ABSTRACT
Abstract
An Internet of Thing (IoT) device includes a camera coupled to a processor; and a wireless transceiver coupled to the processor. Blockchain smart contracts can be used with the device to facilitate secure operation.
Description
The present application claims priority to application Ser. No. 15/594,214 and Ser. No. 15/594,311 and Ser. No. 15/973,524, the content of which is incorporated by reference.
BACKGROUND
The emergence of smart devices such as Internet of Things (IOT) devices has provided intelligence to many common appliances and gears for sports.
IOT devices have appeared with features of autonomous operation. For example, smart sport gears monitor the users' behavior and improve or aid user performance. Smart cars can drive autonomously. Many other convenient and timesaving features are appearing in IOT devices.
In a parallel trend, the wealth of data generated by IOT devices can overwhelm the Internet cloud. Moreover, fraudulent and harmful activities arising from hacked IOT devices have potential to cause major disruptions to the Internet.
SUMMARY
In one aspect, an Internet of Thing (IoT) device includes a processor, sensor(s), and a wireless transceiver coupled to the processor.
These and other features of the present invention will become readily apparent upon further review of the following specification and drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 A illustrates an exemplary environment for communicating data from a monitoring device to external computers,
FIG. 1 B is a schematic view of an exemplary IoT sport device system, and FIG. 1 C is an exemplary process supported by the IoT device.
FIG. 2 A is a block diagram of an electronic circuit for a smart device, while FIG. 2 B is a block diagram of a big data system for predicting stress experienced by a structural unit such as a bridge, a building, or a plane, for example.
FIG. 3 is a flowchart illustrating one operation of the system of FIG. 2 A- 2 B in detecting stress on a unit.
FIG. 4 shows an exemplary sports diagnosis and trainer system for augmented and/or virtual reality, FIG. 5 shows an exemplary process for augmented and/or virtual reality for viewers participating in a game, and FIG. 6 shows an exemplary process to identify reasons for sensor data changes using a gaming process.
FIG. 7 shows an exemplary smart band,
FIG. 8 shows an exemplary glove,
FIG. 9 shows exemplary smart clothing, and
FIG. 10 shows exemplary smart balls.
FIG. 11 A shows exemplary smart rackets while FIG. 11 B shows electronics in the handle for golf clubs, rackets, or kung fu sticks.
FIGS. 12 A- 12 B show exemplary protective gears, while FIG. 12 C shows an exemplary process to fabricate mass-customized protective gear;
FIGS. 13 A- 13 I show exemplary blockchain smart contract processes.
FIGS. 13 J- 13 N show exemplary chain of custody (CCC) and supply chain tracking system of drugs such as cannabis.
FIGS. 14 A- 14 H show exemplary IF systems with blockchain and flowcharts detailing their operations.
FIGS. 14 I- 14 J show exemplary blockchain energy delivery systems.
FIG. 15 A shows an exemplary virtual reality camera mounted on a gear, and FIG. 1 H shows exemplary augmented reality real-time coaching of a player such as a quarterback during fourth down.
FIGS. 16 A- 16 C shows exemplary coaching system for skiing, bicycling, and weightlifting/free style exercise, respectively, while FIG. 16 D shows a kinematic modeling for detecting exercise motion which in turn allows precision coaching suggestions.
Similar reference characters denote corresponding features consistently throughout the attached drawings.
