Patent Application
20240232766
This disclosure generally relates to monitoring systems. More specifically and without limitation, this disclosure relates to a monitoring system utilizing wearable devices to gather information indicative of work performed and/or work conditions.
Injuries at work are tremendously costly for both the corporation as well as the injured worker. As an example, it is estimated that yearly workers' compensation claims exceed 100 billion dollars, with the average claim in the United State amounting to over 100,000 dollars.
Most, if not all of these work-related injuries are avoidable. In view of the personal cost to the injured worker and the financial cost to the employer, a great amount of energy and effort has been placed on avoiding workplace injuries. Many employers have implemented various systems to avoid accidents ranging from common sense solutions to sophisticated systems, from establishing safety teams and safety managers to hiring third-party safety auditors, and everything in-between. However, despite these many efforts, avoidable injuries continue to occur at an alarming pace.
To better inform and address workplace injuries, some current systems utilize wearable devices to gather data to evaluate movement, physical exertion, biometric data, environmental, or other data relevant to health and/or safety of workers. It is desired to be able to receive data from wearable devices continuously to facilitate monitoring of workers throughout a work shift and facilitate early intervention when safety risks are detected and/or early response to accidents. It is also desirable to collect data for an entire work shift to facilitate analysis of worker data. However, in many workplace settings, workers may move around different areas of a workplace center and/or travel to various different locations in the field. Such movement can cause intermittent communication with wearable devices used to collect data.
Therefore, there is a need in the art to provide a device, system, and method of use for collecting, reporting and analyzing information relating to or indicative of work performed by workers and/or workplace conditions to better assess physicality of workers and risk posed to workers during a work shift.
Thus, it is a primary object of the disclosure to provide a wearable device, system, and method of use that improves upon the state of the art.
Another object of the disclosure is to provide a wearable device, system, and method of use that collects information about the work performed by workers and workplace conditions.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication to communicate data from wearable devices to a monitoring system.
Another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that ensures that all data is communicated to the monitoring system when communication is intermittent.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that utilizes multiple different networks.
Another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that utilizes infrastructure and ad hoc networks.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that adjusts the method of communication to fit the needs of each worker.
Another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that adjusts the method of communication based on the work schedule of each worker.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that is energy efficient.
Another object of the disclosure is to provide a wearable device, system, and method of use that utilizes an adaptive method of communication that facilitates communication from nearly any location.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that aggregates a great amount of information about the work performed by workers and workplace conditions.
Another object of the disclosure is to provide a wearable device, system, and method of use that eliminates bias in the collection of information about the work performed by workers and workplace conditions.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that eliminates the inconsistency in reporting information about the work performed by workers and workplace conditions.
Another object of the disclosure is to provide a wearable device, system, and method of use that utilizes collected information to assess physicality exhibited by workers during a work shift.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that utilizes collected information to assess safety risks faced during a work shift.
Another object of the disclosure is to provide a wearable device, system, and method of use that aggregates a great amount of information indicative of work performed by workers and workplace conditions to facilitate data analytics.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that is cost effective.
Another object of the disclosure is to provide a wearable device, system, and method of use that is safe to use.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that is easy to use.
Another object of the disclosure is to provide a wearable device, system, and method of use that is efficient to use.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that is durable.
Another object of the disclosure is to provide a wearable device, system, and method of use that is robust.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that can be used with a wide variety of manufacturing facilities.
Another object of the disclosure is to provide a wearable device, system, and method of use that is high quality.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that has a long useful life.
Another object of the disclosure is to provide a wearable device, system, and method of use that can be used with a wide variety of occupations.
Yet another object of the disclosure is to provide a wearable device, system, and method of use that provides high quality data.
Another object of the disclosure is to provide a wearable device, system, and method of use that provides data and information that can be relied upon.
These and countless other objects, features, or advantages of the present disclosure will become apparent from the specification, figures, and claims.
In one or more arrangements, a system and method for monitoring worker activity is presented. In one or more arrangements, the system includes a wearable device and a monitoring system. The wearable device is configured to be worn by a worker during a work shift. The wearable device communicates data collected from a plurality of sensors during the work shift to the monitoring system. The wearable device is configured to communicate data to the monitoring system using a plurality of communication methods.
In one or more arrangements, in a first communication method, the wearable device communicates over a WiFi network. In one or more arrangements, in a second communication method, the wearable device communicates over a mobile network via a mobile device. In one or more arrangements, in a third communication method, the wearable device communicates over an ad hoc wireless network formed by the wearable device and one or more additional wearable devices.
In one or more arrangements, the system includes a docking station. The docking station has a socket configured to receive and hold the wearable device. The docking station is configured to charge the wearable device when held within the socket. The docking station has a user interface for the worker to check out the wearable device. In one or more arrangements, when the worker checks out the wearable device, the docking station automatically configures communication settings on the wearable device for at least one communication method of the plurality of communication methods.
In one or more arrangements, the docking station and/or monitoring system is configured to automatically select a communication method for the wearable device to use when the worker checks out the wearable device. In one or more arrangements, the communication method is selected based on worker specific data stored in the docking station and/or monitoring system. In one or more arrangements, the communication method is selected based on a work schedule of the worker. Additionally or alternatively, in one or more arrangements, the wearable device is configured to dynamically select the method of communication during a work shift. In one or more arrangements, the wearable device is configured to dynamically select the method of communication based on sensor data gathered by the wearable device.
In one or more arrangements, wearable devices are configured to form an hoc wireless network of the plurality of wearable devices.
In one or more arrangements, the wearable devices are each configured to indicate a weight corresponding to the number of hops in the ad hoc wireless network to a base station 80. The wearable devices are each configured to detect a set of the plurality of wireless devices within range and select the wireless device of the set having the lowest weight for the device to communicate data to the monitoring system.
In the following detailed description of the embodiments, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the disclosure may be practiced. The embodiments of the present disclosure described below are not intended to be exhaustive or to limit the disclosure to the precise forms in the following detailed description. Rather, the embodiments are chosen and described so that others skilled in the art may appreciate and understand the principles and practices of the present disclosure. It will be understood by those skilled in the art that various changes in form and details may be made without departing from the principles and scope of the invention. It is intended to cover various modifications and similar arrangements and procedures, and the scope of the appended claims therefore should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements and procedures. For instance, although aspects and features may be illustrated in or described with reference to certain figures or embodiments, it will be appreciated that features from one figure or embodiment may be combined with features of another figure or embodiment even though the combination is not explicitly shown or explicitly described as a combination. In the depicted embodiments, like reference numbers refer to like elements throughout the various drawings.
It should be understood that any advantages and/or improvements discussed herein may not be provided by various disclosed embodiments, or implementations thereof. The contemplated embodiments are not so limited and should not be interpreted as being restricted to embodiments which provide such advantages or improvements. Similarly, it should be understood that various embodiments may not address all or any objects of the disclosure or objects of the invention that may be described herein. The contemplated embodiments are not so limited and should not be interpreted as being restricted to embodiments which address such objects of the disclosure or invention. Furthermore, although some disclosed embodiments may be described relative to specific materials, embodiments are not limited to the specific materials or apparatuses but only to their specific characteristics and capabilities and other materials and apparatuses can be substituted as is well understood by those skilled in the art in view of the present disclosure.
It is to be understood that the terms such as “left, right, top, bottom, front, back, side, height, length, width, upper, lower, interior, exterior, inner, outer, and the like as may be used herein, merely describe points of reference and do not limit the present invention to any particular orientation or configuration.
As used herein, “and/or” includes all combinations of one or more of the associated listed items, such that “A and/or B” includes “A but not B,” “B but not A,” and “A as well as B,” unless it is clearly indicated that only a single item, subgroup of items, or all items are present. The use of “etc.” is defined as “et cetera” and indicates the inclusion of all other elements belonging to the same group of the preceding items, in any “and/or” combination(s).
