type as the article of PPE; and detect the safety event signature indicative of the occurrence of the safety event in the usage data based on processing the usage data with the model, and perform at least one operation in response to detecting the safety event signature. ### Claim 18 (depends on 17) The non-transitory computer-readable storage medium of claim 17 encoded with instructions that, when executed, cause at least one processor of a computing device to: select a training set comprising a set of training instances, each training instance comprising an association between respective usage data over a defined time duration and a respective safety event, wherein the respective usage data comprise one or more metrics that characterize at least one of a user, a work environment, or one or more articles of PPE; and for each training instance in the training set, modify, based on particular usage data over the defined time duration and a particular safety event of the training instance, the model to change a likelihood predicted by the model for the particular safety event signature associated with the particular safety event in response to subsequent usage data over the defined time duration applied to the model. ### Claim 19 (depends on 18) The non-transitory computer-readable storage medium of claim 18, wherein one or more training instances of the set of training instances are generated from use of one or more articles of PPE after the one or more computer processors detect the safety event signature. ### Claim 20 (depends on 17) The non-transitory computer-readable storage medium of claim 17, wherein the safety event signature comprises at least one of an anomaly in the usage data from the at least one sensor, a pattern in the usage data from the at least one sensor, a particular set of occurrences of particular events over a defined period of time, a particular set of types of particular events over a defined period of time, a particular set of magnitudes of particular events over a defined period of time, or a value that satisfies a threshold.