DETAILED DESCRIPTION
FIG. 1 A illustrates an exemplary environment for communicating data from a monitoring device to external computers. In FIG. 1 A , the monitoring device used for a sport device 9 includes an interface with a radio transmitter for forwarding the result of the comparison to a remote device. In one example, the monitoring device may include an additional switch and user interface. The user interface may be used by the user in order to trigger transmission of the comparison of the hand or foot pattern reference data with the stroke patterns data to the remote device. Alternatively, the transmission may occur automatically each time the device has been used, or may be triggered by placing the sport device in a cradle or base. All parts of the monitoring device may be encapsulated with each other and/or may be integrated into or attached to the body of the sport device 9 . Alternatively, a radio transmitter may be arranged separately from the other parts, for instance, in a battery charger, cradle or base of the sport device 9 . In that example, the interface 7 may include contact terminals in the sport device 9 , which are connected to the corresponding terminals in the battery charger for forwarding the result of the comparison via a wired connection to the transmitter in the battery charger or may be connected by induction or short range wireless communications. The radio transmitter in the battery charger then transmits this comparison result further via the wireless radio connection to the remote device. In FIG. 1 A , the remote device may be a mobile phone 16 , PDA or computer 19 , which receives the information directly from the monitoring device via a short range radio connection, as one example of a transmitter, such as a Bluetooth or a Wifi or a Zigbee connection. In one example, the user of the remote device may receive information about how thoroughly the sport device 9 has been used or the need to provide a replacement sport device. FIG. 1 A also illustrates an alternate example of a transmitter, using an intermediate receiver 17 and a network 18 , such as a cellular radio system. Also in this example, the radio transmitter may be located in connection with the sport device 9 or alternatively in connection, with a charger, cradle or base station of the sport device 9 . In such an example, the comparison result may be transmitted via an intermediate receiver 17 and the network 18 to a remote device
19 , 16 located further away than the range of a short range radio system, for example. The remove device
19 , 16 may be any device suitable for receiving the signals from the network 18 and providing feedback on an output device. The transmission of information via a cellular radio system to the remote device may allow an advertiser provide an advertisement. For example, an advertisement may be added to the comparison result using network elements in the cellular radio system. The user may receive an advertisement with the comparison result. An advantage with such a solution is that the advertiser may provide revenue offsetting all or a portion of the cost for the transmission of the comparison result from the sport device 9 to the remote device
19 , 16 .
FIG. 1 B shows a block diagram of the unit 9 with processor/RAM/ROM II. The unit 9 includes a motion sensor, a multi-axis accelerometer, and a strain gage 42 . The multi-axis accelerometer may be a two-axis or three-axis accelerometer. Strain gage 21 is mounted in the neck of the racket, and measures force applied to the ball, i.e., force in a z direction. Acceleration and force data are acquired by the microprocessor at a data acquisition rate (sampling rate) of from about 10 to 50 samples/second, e.g., about 2D samples/second. The acceleration data is used to infer motion, using an algorithm discussed below; it is not converted to position data. In this embodiment, because the sensors and strain gage are not in the head region, the head can be removable and replaceable, e.g., by threaded engagement with the handle (not shown), so that the sport device can continue to be used after instrument wear has occurred. Any desired type of removable head or cartridge can be used.
The unit 11 also includes a camera, which can be a 360 degree camera. Alternatively, the camera can be a 3D camera such as the Kinect camera or the Intel RealSense camera for ease of generating 3D models and for detecting distance of objects. To reduce image processing load, each camera has a high performance GPU to perform local processing, and the processed images, sound, and odor data are uploaded to a cloud storage for subsequent analysis.
The unit 11 includes an electronic nose to detect odor. The electronic nose can simply be a MEMS device acting as a particle counter. An embodiment of the electronic nose can be used that includes a fan module, a gas molecule sensor module, a control unit and an output unit. The fan module is used to pump air actively to the gas molecule sensor module. The gas molecule sensor module detects the air pumped into by the fan module. The gas molecule sensor module at least includes a gas molecule sensor which is covered with a compound. The compound is used to combine preset gas molecules. The control unit controls the fan module to suck air into the electronic nose device. Then the fan module transmits an air current to the gas molecule sensor module to generate a detected data. The output unit calculates the detected data to generate a calculation result and outputs an indicating signal to an operator or compatible host computer according to the calculation result.
FIG. 1 C schematically shows a method or app 2 which may be implemented by the computing unit 11 shown in FIG. 1 B . For example, the app 2 may be a computer implemented method. A computer program may be provided for executing the app 2 . The app 2 includes code for:
( 21 ) capture user motion with accelerometer or gyroscope
( 22 ) capture VR views through camera and process using GPU
( 23 ) capture user emotion using facial recognition or GSR
( 24 ) model user action using kinematic model
( 25 ) compare user action with idea action
( 26 ) coach user on improvement to user sport techniques.
The device can negotiate and enforce agreements with others blockchain smart contracts. The system may include one or more of the following:
code to determine trade settlement amounts and transfers funds automatically,
code to automatically pay coupon payments and returns principal upon bond expiration,
code to determine payout based on claim type and policy coverage,
code to collect insurance based on usage and upon a claim submission, code to determine payout based on claim type and policy coverage,
code to transfer electronic medical record from a source to a destination based on patient consent,
code to anonymously store wearable health data from wearable devices for public health monitoring,
a secured content and code to determine and distributes royalty to an author,
c
The present application claims priority to application Ser. No. 15/594,214 and Ser. No. 15/594,311 and Ser. No. 15/973,524, the content of which is incorporated by reference.