As used herein, the singular forms “a,” “an,” and “the” are intended to include both the singular and plural forms, unless the language explicitly indicates otherwise. Indefinite articles like “a” and “an” introduce or refer to any modified term, both previously-introduced and not, while definite articles like “the” refer to a same previously-introduced term; as such, it is understood that “a” or “an” modify items that are permitted to be previously-introduced or new, while definite articles modify an item that is the same as immediately previously presented. It will be further understood that the terms “comprises,” “comprising,” “includes,” and/or “including,” when used herein, specify the presence of stated features, characteristics, steps, operations, elements, and/or components, but do not themselves preclude the presence or addition of one or more other features, characteristics, steps, operations, elements, components, and/or groups thereof, unless expressly indicated otherwise. For example, if an embodiment of a system is described at comprising an article, it is understood the system is not limited to a single instance of the article unless expressly indicated otherwise, even if elsewhere another embodiment of the system is described as comprising a plurality of articles.
It will be understood that when an element is referred to as being “connected,” “coupled,” “mated,” “attached,” “fixed,” etc. to another element, it can be directly connected to the other element, and/or intervening elements may be present. In contrast, when an element is referred to as being “directly connected,” “directly coupled,” “directly engaged” etc. to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a like fashion (e.g., “between” versus “directly between,” “adjacent” versus “directly adjacent,” “engaged” versus “directly engaged,” etc.). Similarly, a term such as “operatively”, such as when used as “operatively connected” or “operatively engaged” is to be interpreted as connected or engaged, respectively, in any manner that facilitates operation, which may include being directly connected, indirectly connected, electronically connected, wirelessly connected or connected by any other manner, method or means that facilitates desired operation. Similarly, a term such as “communicatively connected” includes all variations of information exchange and routing between two electronic devices, including intermediary devices, networks, etc., connected wirelessly or not. Similarly, “connected” or other similar language particularly for electronic components is intended to mean connected by any means, either directly or indirectly, wired and/or wirelessly, such that electricity and/or information may be transmitted between the components.
It will be understood that, although the ordinal terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited to any order by these terms unless specifically stated as such. These terms are used only to distinguish one element from another; where there are “second” or higher ordinals, there merely must be a number of elements, without necessarily any difference or other relationship. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments or methods.
Similarly, the structures and operations discussed herein may occur out of the order described and/or noted in the figures. For example, two operations and/or figures shown in succession may in fact be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Similarly, individual operations within example methods described below may be executed repetitively, individually or sequentially, to provide looping or other series of operations aside from single operations described below. It should be presumed that any embodiment or method having features and functionality described below, in any workable combination, falls within the scope of example embodiments.
As used herein, various disclosed embodiments may be primarily described in the context of gathering information for assessment of physicality and safety risk of workers. However, the embodiments are not so limited. It is appreciated that the embodiments may be adapted for use in other applications which may be improved by the disclosed structures, arrangements and/or methods. The system is merely shown and described as being used in the context of gathering information for assessment of physicality and worker risk for ease of description and as one of countless examples.
With reference to the figures, a system for collection of data indicative of worker activity, and/or health and safety risks 10 is presented (system 10). In one or more arrangements, system 10 includes a plurality of wearable devices 12 and a monitoring system 14 among other components.
Wearable devices 12 are formed of any suitable size, shape, and design and are configured to record motion and/or other data indicative of work performed by workers 16 and/or safety risks encountered by workers 16b during a work shift, such as environmental conditions as well as near misses. In one or more arrangements, recorded information may include, for example, motion of workers 16 (e.g., accelerometer and/or gyroscopic data), location of workers 16 during a work shift, proximity to high risk machinery, air quality, sound levels, data indicative of physicality of tasks performed by workers 16 such as heart rate, temperature, perspiration level, number of steps, distance traveled, and/or other data acquired by sensors of wearable devices 12.
In one or more arrangements, system 10 may include wearable devices 12, charging base 18 and/or other components implemented as described in U.S. patent application Ser. No. 17/518,644 filed Nov. 4, 2021 and titled DEVICE, SYSTEM, AND METHOD FOR ASSESSING WORKER RISK; U.S. Pub. No. 2021/0264764 filed May 6, 2021 and titled DEVICE, SYSTEM, AND METHOD FOR HEALTH AND SAFETY MONITORING; U.S. Pat. No. 11,030,875, filed on Nov. 20, 2019 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE; U.S. Pat. No. 10,522,024 filed on Sep. 7, 2018 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE; and U.S. Pat. No. 10,096,230 filed on Jun. 6, 2017 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE, each of which is hereby incorporated by reference herein in its entirety, including any figures, tables, or drawings or other information.
However, the embodiments are not so limited. Rather, it is contemplated that wearable devices 12 may be implemented using various other devices and/or arrangements configured to acquire sensor data and communicate recorded sensor data to monitoring system 14. In the arrangement shown, as one example, wearable devices 12 each include one or more sensors 22, an electronic circuit 24, and a power source 26 among other components.
Sensors 22 are formed of any suitable size, shape, and design and are configured to record data relating to worker activity, and/or health and safety risks encountered by worker 16 while working. In one or more arrangements, wearable device 12 includes a plurality of sensors 22.
In one or more arrangements, wearable device 12 includes an accelerometer 22A. Accelerometer 22A is formed of any suitable size, shape, and design and is configured to detect acceleration and/or movement of the wearable device 12, such as when a worker 16 trips on something on the floor and almost falls, or when a worker 16 falls off of a ladder, is hit by a fork truck, or has another traumatic event. Accelerometer 22A may be formed of any acceleration detecting device such as a one axis accelerometer, a two-axis accelerometer, a three axis accelerometer or the like. Accelerometer 22A also allows for the detection of changes in acceleration, detection of changes in direction as well as elevated levels of acceleration.
In an alternative arrangement, or in addition to an accelerometer 22A, a gyroscope or gyro-sensor may be used to provide acceleration and/or movement information. Any form of a gyro is hereby contemplated for use, however, in one or more arrangements a three-axis MEMS-based gyroscope, such as that used in many portable electronic devices such as tablets, smartphones, and smartwatches are contemplated for use. These devices provide 3-axis acceleration sensing ability for X, Y, and Z movement, and gyroscopes for measuring the extent and rate of rotation in space (roll, pitch, and yaw).
In another arrangement, and/or in addition to an accelerometer 22A, a magnetometer may be used to provide acceleration and/or movement information. Any form of a magnetometer that senses information based on magnetic fields is hereby contemplated for use. In one or more arrangements, a magnetometer is used to provide absolute angular measurements relative to the Earth's magnetic field. In one or more arrangements, an accelerometer, gyro and/or magnetometer are incorporated into a single component or a group of components that work in corresponding relation to one another to provide up to nine axes of sensing in a single integrated circuit providing inexpensive and widely available motion sensing.
In one or more arrangements, wearable device 12 includes a temperature sensor 22B. Temperature sensor 22B is formed of any suitable size, shape, and design and is configured to detect the temperature of the environment surrounding the worker 16. The same and/or an additional temperature sensor 22B may be configured to detect the temperature of the worker 16 themselves. In one or more arrangements, temperature sensor 22B is a thermometer. Temperature sensor 22B allows for the detection of high or low temperatures as well as abrupt changes in temperature. Temperature sensor 22B also allows for the detection of when a temperature threshold is approached or exceeded. In one or more arrangements, wearable device 12 includes a humidity sensor 22C. Humidity sensor 22C is formed of any suitable size, shape, and design and is configured to detect the humidity of the environment surrounding the worker 16. The same and/or an additional humidity sensor 22C may be configured to detect the humidity level, moisture level or perspiration level of the worker 16 themselves. Humidity sensor 22C allows for the detection of high or low levels of humidity as well as abrupt changes in humidity. Humidity sensor 22C also allows for the detection of when a humidity threshold is approached or exceeded. In one or more arrangements, wearable device 12 includes a light sensor 22D. Light sensor 22D is formed of any suitable size, shape, and design and is configured to detect the light levels of the environment surrounding the worker 16. Light sensor 22D allows for the detection of high or low levels of light as well as abrupt changes in light levels. Light sensor 22D also allows for the detection of when a light threshold is approached or exceeded. In one or more arrangements, light sensor 22D is operably connected to and/or accessible by a light pipe (not shown). Light pipe is any device that facilitates the collection and transmission of light from the environment surrounding the worker 16. In one or more arrangements, the light pipe is a clear, transparent, or translucent material that extends from the exterior of the wearable device 12 to the light sensor 22D and therefore covers and protects light sensor 22D while enabling the sensing of light conditions.