BACKGROUND
The emergence of smart devices such as Internet of Things (IOT) devices has provided intelligence to many common appliances and gears for sports.
IOT devices have appeared with features of autonomous operation. For example, smart sport gears monitor the users' behavior and improve or aid user performance. Smart cars can drive autonomously. Many other convenient and timesaving features are appearing in IOT devices.
In a parallel trend, the wealth of data generated by IOT devices can overwhelm the Internet cloud. Moreover, fraudulent and harmful activities arising from hacked IOT devices have potential to cause major disruptions to the Internet.
SUMMARY
In one aspect, an Internet of Thing (IoT) device includes a processor, sensor(s), and a wireless transceiver coupled to the processor.
These and other features of the present invention will become readily apparent upon further review of the following specification and drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 A illustrates an exemplary environment for communicating data from a monitoring device to external computers,
FIG. 1 B is a schematic view of an exemplary IoT sport device system, and FIG. 1 C is an exemplary process supported by the IoT device.
FIG. 2 A is a block diagram of an electronic circuit for a smart device, while FIG. 2 B is a block diagram of a big data system for predicting stress experienced by a structural unit such as a bridge, a building, or a plane, for example.
FIG. 3 is a flowchart illustrating one operation of the system of FIG. 2 A- 2 B in detecting stress on a unit.
FIG. 4 shows an exemplary sports diagnosis and trainer system for augmented and/or virtual reality, FIG. 5 shows an exemplary process for augmented and/or virtual reality for viewers participating in a game, and FIG. 6 shows an exemplary process to identify reasons for sensor data changes using a gaming process.
FIG. 7 shows an exemplary smart band,
FIG. 8 shows an exemplary glove,
FIG. 9 shows exemplary smart clothing, and
FIG. 10 shows exemplary smart balls.
FIG. 11 A shows exemplary smart rackets while FIG. 11 B shows electronics in the handle for golf clubs, rackets, or kung fu sticks.
FIGS. 12 A- 12 B show exemplary protective gears, while FIG. 12 C shows an exemplary process to fabricate mass-customized protective gear;
FIGS. 13 A- 13 I show exemplary blockchain smart contract processes.
FIGS. 13 J- 13 N show exemplary chain of custody (CCC) and supply chain tracking system of drugs such as cannabis.
FIGS. 14 A- 14 H show exemplary IF systems with blockchain and flowcharts detailing their operations.
FIGS. 14 I- 14 J show exemplary blockchain energy delivery systems.
FIG. 15 A shows an exemplary virtual reality camera mounted on a gear, and FIG. 1 H shows exemplary augmented reality real-time coaching of a player such as a quarterback during fourth down.
FIGS. 16 A- 16 C shows exemplary coaching system for skiing, bicycling, and weightlifting/free style exercise, respectively, while FIG. 16 D shows a kinematic modeling for detecting exercise motion which in turn allows precision coaching suggestions.
Similar reference characters denote corresponding features consistently throughout the attached drawings.
DETAILED DESCRIPTION
FIG. 1 A illustrates an exemplary environment for communicating data from a monitoring device to external computers. In FIG. 1 A , the monitoring device used for a sport device 9 includes an interface with a radio transmitter for forwarding the result of the comparison to a remote device. In one example, the monitoring device may include an additional switch and user interface. The user interface may be used by the user in order to trigger transmission of the comparison of the hand or foot pattern reference data with the stroke patterns data to the remote device. Alternatively, the transmission may occur automatically each time the device has been used, or may be triggered by placing the sport device in a cradle or base. All parts of the monitoring device may be encapsulated with each other and/or may be integrated into or attached to the body of the sport device 9 . Alternatively, a radio transmitter may be arranged separately from the other parts, for instance, in a battery charger, cradle or base of the sport device 9 . In that example, the interface 7 may include contact terminals in the sport device 9 , which are connected to the corresponding terminals in the battery charger for forwarding the result of the comparison via a wired connection to the transmitter in the battery charger or may be connected by induction or short range wireless communications. The radio transmitter in the battery charger then transmits this comparison result further via the wireless radio connection to the remote device. In FIG. 1 A , the remote device may be a mobile phone 16 , PDA or computer 19 , which receives the information directly from the monitoring device via a short range radio connection, as one example of a transmitter, such as a Bluetooth or a Wifi or a Zigbee connection. In one example, the user of the remote device may receive information about how thoroughly the sport device 9 has been used or the need to provide a replacement sport device. FIG. 1 A also illustrates an alternate example of a transmitter, using an intermediate receiver 17 and a network 18 , such as a cellular radio system. Also in this example, the radio transmitter may be located in connection with the sport device 9 or alternatively in connection, with a charger, cradle or base station of the sport device 9 . In such an example, the comparison result may be transmitted via an intermediate receiver 17 and the network 18 to a remote device
19 , 16 located further away than the range of a short range radio system, for example. The remove device
19 , 16 may be any device suitable for receiving the signals from the network 18 and providing feedback on an output device. The transmission of information via a cellular radio system to the remote device may allow an advertiser provide an advertisement. For example, an advertisement may be added to the comparison result using network elements in the cellular radio system. The user may receive an advertisement with the comparison result. An advantage with such a solution is that the advertiser may provide revenue offsetting all or a portion of the cost for the transmission of the comparison result from the sport device 9 to the remote device
19 , 16 .
FIG. 1 B shows a block diagram of the unit 9 with processor/RAM/ROM II. The unit 9 includes a motion sensor, a multi-axis accelerometer, and a strain gage 42 . The multi-axis accelerometer may be a two-axis or three-axis accelerometer. Strain gage 21 is mounted in the neck of the racket, and measures force applied to the ball, i.e., force in a z direction. Acceleration and force data are acquired by the microprocessor at a data acquisition rate (sampling rate) of from about 10 to 50 samples/second, e.g., about 2D samples/second. The acceleration data is used to infer motion, using an algorithm discussed below; it is not converted to position data. In this embodiment, because the sensors and strain gage are not in the head region, the head can be removable and replaceable, e.g., by threaded engagement with the handle (not shown), so that the sport device can continue to be used after instrument wear has occurred. Any desired type of removable head or cartridge can be used.
The unit 11 also includes a camera, which can be a 360 degree camera. Alternatively, the camera can be a 3D camera such as the Kinect camera or the Intel RealSense camera for ease of generating 3D models and for detecting distance of objects. To reduce image processing load, each camera has a high performance GPU to perform local processing, and the processed images, sound, and odor data are uploaded to a cloud storage for subsequent analysis.
The unit 11 includes an electronic nose to detect odor. The electronic nose can simply be a MEMS device acting as a particle counter. An embodiment of the electronic nose can be used that includes a fan module, a gas molecule sensor module, a control unit and an output unit. The fan module is used to pump air actively to the gas molecule sensor module. The gas molecule sensor module detects the air pumped into by the fan module. The gas molecule sensor module at least includes a gas molecule sensor which is covered with a compound. The compound is used to combine preset gas molecules. The control unit controls the fan module to suck air into the electronic nose device. Then the fan module transmits an air current to the gas molecule sensor module to generate a detected data. The output unit calculates the detected data to generate a calculation result and outputs an indicating signal to an operator or compatible host computer according to the calculation result.
FIG. 1 C schematically shows a method or app 2 which may be implemented by the computing unit 11 shown in FIG. 1 B . For example, the app 2 may be a computer implemented method. A computer program may be provided for executing the app 2 . The app 2 includes code for:
( 21 ) capture user motion with accelerometer or gyroscope
( 22 ) capture VR views through camera and process using GPU
( 23 ) capture user emotion using facial recognition or GSR
( 24 ) model user action using kinematic model
( 25 ) compare user action with idea action
( 26 ) coach user on improvement to user sport techniques.
The device can negotiate and enforce agreements with others blockchain smart contracts. The system may include one or more of the following:
code to determine trade settlement amounts and transfers funds automatically,
code to automatically pay coupon payments and returns principal upon bond expiration,
code to determine payout based on claim type and policy coverage,
code to collect insurance based on usage and upon a claim submission, code to determine payout based on claim type and policy coverage,
code to transfer electronic medical record from a source to a destination based on patient consent,
code to anonymously store wearable health data from wearable devices for public health monitoring,
a secured content and code to determine and distributes royalty to an author,
code for storing a stock certificate number with stock quantity,
code to determine a share registry or a capitalization table from each stock certificate number and stock quantity,
code to distribute shareholder communication from a share registry or a capitalization table,
code to collect secure shareholder votes from a share registry or a capitalization table for transparent corporate governance,
code to provide financial information to shareholder a share registry or a capitalization table for corporate governance,
code to enforce majority or supermajority shareholder votes from a share registry or a capitalization table for corporate governance,
code for supply chain management,
code for tracking chain of custody for an item, or
code for peer-to-peer transactions for between two computers.