In one or more arrangements, wearable device 12 includes an air quality sensor 22E. Air quality sensor 22E is formed of any suitable size, shape, and design and is configured to detect the air quality of the environment surrounding the worker 16, the particulate matter in the air of the environment surrounding the worker 16, the contaminant levels in the air of the environment surrounding the worker 16, or any particular contaminant level in the air surrounding the worker 16 (such as ammonia, chlorine, or any other chemical, compound or contaminant). Air quality sensor 22E allows for the detection of high contaminant levels in the air as well as abrupt changes in air quality. Air quality sensor 22E also allows for the detection of when an air quality threshold is approached or exceeded.
In one or more arrangements, air quality sensor 22E is a total volatile organic compound sensor, also known as a TVOC sensor. Volatile organic compounds (or VOCs) are organic chemicals that have a high vapor pressure at ordinary room temperature. VOCs are numerous, varied, and ubiquitous. They include both human-made and naturally occurring chemical compounds. Most scents or odors are of VOCs. In this arrangement, air quality sensor 22 is configured to detect VOCs. Also, in one or more arrangements, air quality sensor 22E is accessible through one or more openings in wearable device 12 that provide unfettered access and airflow for sensing by air quality sensor 22E.
In one or more arrangements, wearable device 12 includes a carbon monoxide (CO) sensor 22F. CO sensor 22F is formed of any suitable size, shape, and design and is configured to detect CO levels of the environment surrounding the worker 16. CO sensor 22F allows for the detection of high CO levels in the air as well as abrupt changes in CO levels. CO sensor 22F also allows for the detection of when a CO threshold is approached or exceeded. Of course, sensor 22F, or additional sensors 22, may be used to sense other gasses in the air around the worker 16, such as carbon dioxide, ozone, or any other gas or other content of the air around the worker 16. Also, in one or more arrangements, sensor 22F is accessible through one or more openings in wearable device 12 that provide unfettered access and airflow for sensing by sensor 22F.
In one or more arrangements, wearable device 12 includes a position sensor 22G. Position sensor 22G is formed of any suitable size, shape, and design and is configured to detect the position of the worker 16 within the manufacturing facility. Notably, the term manufacturing facility is to be construed in a broad manner and may include being within one or a plurality of buildings. However, the manufacturing facility may include being outside and unconstrained by the boundaries of a building or any particular grounds. Position sensor 22G allows for the detection of movement of the worker 16 within the manufacturing facility, the speed of movement of the worker 16 within the manufacturing facility, the tracking of the position of the worker 16 within the manufacturing facility, among any other speed, location, direction, inertia, acceleration or position information. This position information can be aggregated over the course of the worker's 16 shift to determine the amount of distance traveled by the worker 16, the average speed, the mean speed, the highest speed, or any other information. In addition, this position information can be aggregated to determine the areas where the worker 16 concentrated their time. In addition, this position information can be correlated with the information detected by the other sensors to determine the concentration of certain environmental factors in different areas of the manufacturing facility. Position sensor 22G may be a GPS device, a wireless device (e.g., Wi-Fi and/or RFID) configured to detect presence of nearby wearable devices, a wireless device that utilizes trilateration from known points, or any other device that detects the position of wearable device 12 and the worker 16.
Wearable device 12 may also include any other sensors 22. For example, in one or more arrangements, wearable device 12 includes one or more sensor 22 that tracks biometric data of the worker 16 including but not limited to, for example, heart rate, blood pressure, blood oxygen levels, blood alcohol levels, blood glucose sensor, respiratory rate, galvanic skin response, bioelectrical impedance, brain waves, and/or combinations thereof.
In one or more arrangements, wearable device 12 includes a sound sensor 22H. Sound sensor 22H is formed of any suitable size, shape, and design and is configured to detect the volume level and/or frequency of sound surrounding the worker 16. In one or more arrangements, sound sensor 22H is a microphone that is accessible through one or more openings in wearable device 12 that provide unfettered access for the sound to reach the microphone. Sound sensor 22H allows for the detection of elevated sounds, abrupt spikes in sounds, loud noises, irritating or distracting frequencies or the like. Sound sensor 22H also allows for the detection of when a volume threshold is approached or exceeded.
During operation, sensors 22 detect environmental conditions, such as sound, temperature, humidity, light, air quality, CO levels, TVOC levels, particulate levels, position and acceleration information, direction information, speed information and the like respectively.
Electronic circuit 24 is formed of any suitable size, shape, design, technology, and in any arrangement and is configured to facilitate retrieval, processing, and/or communication of data from sensor(s) 22 of wearable device 12 to monitoring system 14. In the arrangement shown, as one example, electronic circuit 24 includes a communication circuit 32, a processing circuit 34, and a memory 36 having software code 38 or instructions that facilitates the operation of wearable device 12.
In one or more arrangements, electronic circuit 24 includes a communication circuit 32. Communication circuit 32 is formed of any suitable size, shape, design, technology, and in any arrangement and is configured to facilitate communication with monitoring system 14. In one or more arrangements, as one example, communication circuit 32 includes a transmitter (for one-way communication) or transceiver (for two-way communication). In some various arrangements, communication circuit 32 may be configured to communicate with monitoring system 14 and/or various components of system 10 using various wired and/or wireless communication technologies and protocols over various networks and/or mediums including but not limited to, for example, IsoBUS, Serial Data Interface 12 (SDI-12), UART, Serial Peripheral Interface, PCI/PCIe, Serial ATA, ARM Advanced Microcontroller Bus Architecture (AMBA), USB, Firewire, RFID, Near Field Communication (NFC), infrared and optical communication, 802.3/Ethernet, 802.11/WiFi, Wi-Max, Bluetooth, Bluetooth low energy. Ultra Wideband (UWB), 802.15.4/ZigBee, ZWave, GSM/EDGE, UMTS/HSPA+/HSDPA, CDMA, LTE, 4G, 5G, FM/VHF/UHF networks, and/or any other communication protocol, technology or network.
In some various arrangements, electronic circuit 24 and/or communication circuit 32 may be configured to communicate data from sensors 22 to monitoring system 14 (or other device) continuously, periodically, according to a schedule, when prompted by monitoring system 14 (or other device), when wearable device is checked in and connected to charging base 18, and/or in response to any other stimuli, command, or event.
Processing circuit 34 may be any computing device that receives and processes information and outputs commands, for example, according to software code 38 stored in memory 36. For instance, in some various arrangements, processing circuit 34 may be discreet logic circuits or programmable logic circuits configured for implementing these operations/activities, as shown in the figures and/or described in the specification. In certain arrangements, such a programmable circuit may include one or more programmable integrated circuits (e.g., field programmable gate arrays and/or programmable ICs). Additionally or alternatively, such a programmable circuit may include one or more processing circuits (e.g., a computer, microcontroller, system-on-chip, smart phone, server, and/or cloud computing resources). For instance, computer processing circuits may be programmed to execute a set (or sets) of software code stored in and accessible from memory 36. Memory 36 may be any form of information storage such as flash memory, ram memory, dram memory, a hard drive, or any other form of memory.
In one or more arrangements, processing circuit 34 and memory 36 may be formed of a single combined unit. Alternatively, processing circuit 34 and memory 36 may be formed of separate but electrically connected components. Alternatively, processing circuit 34 and memory 36 may each be formed of multiple separate but communicatively connected components. Software code 38 is any form of instructions or rules that direct how processing circuit 34 is to receive, interpret and respond to information to operate as described herein. Software code 38 or instructions are stored in memory 36 and accessible to processing circuit 34.
Power Source 26:
In the arrangement shown, as one example, wearable device 12 includes a power source 26. Power source 26 is formed of any suitable size, shape, design, technology, and in any arrangement or configuration and is configured to provide power to wearable device 12 so as to facilitate the operation of the electronic circuit 24, sensors 22, and/or other electrical components of the wearable device 12. In the arrangement shown, as one example, power source 26 is formed of one or more batteries, which may or may not be rechargeable. Additionally or alternatively, in one or more arrangements, power source 26 may include a solar cell or solar panel that may power or recharge wearable device 12. Additionally or alternatively, in one or more arrangements, power source 26 may be line-power that is power that is delivered from an external power source into the wearable device 12 through a wired connection. Additionally or alternatively, in one or more arrangements, power source 26 may be a wireless power delivery system configured to power or recharge wearable device 12. Any other form of a power source 26 is hereby contemplated for use.