As shown in FIG. 2 A , a microcontroller 155 receives and processes signals from the sensor 112 - 114 , and converts those signals into an appropriate digital electronic format. The microcontroller 155 wirelessly transmits tension information in the appropriate digital electronic format, which may be encoded or encrypted for secure communications, corresponding to the sensed traffic and/or crime indication through a wireless communication module or transceiver 160 and antenna 170 . Optionally, a camera 140 can be provided to visually detect traffic and/or crime and movement of the structure. While monitoring of the smart device 100 traffic and/or crime is continuous, transmission of tension information can be continuous, periodic or event-driven, such as when the tension enters into a warning or emergency level. Typically the indicated tension enters a warning level, then an emergency level as tension drops below the optimal range, but corresponding warning and emergency levels above the optimal range can also be used if supported by the smart device 100 . The microcontroller 155 is programmed with the appropriate warning and emergency levels, as well as internal damage diagnostics and self-recovery features.
The sensor 112 - 114 , transceiver 160 / antenna 170 , and microcontroller 155 are powered by and suitable power source, which may optionally include an electromagnetic field (EMF) scavenging device 145 , such as those known in the art, that convert ambient EMF (such as that emitted by radio station broadcasts) into small amounts of electrical power. The EMF scavenging device 145 includes a battery to buffer and store energy for the microcontroller 155 , sensor 112 - 114 , camera 140 and wireless communications 160 / 170 , among others.
The circuit of FIG. 2 A contains an analog front-end (âAFEâ) transducer 150 for interfacing signals from the sensor 112 - 114 to the microcontroller 155 . The AFE 150 electrically conditions the signals coming from the sensor 112 - 114 prior to their conversion by the microcontroller 155 so that the signals are electrically compatible with the specified input ranges of the microcontroller 155 . The microcontroller 155 can have a CPU, memory and peripheral circuitry. The microcontroller 155 is electrically coupled to a wireless communication module 160 using either a standard or proprietary communication standard. Alternatively, the microcontroller 155 can include internally any or all circuitry of the smart device 100 , including the wireless communication module 160 . The microcontroller 155 preferably includes power savings or power management circuitry 145 and modes to reduce power consumption significantly when the microcontroller 155 is not active or is less active. The microcontroller 155 may contain at least one Analog-to-Digital Converter (ADC) channel for interfacing to the AFE 150 .
The battery/ power management module 145 preferably includes the electromagnetic field (EMF) scavenging device, but can alternatively run off of previously stored electrical power from the battery alone. The battery/ power management module 145 powers all the circuitry in the smart device 100 , including the camera 140 , AFE 150 , microcontroller 155 , wireless communication module IR and antenna 170 . Even though the smart device 100 is preferably powered by continuously harvesting RF energy, it is beneficial to minimize power consumption. To minimize power consumption, the various tasks performed by the circuit should be repeated no more often than necessary under the circumstances.
Stress information from the smart device 100 and other information from the microcontroller 155 is preferably transmitted wirelessly through a wireless communication module 160 and antenna 170 . As stated above, the wireless communication component can use standard or proprietary communication protocols. Smart lids 100 can also communicate with each other to relay information about the current status of the structure or machine and the smart device 100 themselves. In each smart device 100 , the transmission of this information may be scheduled to be transmitted periodically. The smart lid 100 has a data storage medium (memory) to store data and internal status information, such as power levels, while the communication component is in an OFF state between transmission periods.
The electronic of FIG. 2 A operates with a big data discovery system of FIG. 2 B that determines events that may lead to failure. FIG. 2 B is a block diagram of an example stress monitoring system 200 that may be process the stress detected by the smart device 100 of FIG. 1 , arranged in accordance with at least some embodiments described herein. Along with the stress monitoring system 220 , a first smart device such as a smart device 240 , a second smart device 250 , a third smart device HO, a fourth smart device HO, and additional sensors 270 may also be associated with the unit 200 . The stress monitoring system 220 may include, but is not limited to, a transceiver module 222 , a stress detection module 224 , a stress prediction module 226 , a determination module 22 B, a stress response module 232 , an interface module 234 , a processor 236 , and a memory 23 B.
The transceiver module 222 may be configured to receive a stress report from each of the first, second, and third sport smart devices 240 , 250 , 260 . In some embodiments, the transceiver module 222 may be configured to receive the stress reports over a wireless network. For example, the transceiver module 222 and the first, second, and third smart devices 240 , 250 , 260 may be connected over a wireless network using the IEEE 802.11 or IEEE 802.15 standards, for example, among potentially other standards. Alternately or additionally, the transceiver module 222 and the first, second, and third smart devices 240 , 250 , 260 may communicate by sending communications over conductors used to carry electricity to the first, second, and third smart devices 240 , 250 , 260 and to other electrical devices in the unit 200 . The transceiver module 222 may send the stress reports from the first, second, and third smart devices 240 , 250 , 260 to the prediction module 226 , the stress detection module 224 , and/or the determination module 228 .
The stress module 224 may be configured to detect stress on the sport object as detected by the devices 100 . The signal sent by the devices 100 collectively may indicate the amount of stress being generated and/or a prediction of the amount of stress that will be generated. The stress detection module 224 may further be configured to detect a change in stress of non-smart devices associated with the unit 200 .
The prediction module 226 may be configured to predict future stress based on past stress history as detected, environmental conditions, forecasted stress loads, among other factors. In some embodiments, the prediction module 226 may predict future stress by building models of usage and weight being transported. For example, the prediction module 226 may build models using machine learning based on support vector machines, artificial neural networks, or using other types of machine learning. For example, stress may correlate with the load carried by a bridge or an airplane structure. In other example, stress may correlate with temperature cycling when a structure is exposed to constant changes (such as that of an airplane).
The prediction module 226 may gather data for building the model to predict stress from multiple sources. Some of these sources may include, the first, second, and third smart devices 240 , 250 , 260 ; the stress detection module 224 ; networks, such as the World Wide Web; the interface module 234 ; among other sources. For example, the first, second, and third smart devices 240 , 250 , 260 may send information regarding human interactions with the first, second, and third smart devices 240 , 250 , 260 . The human interactions with the first, second, and third smart devices 240 , 250 , 260 may indicate a pattern of usage for the first, second, and third smart devices 240 , 250 , 260 and/or other human behavior with respect to stress in the unit 200 .
In some embodiments, the first, second, and third smart devices 240 , 250 , 260 may perform predictions for their own stress based on history and send their predicted stress in reports to the transceiver module 222 . The prediction module 226 may use the stress reports along with the data of human interactions to predict stress for the system 200 . Alternately or additionally, the prediction module 226 may make predictions of stress for the first, second, and third smart devices 240 , 250 , 260 based on data of human interactions and passed to the transceiver module 222 from the first, second, and third smart devices 240 , 250 , 260 . A discussion of predicting stress for the first, second, and third smart devices 240 , 250 , 260 is provided below with respect to FIGS. 5 and 6 .
The prediction module 224 may predict the stress for different amounts of time. For example, the prediction module 224 may predict stress of the system 200 for 1 hour, 2 hours, 12 hours, 1 day, or some other period. The prediction module 224 may also update a prediction at a set interval or when new data is available that changes the prediction. The prediction module 224 may send the predicted stress of the system 200 to the determination module 22 B. In some embodiments, the predicted stress of the system 200 may contain the entire stress of the system 200 and may incorporate or be based on stress reports from the first, second, and third smart devices 240 , 250 , 260 . In other embodiments, the predicted stress of the system 200 may not incorporate or be based on the stress reports from the first, second, and third smart devices 240 , 250 , 260 .
The determination module 228 may be configured to generate a unit stress report for the system 200 . The determination module 228 may use the current stress of the system 200 , the predicted stress of the system 200 received from the prediction module 224 ; stress reports from the first, second, and/or third smart devices 240 , 250 , 260 , whether incorporated in the predicted stress of the system 200 or separate from the predicted stress of the system 200 ; and an amount of stress generated or the predicted amount of stress, to generate a unit stress report.
In some embodiments, one or more of the stress reports from the first, second, and/or third smart device 240 , 250 , 260 may contain an indication of the current operational profile and not stress. In these and other embodiments, the determination module 228 may be configured to determine the stress of a smart device for which the stress report indicates the current operational profile but not the stress. The determination module 228 may include the determined amount of stress for the smart device in the unit stress report. For example, both the first and second smart device 240 , 250 may send stress report. The stress report from the first smart device 240 may indicate stress of the first smart device 240 . The stress report from the second smart device 250 may indicate the current operational profile but not the stress of the second smart device 250 . Based on the current operational profile of the second smart device 250 , the determination module 228 may calculate the stress of the second smart device 250 . The determination module 228 may then generate a unit stress report that contains the stress of both the first and second smart devices 240 , 250 .