In one or more arrangements, wearable device 12 is configured to be worn by a worker 16 and in this way, wearable device 12 is considered to be a wearable device 12. To facilitate being worn by a worker 16 while working, wearable device 12 includes an attachment member 28 connected to or formed into wearable device 12. In some various arrangements, wearable device 12 may utilize various different methods and/or means to attach with a worker 16 including but not limited to, for example, a band, strap, belt, elastic strap or the like, that is attachable to a worker's arm wrist, waist or other part of the body or clothing worn by the worker 16. In one or more arrangements, it is desirable to attach the wearable device 12 to the worker's non-dominant arm while working. Alternatively, attachment member 28 is formed of any other device that connects two components together such as a snap-fit member, a clip, hook-and-loop arrangement, a button, a snap, a zipper-mechanism, a zip-tie member, or the like, just to name a few. As another arrangement, wearable device 12 can be attached to or formed as part of a piece of clothing or equipment, such as a safety vest, a helmet or the like. In one or more arrangements, as is further described herein, wearable device 12 is held within a holster having an attachment member in a removable manner, as is further described herein.
In some arrangements, electronic circuit 24 is configured to retrieve and evaluate data from sensors 22 to identify events of interest to facilitate selection of sensor data for analysis by monitoring system 14 and/or trigger performance of one or more actions. For example, in one or more arrangements, electronic circuit 24 of wearable device 12 is configured to capture data from by sensors 22 and periodically communicate the data or data metrics derived therefrom to monitoring system 14. In some various arrangements, such communication of data may be performed, for example, every second, ten seconds, thirty seconds, minute, 5 minutes, or any other suitable duration of time. In some various arrangements, such communication may communicate sensor measurements and/or data metrics from a single point in time, or measurements and/or data metrics collected over a certain window of time.
Additionally or alternatively, in one or more arrangements electronic circuit 24 of wearable device 12 is configured to communicate data captured by sensors 22 in response to the data satisfying a set of criteria. For example, in one or more arrangements, electronic circuit 24 of wearable device 12 is configured to continuously monitor data captured by sensors 22 of wearable device 12 of a worker 16 during a work shift and evaluate the data to identify instances in which the data indicates an event of interest (e.g., motion data indicating acceleration/deceleration exceeding a threshold). In response to identifying an event of interest, a segment (or window) of the sensor data in which the event occurred is communicated to the monitoring system for evaluation. Said another way, in some arrangements wearable device 12 pre-evaluates sensor data so as to only communicate sensor data when events of interest occur. Pre-evaluation of sensor data by the wearable device 12 provides several benefits. Power usage by wearable device 12 for communication of data is reduced as less data is required to be transmitted to monitoring system 14. Furthermore, because less data is transmitted by wearable devices 12 more bandwidth is available for communication data and interference and collisions are reduced. Pre-evaluation of sensor data by the wearable device 12 also reduces processing and storage requirements of monitoring system 14.
Different arrangements may utilize various different criteria and/or processes to identify events of interest. In the example shown, process block 110 shown an example process for identifying events of interest. In this example, events of interest are identified when acceleration in any direction exceeds a threshold. At process block 112, the magnitude of the acceleration vector is determined. Magnitude of the acceleration vector d may be determined by
At decision block 114, the determined magnitude of the acceleration vector is compared to a threshold. In this example arrangement, if the determined magnitude exceeds that threshold an event of interest is detected. Otherwise, an event of interest is not detected. In one or more arrangements, a threshold acceleration of 2 g (19.6133 m/sec2) is used to identify when motion data indicates an event of interest has occurred.
However, the embodiments are not so limited. Rather, other thresholds may be appropriate for identifying events of interest depending on the type of activity that workers 16 engage in during a work shift. For example in one or more arrangements, wearable devices may be configured to process data acquired from motion and/or other sensors, for example using classifiers and/or other analytics processes to identify various events of interest. Such events of interest may include but are not limited to, for example, acceleration exceeding threshold, repetitive motions, excessive noise, adverse temperatures or other working conditions, worker 16 being in close proximity to dangerous equipment, potential accidents or near misses and/or any other notable event that may be pertinent to worker 16 safety and/or management.
If an event of interest is detected, the process proceeds from decision block 104 to process block 106, where the current window of motion data is communicated to monitor system 14. In one or more arrangements, the window of motion data includes 15 seconds of motion data centered on the motion data sample in which the event of interest was detected. In other words, the window of motion data includes approximately 7.5 seconds of motion data preceding the event of interest and 7.5 seconds of motion data following the event of interest. The motion data preceding and following the event of interest may help facilitate further analytics of the motion data. However, the embodiments are not so limited. Rather, it is contemplated that in some various arrangements, wearable device(s) 12 may be configured to use windows of various different lengths of time and/or time period relative to detected events of interest.
If an event of interest is not detected at decision block 104, the process returns to process block 100, where motion data is retrieved from one or more sensors 22 and moved into the buffer. The process repeats in this manner until wearable device 12 is checked-in, powered off, or operation is otherwise disabled. In one or more arrangements, wearable devices 12 are configured to sample data from sensors at approximately 25 hz. However, the embodiments are not so limited. Rather, it is contemplated that wearable devices 12 may sample data from sensors 22 at any frequency as may be appropriate for the type of data.
Although some arrangements are primarily described with reference to communication of certain types of sensor data (e.g., motion data), the embodiments are not so limited. Rather, it is contemplated that wearable devices 12 may communicate data of various other types of sensors in the windows of data in addition to or in lieu of motion data. For example, in one or more arrangements, wearable devices 12 may be configured to communicate data from all sensors 22 in the window of sensor data that is communicated to the monitoring system 14. Data from all sensors may be useful, for example, to facilitate analytics by monitoring system 14.
It is noted that in some arrangements, wearable devices 12 need not communicate a separate window of sensor data for every sample that satisfies criteria for an event of interest. For example, in one or more arrangements, wearable devices 12 may be configured to disable communication of data windows for the same events of interest for a period of after communicating a first window of sensor data for a detected event of interest (e.g., for 1 minute). However, the embodiments are not so limited. Rather, it is contemplated that wearable devices 12 may be configured to disable communication of data windows for any other length of time after communicating a first window of sensor data for a detected event of interest.
In the arrangement shown in
At process block 130, motion data is retrieved from one or more sensors 22 and placed in a buffer (e.g., a FIFO buffer), which stores a window of recent motion data (e.g., the most recent 10 seconds). At process block 132, the motion data is evaluated to determine if an event of interest occurred and then proceeds to decision block 134.
If an event of interest is not detected at decision block 134, the process proceeds to decision block 142. Otherwise, the process proceeds to process block 136. At process block 136, the current window of motion data is wirelessly communicated to monitor system 14. If communication is successful at decision block 138, the process proceeds directly to decision block 142. Otherwise, if communication is not successful at decision block 138, the process proceeds to process block 140, where the window of data is stored (e.g., in a memory) for later transmission. The process then proceeds to decision block 142.
In this example, unless the wearable device 12 is checked in, the process proceeds from decision block 134 back to process block 130, where motion data is retrieved from one or more sensors 22 and moved into the buffer. The process loops in this manner until the wearable device 12 is checked in by the worker 16, powered off, or otherwise disabled. In successive loops, when wearable device 12 attempts to communicate the current window of sensor data to monitoring system 14 wearable device 12 also attempts to resend any stored window of sensor data that previously were unable to be communicated. If communication is again unsuccessful, the current window of sensor data is also stored at process block 140. As the process loops, windows of sensor data for events of interest continue to be stored until communication is successful at decision block 138 or the wearable device 12 is checked in. When the wearable device 12 is checked in and connected to charging base 18, the process proceeds from decision block 142 to process block 144, where stored windows of sensor data (if any) are communicated to monitoring system 14 over a wired connection.