In some embodiments, the stress monitoring system 220 may not include the prediction module 226 . In these and other embodiments, the determination module 228 may use stress reports from the first, second, and/or third smart devices 240 , 250 , 260 , with the received amount of stress inferred on non-smart devices, if any, to generate the unit stress report. The determination module 228 may send the unit stress report to the transceiver module 222 .
In some embodiments, the processor 236 may be configured to execute computer instructions that cause the stress monitoring system 220 to perform the functions and operations described herein. The computer instructions may be loaded into the memory 23 B for execution by the processor 236 and/or data generated, received, or operated on during performance of the functions and operations described herein may be at least temporarily stored in the memory 23 B.
Although the stress monitoring system 220 illustrates various discrete components, such as the prediction module 226 and the determination module 22 B, various components may be divided into additional components, combined into fewer components, or eliminated, depending on the desired implementation. In some embodiments, the unit 200 may be associated with more or less smart devices than the three smart devices 240 , 250 , 260 illustrated in FIG. 2 .
FIG. 3 is a flow chart of an example method 300 of monitoring stress of a sport or game unit, arranged in accordance with at least some embodiments described herein. The method 300 may be implemented, in some embodiments, by an stress monitoring system, such as the stress monitoring system 220 of FIG. 2 . For instance, the processor 236 of FIG. 2 B may be configured to execute computer instructions to perform operations for monitoring stress as represented by one or more of
blocks
302 , 304 , 306 , 310 , 312 , and/or 314 of the method 300 . Although illustrated as discrete blocks, various blocks may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the desired implementation.
The method 300 may begin at one or more of blocks
302 , 304 , and/or 306 . The blocks
302 , 304 , and/or 306 may occur at the same time or at different times and may or may not depend on one another. Furthermore, one or more of the
block
302 , 304 , 306 may occur during the method 300 . For example, the method 300 may complete when
blocks
304 , 310 , and 312 occurs and without the occurrence of block
302 and 306 .
In block 302 , a change in stress of a device (device or beam) associated with a unit may be detected. A non-smart device may by any device that receives stress and does not generate an stress report indicating its stress, for example a legacy racket without IoT electronics. A change in the stress of a non-smart device may be detected using an stress detection module and/or usage meter associated with the unit, such as the stress detection module 224 and/or the smart device 100 . For example, non-smart device stress can be estimated by the load the unit carries, the temperature cycling experienced by the unit, for example.
After a change in stress of the non-smart device is detected, the method 300 proceeds to block 310 . In block 304 , a stress report from a smart device such as the smart device 100 associated with the unit may be received. A smart device may be a device that detects stress and generates and transmits an stress report indicating the stress on the smart device. The stress report may indicate predicted future stress of the smart device. In some embodiments, a stress report may be received at set intervals from the smart device regardless of a change in the stress report. Alternately or additionally, a stress report may be received after a change in the stress of the smart device results in a change to the stress report. After a stress report is received from the smart device, the method 300 proceeds to block 310 .
In block 306 , stress experienced at the unit may be detected. Stress at the unit may be detected using a stress detection module, such as the stress detection module 224 of FIG. 2 B . After detecting stress at the unit, the method proceeds to block 310 . At block 310 , it is determined if a change in the stress occurred. For example, if an increase in stress occurs at the same time and at the same amount as an increase in the stress of a non-smart device, a change in the stress may not occur. If a change in the stress occurs, the method 300 proceeds to block 312 . If no change occurs, the method 300 ends.
At block 312 , a unit stress report is generated for the unit. In some embodiments, the unit stress report may indicate the current stress of the unit. Alternately or additionally, the unit stress report may indicate a current and predicted future stress of the unit. At block 314 , the unit stress report is transmitted to a maintenance provider. In some embodiments, the unit stress report may be transmitted when the unit stress report indicates a change in stress for the unit that is greater than a predetermined threshold. If the unit stress report indicates a change in stress for the unit that is less than the predetermined threshold, the unit stress report may not be transmitted to the provider of maintenance services.