Although some arrangements are primarily described with reference to identifying events of interest in motion data, the embodiments are not so limited. Rather, it is contemplated that in some arrangements wearable devices 12 may additionally or alternatively identify events of interest based on data of other sensors and/or data metrics derived therefrom and/or using various different criteria and/or algorithms. In one or more arrangements, wearable devices 12 are configured to perform analytics on sensor data directly on the wearable devices 12 to identify events of interest, generate data metrics, and/or trigger performance of various actions by wearable devices 12. In some various arrangements, actions may include but are not limited to, providing status messages, alerts, or other notification (e.g., emails, SMS, push notifications, automated phone call, social media messaging, and/or any other type of messaging) to a safety manager or other users and/or devices (e.g., computer, table, or smartphone).
In one or more arrangements, wearable devices 12 are configured to perform various preprogrammed actions in response to analytics of sensor data and/or derived data metrics satisfying one or more trigger conditions (e.g., detecting certain events of interest). In one or more arrangements, wearable devices 12 include a configuration data file in memory 36 that specifies one or more trigger condition and one or more actions to be performed when respective trigger conditions are satisfied. The configuration data file may be any form of information that indicates conditions in which wearable device 12 is to perform actions and which actions are to be performed. In one or more arrangements, configuration data file is arranged as a set of rules, where each rule indicates a set of conditions and one or more actions to be performed when the conditions are satisfied. However, it is contemplated that wearable devices 12 may be configured to utilize a configuration data file with any configuration, arrangement, format, or structure.
In one or more arrangements, system 10 includes a charging base 18. Charging base 18 is formed of any suitable size, shape, and design and is configured to receive, charge and transfer information from and to wearable devices 12. In the arrangement shown, as one example, charging base 18 includes a back wall 42 that includes a plurality of sockets 44 therein that are sized and shaped to receive wearable devices 12 therein. When wearable devices 12 are placed within sockets 44, wearable devices 12 are charged by charging base 18 and data may be transferred between wearable device 12 and charging base 18 and the other components of the system 10. Charging base 18 also includes a user interface 46 configured to provide the ability for the workers 16 to interact with the charging base 18. User interface 46 may include but is not limited to, for example, a plurality of sensors, a key pad, a biometric scanner, a touch screen or any other means or method input for information.
In one or more arrangements, charging base 18 is configured to facilitate checkout/checking of wearable devices 12 by workers 16. As one example, at the beginning of a shift, a worker 16 engages the charging base 18 using user interface to identify the worker 16 with the system 10 (e.g., by biometrically scanning in with a finger or thumb print, a retinal scan, facial recognition, voice recognition, inputting a name or identifier, swiping an ID card, and/or any other manner or method of associating their personal identification with the system 10).
Upon receiving this information, charging base 18 and system 10 identifies the worker 16 and allocates a wearable device 12 held within one of the sockets 44 of the charging base 18 that is fully charged, or has the highest charge among the wearable devices 12, and assigns that wearable device 12 to that worker 16 by illuminating the wearable device 12, illuminating the socket 44 that the wearable device 12 is held in, or providing the socket number to the worker 16 or by identifying which wearable device 12 the worker 16 is to take by any other manner, method or means. Once the proper wearable device 12 has been identified to the worker 16, the worker 16 retrieves that wearable device 12 from the charging base 18 and puts on the wearable device 12.
During the work shift, the wearable device 12 gathers data from sensors 22 and communicates data to monitoring system 14 as described herein. At the end of the shift, the worker 16 returns the wearable device 12 to the charging base 18. Once the wearable device 12 is plugged into a socket 44, the charging base 18 begins charging the wearable device 12. If the wearable device 12 has buffered data, charging base 18 retrieves the data from the wearable device 12 and provides the retrieved data to monitoring system 14.
In one or more arrangements, after turning in the wearable device 12 at the end of their shift, the worker 16 is provided with a log of all instances that were identified as events of interest. The information related to each of these potential accidents or near misses and/or notable events is provided to the worker 16 such as time, acceleration, position, temperature, light level, air quality, volume, CO level, the audible recording or converted text of the contemporaneous recording of the incident or notable event. The worker 16 is then provided the opportunity to confirm or deny whether a notable event of interest actually occurred and provide additional information regarding the notable event of interest. This provides the worker 16 the opportunity to clarify the record and provide additional information.
In one or more arrangements, the system 10 may also update the software or firmware on the wearable device 12 and prepare the wearable device 12 for another use while in the charging base. For example, in one or more arrangements, system 10 may from time to time update classifiers or other analytics algorithms used by wearable devices 12 to identify events of interest.
Monitoring system 14 is formed of any suitable size, shape, design and is configured to receive and process sensor data from wearable devices 12 to facilitate analysis of sensor data (e.g., to assess worker physicality, risk, and/or derive various other data metrics). In the arrangement shown, as one example, monitoring system 14 includes a database 60 and a data processing system 62, among other components.
Database 60 is formed of any suitable size, shape, design and is configured to facilitate storage and retrieval of data. In the arrangement shown, as one example, database 60 is local data storage connected to data processing system 62 (e.g., via a data bus or electronic network 20). However, embodiments are not so limited. Rather, it is contemplated that in one or more arrangements database 60 may be remote storage or cloud based service communicatively connected to data processing system 62 via one or more external communication networks.
In some various arrangements, information recorded by wearable devices 12 may be communicated to database 60 for storage directly (e.g., over electronic network 20) from wearable devices. Additionally or alternatively, in some various arrangements, information recorded by wearable devices 12 may be communicated to database 60 for storage indirectly (e.g., by charging base 18 and/or data processing system 62).
Data processing system 62 is formed of any suitable size, shape, and design and is configured to facilitate receipt, storage, and/or retrieval of information in database 60, execution of analytics processes 70, providing of a user interface 72, and/or implementation of various other modules, processes or software of system 10. In one or more arrangements, for example, such data processing system 62 includes a circuit specifically configured and arranged to carry out one or more of these or related operations/activities. For example, data processing system 62 may include discrete logic circuits or programmable logic circuits configured and arranged for implementing these operations/activities, as shown in the figures, and/or described in the specification. In certain embodiments, such a programmable circuit may include one or more programmable integrated circuits (e.g., field programmable gate arrays and/or programmable ICs). Additionally or alternatively, such a programmable circuit may include one or more processing circuits (e.g., a computer, microcontroller, system-on-chip, smart phone, server, and/or cloud computing resources). For instance, computer processing circuits may be programmed to execute a set (or sets) of instructions (and/or configuration data). The instructions (and/or configuration data) can be in the form of firmware or software stored in and accessible from a memory (circuit). Certain embodiments are directed to a computer program product (e.g., nonvolatile memory device), which includes a machine or computer-readable medium having stored thereon instructions, which may be executed by a computer (or other electronic device) to perform these operations/activities.
User interface 72 is formed of any suitable size, shape, design, technology, and in any arrangement and is configured to facilitate user control and/or adjustment of various components of system 10. In one or more arrangements, as one example, user interface 72 includes a set of inputs (not shown). Inputs are formed of any suitable size, shape, and design and are configured to facilitate user input of data and/or control commands. In various different arrangements, inputs may include various types of controls including but not limited to, for example, buttons, switches, dials, knobs, a keyboard, a mouse, a touch pad, a touchscreen, a joystick, a roller ball, or any other form of user input. Optionally, in one or more arrangements, user interface 72 includes a display (not shown). Display is formed of any suitable size, shape, design, technology, and in any arrangement and is configured to display information of settings, sensor readings, time elapsed, and/or other information pertaining to worker activity and/or health and safety risks; operation of system 10; and/or management of workers 16. In one or more arrangements, the display may include, for example, LED lights, meters, gauges, screen or monitor of a computing device, tablet, and/or smartphone.
Additionally, or alternatively, in one or more arrangements, the inputs and/or display may be implemented on a separate device that is communicatively connected to monitoring system 14. For example, in one or more arrangements, operation of monitoring system 14 may be customized or controlled using a smartphone or other computing device that is communicatively connected to the monitoring system 14 (e.g., via Bluetooth, WiFi, and/or the internet).
In some example arrangements, data processing system 62 is configured to perform various tracking, analytics processes 70, and/or other operations described using data received from wearable devices 12 and/or data stored in database 60.
In one or more arrangements, analytics processes 70 are configured to analyze data provided by sensors 22 to assess the physical exertion of workers 16. Jobs requiring high levels of physical exertion may be more likely to result in injury or require more frequent rotation between assigned jobs. In this example arrangement, analytics processes 70 are configured to quantify the total physicality of tasks performed by workers 16 based on heart rate, temperature, perspiration level, number of steps, distance traveled, accelerometer data, and/or other data acquired by sensors 22 or determined by analytics processes 70 using data analytics (e.g., the determined repetitive motion quantification). In some various arrangements, the analytics processes 70 may generate and store data metrics indicating instances in which a worker 16 exhibits high levels of physical exertion during a work shift. Such data metrics may be useful in assessing safety risk faced by a worker 16 during a work shift, assessing worker 16 productivity, and/or determining work schedules.
In one or more arrangements, analytics processes 70 are configured to process information received from wearable devices 12 and/or data stored in database 60 to derive additional data metrics pertinent to assessment of safety risk of workers 16. In an example arrangement, analytics processes 70 may be configured to evaluate the data using a classifier, state machine, and/or other machine learning algorithm that is trained to identify high risk events (e.g., accidents, trips/falls, near misses, and/or other events indicative of injury or heightened safety risk) that are not directly identified and reported by wearable devices 12. In some arrangements, identified instances may be logged to create a history of high risk events for a worker 16. Such historical data may be useful in assessing safety risks faced by a worker 16 during a work shift.
In yet another example arrangement, analytics processes 70 are configured to analyze data of an accelerometer sensor 22 to identify motions which may lead to injury over time. Identification of motions may be helpful to identify performance of tasks that have a higher risk of injury. Identification of such tasks may be useful in assessing safety risks faced by a worker 16 during a work shift. In one or more arrangements, analytics processes 70 may be configured to identify any number of different motions including but not limited to, for example, bending at waist, twisting, overhead reach, walking, slips, trips, falls, and/or repetitive motions.
Identification of repetitive motions may be helpful to facilitate development and execution of measures to avoid such injury. In this example arrangement, analytics processes 70 may be configured to regularly retrieve accelerometer sensor 22 data of workers 16 from database 60 for evaluation (e.g., daily, weekly, or monthly). After retrieving the data, analytics processes 70 processes the data using, for example a classifier, state machine or other machine learning algorithm that is trained to detect and group similar motion events.
In an example arrangement, after processing the data to identify similar motion events, analytics processes 70 determines a set of workers 16 in which a motion or similar group of motions is identified with a high number of occurrences (e.g., exceeding a specified threshold). In this example arrangement, analytics processes 70 then flag the task performed by the workers 16 as a high risk activity.
In one or more arrangements, analytics processes 70 are configured to quantify the level of repetitive motions performed by a worker 16. For example, in one or more arrangements, analytics processes 70 may be configured to quantify repetitive motions based on the number of instances that a worker 16 performs the identified repetitive motions in a certain period of time (e.g., day, week, month). In some various arrangements, the analytics processes 70 may generate reports, e.g., tables, charts, graphs, maps, showing the quantified repetitive motion, for example, for different jobs, workplace areas, different departments, groups and/or individual workers 16, and/or different shifts or times of day.
Deviation from Similar Workers
In one or more arrangements, analytics processes 70 are configured to identify workers 16 in which recorded information and/or data metrics deviates from that of other similarly situated workers 16. Such identification of workers 16 may be useful for example to identify workers 16 whose safety risk may be atypical and not accurately represented by the average risk for the worker's 16 occupational role. In one or more arrangements, analytics processes 70 may generate a report indicating workers 16 for which deviations have been identified. In some arrangements, the analytics processes 70 may send the report to a manager for review. In some arrangements, in response to identifying deviations for a set of workers 16, monitoring system 14 may be configured to automatically perform various additional analytics processes 70 to generate data metrics indicative of safety risk faced by the workers 16.
It is recognized that workers 16 tend to experience increased risk over time, often due to changes in their work environment and/or long hours in difficult conditions. As an illustrative example, a worker 16 may begin to regularly work in low lighting at the end of a long shift. Such low lighting may present risk of fatigue and increase risk of injury. In one or more arrangements, analytics processes 70 are configured to track values of the worker 16 data stored in database 60 to identify when trends occur. In one example arrangement, in response to identifying a trend in the data, analytics processes 70 update data metrics and/or risk assessments for the worker 16. Additionally or alternatively, in response to identifying a trend in the data, analytics processes 70.
In one or more embodiments, data processing system 62 and/or other components of system 10 may be configured and arranged to monitor, learn, and modify one or more features, functions, and/or operations of the system. For instance, analytics processes 70 of data processing system 62 may be configured to monitor and/or analyze data stored in database 60 and/or operation of system 10. As one example, in one or more arrangements, data processing system 62 may be configured to analyze the data and learn, over time, data metrics indicative of safety risks and/or algorithms for identification of safety risks. Such learning may include, for example, generation and refinement of classifiers and/or state machines configured to map input data values to outcomes of interest or to operations to be performed by the system 10. In various embodiments, analysis by the data processing system 62 may include various guided and/or unguided artificial intelligence and/or machine learning techniques including, but not limited to: neural networks, genetic algorithms, support vector machines, k-means, kernel regression, discriminant analysis and/or various combinations thereof. In different implementations, analysis may be performed locally, remotely, or a combination thereof.
In one or more arrangements, analytics processes 70 are configured to utilize physicality ratings data of workers 16 to select data for training of classifiers (or other machine learning algorithms). Such selection of data may be used, for example, to facilitate unsupervised training of machine learning algorithms. For example, data of workers 16 having high physicality ratings may be used to train machine learning algorithms to identify high physicality, safety risks from other data metrics, sensor data, and/or evaluation criteria.
In one or more arrangements, information provided by wearable devices 12 is processed by management software 74. Management software 74 converts the information into an incident report and a signal, such as a text message, email, or the like is transmitted to an electronic device (such as a cell phone, a handheld device, their own wearable device 12, an email account, or any other electronic device capable of receiving an electronic message or information) of one or more safety managers or other managers or other persons in charge of managing safety in the manufacturing facility. This signal includes the position/location of the event, time of the event, name of the worker 16 involved and type of potential accident or near miss along with any other pertinent information. In one or more arrangements, the audible recording of the worker's 16 description of the accident or near miss is also transmitted, or this audible recitation is automatically converted to text which is transmitted in text form as part of this signal. With this timely information, the safety manager can quickly and effectively respond to the potential accident or near miss. This information is also stored as an incident report in database 60 for risk assessment, data mining, data retrieval, data analytics, and/or machine learning and artificial intelligence purposes.
As this event is a safety event, transmission is expedited through the system 10 so that the safety manager, a response team or others can quickly respond in an attempt to mitigate the injury or damage. In one or more arrangements, when this signal indicating a safety event occurred is received, the location of the event is transmitted to a building control or safety system that then implements alarms, flashing lights or other safety precautions in the affected portion of the manufacturing facility to alert others as to the event and in an attempt to prevent further injury or damage. Once the safety manager arrives at the scene of the accident or near miss they may see that a pallet was placed in a high traffic area, as one example. In response, the safety manager can move the pallet or cordon off the area to prevent future accidents and/or take further corrective actions.
In one or more arrangements, management software 74 (and/or analytic processes 70) may be configured to perform various actions in response to data provided by wearable devices satisfying certain criteria. For example, in one or more arrangements, monitoring system 14 may be configured to generate control signals and/or control various equipment or switching of one or more relay switches (not shown) in response to data received from a wearable device 12 satisfying a particular set of criteria. For example, in one or more arrangements, management software 74 may be configured to control operation of various devices (e.g., lights, alarms, locks, doors, and/or any other devices) based on location of wearable devices 12.
In one or more arrangements, wearable devices 12 are configured to communicate sensor and/or other data to monitoring system 14 over an adaptive communication network 20 that can be tailored to suit the work shift of each individual worker 16. In one or more arrangements, wearable devices 12 are configured to selectably communicate data to monitoring system 14 using any of a plurality of methods of communication, which may include but are not limited to one or more infrastructure networks, (e.g., WiFi and/or cellular networks) and/or one or more ad hoc networks, among others.
In one or more arrangements, wearable devices 12 may be configured by a worker 16 based on the work that will be performed during the work shift. For example, in one or more arrangements, when the worker 16 checks out a wearable device from charging base 18, the charging base 18 may prompt the worker 16 to select which communication method to use for communication of sensor data during the upcoming work shift. For example, if the worker 16 will be in the field or at a remote worksite, the work shift may use a user interface of charging base 18 select to use a cellular network for communication of sensor data to monitoring system 14. As another example, if a worker 16 will be primarily working at a single location for the work shift, the worker 16 may select to use WiFi for communication of sensor data to monitoring system 14. As yet another example, if a worker 16 will be moving between several locations during the work shift, the worker 16 may select to use an ad hoc network formed with other wearable devices 12 for communication of sensor data to monitoring system 14.
In one or more arrangements, in response to a worker 16 selecting a method to be used for communication, charging base 18 communicates with the wearable device 12 assigned to the worker 16 to configure the wearable device 12 to use the selected method of communication. In one or more arrangements, charging base 18 is configured to automatically retrieve user connection information (e.g., from monitoring system 14) to facilitate automatic configuration of the wearable device 12 for the selected communication. For example, such user information may include but is not limited to, for example, network/device IDs, group ID, communication channel assignments, login/security credentials, and/or any other information used to establish a network connection. As an illustrative example, such user connection information may include information to establish a relay connection with a smartphone or other personal device of the worker's 16 (e.g., via Bluetooth and/or hotspot) to facilitate communication of data over a cellular network. As another example, such user connection information may include information to establish connections with WiFi networks available in work area(s)/locations of the worker 16. As another example, such user connection information may include information to establish connections with other wearable devices in work area(s)/locations of the worker 16.
Additionally or alternatively, in lieu of selection by a worker 16, in one or more arrangements charging base 18 and/or monitoring system 14 may be configured to automatically select an available method of communication for the worker 16 based on a work schedule, job assignment, and/or other information for the worker 16 (e.g., worker preferences stored in monitoring system 14). As one example, if the worker 16 is scheduled to work in the field for the day, charging base 18 may select to have wearable device 12 communicate data over a cellular network via a smartphone of the worker 16.
Upon configuring the wearable device to use the selected method of communication, charging base 18 identifies the wearable device 12 to the worker 16 (e.g., by illuminating the wearable device 12, illuminating the socket 44 that the wearable device 12 is held in, or providing the socket number to the worker 16 or by identifying which wearable device 12 the worker 16 is to take by any other manner, method or means). Once the proper wearable device 12 has been identified to the worker 16, the worker 16 retrieves that wearable device 12 from the charging base 18 and puts on the wearable device 12. During the work shift, the wearable device 12 gathers data from sensors 22 and communicates data to monitoring system 14 using the selected method of communication.
Upon receiving this information, charging base 18 communicates credentials 152 to monitoring system 14. At process block 154, monitoring system 14 assigns a wearable device 12 to the worker 16. At process block 156, monitoring system 14 selects a communication method to be used by the wearable device 12 (e.g., based on the workers' 16 work schedule for the day and/or saved user preferences) and determines configuration settings 158 for the selected communication method. Configuration settings 158 may include various information to facilitate communication using the selected communication method, which may include but is not limited to, for example, device/network IDs, access credentials, encryption keys, etc. The determined communication settings 158 are communicated from monitoring system 14 to the charging base 18.
In this example arrangement, at process block 162 charging base 18 prompts the worker 16 to confirm the selected communication method or select another option. In one or more arrangements, if another option is selected, charging base 18 may retrieve corresponding configuration settings 158 for the selected communication method. At process block 164, charging base 18 configures wearable device to use the selected communication method to communicate data to the monitoring system 14 during use and prompts the worker 16 to checkout the assigned wearable device 12 to complete checkout (e.g., by illuminating the wearable device 12, illuminating the socket 44 that the wearable device 12 is held in, or providing the socket number to the worker 16 or by identifying which wearable device 12 the worker 16 is to take by any other manner, method or means).
During the worker's 16 work shift, at process block 166, wearable device 12 collects data and communicates the data to monitoring system 14 using the selected communication method, as described herein. The process loops at process block 166 until the worker 16 docks the wearable device 12 at charging base 18 at decision block 168. Once docked, at process block 170 charging base 18 retrieves any data stored on wearable device 12 and communicates the data to monitoring system 14 (if not previously communicated) and completes check in.
Although in some arrangements charging base 18 may configure an assigned wearable device 12 to use a selected method of communication when the wearable device 12 is checked out by a worker 16, the arrangements are not so limited. Rather, it is contemplated that in one or more arrangements wearable devices 12 may be configured to dynamically select between communication methods at various times during a work shift. For example, in one or more arrangements, wearable device 12 may be configured to (or prompted to) use a different method of communication in response to data gathered by the wearable device satisfying a particular set of criteria. In some various arrangements, dynamic selection of methods for communication may be based on various data metrics and/or data sources including but not limited to, for example, geolocation of wearable device, proximity to particular equipment, detected wearable devices, time of day, work schedule, network throughput or availability, and/or based on any other data gathered by wearable devices or stored in monitoring system 14.
In one or more arrangements, the criteria for selection of communication methods may be specified by a set of rules in a configuration data file, where each rule indicates a set of trigger conditions and the communication method to be used when the trigger conditions are satisfied. Additionally or alternatively, in some various arrangements, rules in the configuration data file may prompt a wearable device 12 to perform one or more actions in response to particular trigger conditions being satisfied. In some various arrangements, such actions may include but are not limited to, for example, transmitting commands (e.g., a remote control command) to devices, providing status messages and/or sensor data to one or more devices, providing alert messages to one or more users or devices, and/or any other action. Trigger conditions may include, for example, Boolean sensor states, various Boolean functions of sensor values (e.g., threshold value triggers), and/or Boolean logic functions function of a combination of Boolean sensor states and/or Boolean functions. However, embodiments are not so limited. Rather, it is contemplated that in some various embodiments, trigger conditions may be specified in any configuration, arrangement, format, or structure.
In one or more arrangements, wearable devices 12 are configured to form an ad hoc communication network as one available method of communicating data to monitoring system 14. In one or more arrangements, such an ad hoc communication network is self organizing to facilitate connectivity of the wearable devices. In one or more arrangement, the ad hoc communication network is configured to dynamically assemble, reorganize, and/or collapse based on real time data about potential connection routes to adapt to changing conditions. The ability to dynamically adapt increases reliability of connectivity of wearable devices 12 as workers (and their wearable devices 12) move about a workplace.
In one or more arrangements, wearable devices 12 are configured to communicate between various wireless devices (e.g., wearable devices 12, repeaters, base stations 80, worker detection devices, smartphones, etc.) in the ad hoc network using Bluetooth. However, the arrangements are not so limited. Rather, it is contemplated that in some various arrangements, data may be communicated between wireless devices in the ad hoc network using various wireless communication protocols including but not limited to 802.11/WIFI, Wi-Max, Bluetooth, Bluetooth low energy, Ultra Wideband (UWB), 802.15.4/ZigBee, ZWave, GSM/EDGE, UMTS/HSPA+/HSDPA, CDMA, LTE, 4G, 5G, FM/VHF/UHF networks, and/or any other wireless communication protocol, technology or network.
For ease of description, ad hoc communication is primarily described with reference to communication between wearable devices 12. However, the arrangements are not so limited. Rather, it is understood that in various different arrangements, an ad hoc network may be formed by various different wireless devices including but not limited to, for example, wearable devices 12, repeaters, base stations 80, worker detection devices, smartphones, and/or any other device utilizing wireless communication. Furthermore, it is contemplated that in some arrangements, some various nodes in the overall network may be connected in a planned organization (e.g., non-self organizing/non-self assembling) in addition to wearable devices 12 or other nodes that self organizing.
In one or more arrangements, wearable devices 12 are configured to self-organize utilize and dynamically adapt the organization based on changing conditions to direct communication based on a best determined route from wearable devices 12 to a base station 80. In some various different arrangements, wearable devices 12 and/or other devices may utilize various different methods to self-organize and/or optimize routes in the ad hoc communication network
As one example, in one or more arrangements, wearable devices 12 utilize a novel weighting method to self-organize into a network to facilitate communication of data to a base station 80 or other infrastructure communication device communicatively connected to monitoring system 14. For example, in one or more arrangements, wearable devices 12 weight and organize themselves based on the number of hops in the network to reach a base station 80. For instance, a base station 80 is assigned a weight of zero, and communicates this weight to wearable devices 12 in range. In this example arrangement, each wearable device 12 is configured to receive weight from all devices (base stations 80, repeaters, wearable devices, etc) and select the device with the lowest weight to communicate data to the monitoring system 14. In this example arrangement, each wearable device 12 assigns itself a weight that is one greater than the weight of the device in the network that was selected for communication. In this example arrangement, each wearable device 12 assigns itself a weight of NULL (or other designated value) if the wearable device 12 is not connected to any device providing a communication path to the base station 80. In this manner, each wearable device is assigned a weight that represents the number of hops in the network for the wearable device to communicate data to the base station 80. Wherein each hop corresponds to a wireless transmission link between two devices in the ad hoc network.
Additionally or alternatively, while some arrangements may be primarily described herein with reference to weighting based on the number of hops from a wearable device 12 to a base station 80 in the ad hoc network 20 the arrangements are not so limited. It is contemplated, that in some arrangements, weights in the ad hoc network 20 may be additionally determined based on various factors in addition or in lieu of the number of hops. This may include but is not limited to the strength of signal, throughput, packet loss, delay time, traffic congestion, and/or any other factor or characteristic relevant to wireless communication between a wearable device 12 and any other wireless device that is part of the ad hoc network. As one example, if a wearable device 12 detects multiple other wearable devices with an equal weight (by number of hops) the wearable device may consider other factors and/or characteristics to select which wireless device/wearable device 12 to connect to and exchange data with in the ad hoc network such as the wireless device with the strongest signal or highest throughput.
In one or more arrangements, weights of wearable devices are periodically broadcast by each wearable device 12 to permit each wearable device to update its selection of device to use for communication and update its weight if applicable. Additionally or alternatively, in one or more arrangements, communication of weight by wearable devices 12 may be event driven (e.g., in response to a wearable device changing its weight).
In one or more arrangements, wearable devices 12 in an ad hoc network may be configured to operate in a plurality of different modes depending on weights of other detected devices.
The wearable device 12 initially starts in the detector mode 200 when joining an ad hoc network. Wearable device 12 transitions to detector mode 200 whenever no device with a non-NULL weight is detected. In detector mode, wearable device 12 passively or actively discovers available devices and determines weights of such devices. In this example arrangement, wearable device 12 transitions to worker mode 202 whenever an available device with a non-NULL weight is detected and devices are detected that have a weight that is NULL or higher than the weight of the device. In worker mode 202, wearable device 12 transmits data to monitoring system via the selected lowest weighted device but does not relay data for other wearable devices 12. This encourages other wearable devices to communicate data to infrastructure-based repeaters and/or base stations 80 that are connected to a continuous power supply rather than batteries. In some various arrangements, transmission is initiated by the lower weight wearable device retrieving data from a higher weight device (if data is available). Additionally or alternatively, in some arrangements, transmission may be initiated by the higher weight device.
In this example arrangement, wearable device 12 transitions to repeater mode 204 whenever a non-NULL weight device is available for it to communicate data and one or more other wearable devices have NULL/higher weight than that of the wearable device. In repeater mode 204, the wearable device 12 communicates data that it generates to a selected device and also relays data received from one or more other wearable devices 12.
In some various network implementations, data may be relayed by either infrastructure-based repeaters, wearable devices 12, or both. When a network is setup to use infrastructure-based repeaters, those repeaters and installed at specific fixed locations at a facility to guarantee a network path to a base station 80. In some implementations, a set of wearable devices 12 may be configured to operate as infrastructure-based repeaters and then installed at fixed locations at the facility. In this configuration, the wearable devices 12 that are worn by workers 16 may be configured to have a NULL/max weight. Since data is communicated from high weight devices to lower weight devices, the wearable devices 12 that are worn by workers 16 will never attempt to connect to other wearable devices 12 that are worn by workers 16. When a network is not setup to use infrastructure-based repeaters or does not have enough infrastructure-based repeaters to provide complete coverage, the wearable devices 12 worn by workers 16 may relay data in the network in addition to or in lieu of infrastructure-based repeaters. However, because such wearable devices 12 are not at fixed locations, a network path to a base station 80 is not always guaranteed.
In some arrangements, a wearable device 12 may be configured to store a copy of data it generates when communicating the data via an ad hoc network to ensure the data is not lost as it is relayed through the ad hoc network. For example, a wearable device in repeater mode may become disconnected from other devices before it is able to relay the data received from another wearable device.
From the above discussion, it will be appreciated that one or more arrangements provide a wearable device, system, and/or method of use that improve upon the state of the art. Specifically, one or more arrangements provide a wearable device, system, and/or method: for collecting, reporting and analyzing information indicative of work performed by workers and/or conditions that workers are exposed to in a workplace to better assess physicality of workers and safety risk posed to workers 16 during a work shift: that improves upon the state of the art; that collects information about the work performed by workers and workplace conditions; that utilizes an adaptive method of communication to communicate data from wearable devices to a monitoring system; that ensures that all data is communicated to the monitoring system when communication is intermittent; that utilizes an adaptive method of communication that utilizes multiple different networks; that utilizes an adaptive method of communication that utilizes infrastructure and ad hoc networks; that utilizes an adaptive method of communication that adjusts the method of communication to fit the needs of each worker; that utilizes an adaptive method of communication that adjusts the method of communication based on the work schedule of each worker; that utilizes an adaptive method of communication that is energy efficient; that utilizes an adaptive method of communication than facilitates communication from nearly any location; that aggregates a great amount of information about the work performed by workers and workplace conditions; that eliminates bias in the collection of information about the work performed by workers and workplace conditions; that eliminates the inconsistency in reporting information about the work performed by workers 16 and workplace conditions; that utilizes collected information to assess physicality exhibited by workers during a work shift; that utilizes collected information to assess safety risks faced during a work shift; that aggregates a great amount of information indicative of work performed by workers and workplace conditions to facilitate data analytics; that is cost effective; that is safe to use; that is easy to use; that is efficient to use; that is durable; that is robust; that can be used with a wide variety of manufacturing facilities; that is high quality; that has a long useful life; that can be used with a wide variety of occupations; that provides high quality data; and/or that provides data and information that can be relied upon.
These and countless other objects, features, or advantages of the present disclosure will become apparent from the specification, figures, and claims.
This application claims priority to U.S. Provisional Patent Application 63/438,294 filed on Jan. 11, 2023 and titled DEVICE, SYSTEM, AND METHOD FOR ASSESSING WORKER RISK which is hereby incorporated by reference herein in its entirety, including any figures, tables, or drawings or other information. This application is related to U.S. patent application Ser. No. 17/962,827 filed Oct. 10, 2022 and titled DEVICE, SYSTEM, AND METHOD FOR OPTIMIZING OPERATION OF PRODUCTION EQUIPMENT; U.S. patent application Ser. No. 17/518,644 filed Nov. 4, 2021 and titled DEVICE, SYSTEM, AND METHOD FOR ASSESSING WORKER RISK; U.S. Pub. No. 2021/0264764 filed May 6, 2021 and titled DEVICE, SYSTEM, AND METHOD FOR HEALTH AND SAFETY MONITORING; U.S. Pat. No. 11,030,875, filed on Nov. 20, 2019 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE; U.S. Pat. No. 10,522,024 filed on Sep. 7, 2018 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE; and U.S. Pat. No. 10,096,230 filed on Jun. 6, 2017 and titled SAFETY DEVICE, SYSTEM, AND METHOD OF USE, each of which is hereby incorporated by reference herein in its entirety, including any figures, tables, or drawings or other information.
| Number | Date | Country | |
|---|---|---|---|
| 63438294 | Jan 2023 | US |