FIG. 5 shows in more details the computer 30 and the interface to the probe 20 . An amplifier 90 amplifies vibratory output from a transducer 92 . A pick up unit having an accelerometer (or an array) 96 receives reflected vibrations from user arm or leg 94 , among others. A computer 98 includes a digital converter to digitize output from the pick-up unit and software on the computer 98 can process the captured diagnostic data. Diagnostic software 100 can include a database of known restorations, diseases, and tissue conditions whose signatures can be matched against the capture diagnostic data, and the result can be displayed on a screen for review by the athlete.
FIG. 6 is a flowchart of a method of an embodiment of the present disclosure. Referring to FIG. 6 , a smart system may collect from smart devices state change events of a smart system in operation 601 . That is, the smart system of FIG. 4 collects information on each of the group of devices, the smart devices, the smart appliances, the security devices, the lighting devices, the energy devices, and the like. The state change events indicate when there is a change in the state of the device or the surrounding environment. The state change events are stored by the smart system. In operation 603 , the system may determine whether a series of the collected state change events are a known pattern. That is, the gateway determines whether there are events which have been correlated or identified in the past. If the collected state change events have been identified in the past, it may be necessary to determine that the smart system trusts the identification the collected state change events. The trust factor of the identification of the collected state change events may be determined by the number of users who have identified the collected state change events or the number of time collected state change events have been repeated and identified. In operation 605 , when the series of the collected state change events is an unknown pattern, request users of the smart system to identify what caused the collected state change events request. That is, the system transmits to a gamification application (hereinafter app) on the user's mobile device a request to identify the collected state change events. The gamification app displays the information and request the user enter information identifying the collected state change events. Each of the mobile devices transmits this information back to the system to the gamification module. In operation 605 , the system transmits the user's identified collected state change events to the other user's of the smart home system and they each vote on the best identification of the collected state change events. Thus, the identified collected change state events that have been repeatedly identified over a period of weeks increases, the trustworthiness of the identification increases. Likewise, if every user of the smart system makes the same identification of the collected change state events, the identified collected change state events may be considered trustworthy at point. Such a determination of a threshold for when the identified collected change state events are considered trustworthy and therefore need not be repeated, is made by a system administrator. However, it will be understood that such a trustworthiness of this type only gives higher confidence of this particular dataset at that point in time. As such further repetition is required, since the sensor data may have noise, the more datasets to be identified to the pattern, the more robust the trustworthiness will be. Until the robustness reaches a threshold, then the system can confirm this is a known trustworthy pattern.
Smart Sport Glove
FIG. 7 shows an exemplary glove which can be thin to provide touch sensitivity or thick to provide shock protection
CLAIMS
Claims ( 20 )
What is claimed is:
1. A device, comprising:
a device body;
an accelerometer coupled to the body; a camera to capture an image;
a wireless transceiver; and
a processor coupled to the body and associated with a blockchain with a blockchain address for a secured transaction by accessing data, content, or application stored in a cloud storage; authorizing a first client device; receiving an authorization request from the first client device; generating an authorization key for accessing a cloud server and storing the key in a blockchain; providing the authorization key to the first client device; receiving the authorization key from a remote device as a second client device working as an agent of the first client device; granting access to the second client device based on the authorization key; receiving code and data associated with an application or content identified in a blockchain, and running code with the data.
2. The device of claim 1 , wherein the processor accessing a digital key in trusted memory to securely sign a blockchain transaction for a contract stored on a decentralized ledger, and wherein the processor to stores events on the blockchain relating to identity wherein the identity is used for accessing a computer, building or equipment.
3. The device of claim 1 , comprising a module to manage a chain of custody of a user, where one or more images are taken of the user and immutably supplemented with location, and an identity of a person associated with the image is added as a metadata.
4. The device of claim 1 , comprising a module to manage a chain of custody for cannabis and a module to manage a chain of custody for a drug with ingredients, where one or more images are taken of drug ingredients and wherein an identity of a person associated with drug production is added as a metadata.
5. The device of claim 1 , comprising a module coupled to the camera for image tagging of one or more objects.
6. The device of claim 5 , wherein the image is stored off or on the blockchain and the image includes embedded information including a signature of a person taking the image.
7. The device of claim 5 , wherein the image includes embedded information including a positioning system coordinate and a temperature.
8. The device of claim 1 , comprising a module to process energy generation or consumption using the blockchain.
9. The device of claim 1 , comprising a module to manage a chain of custody for an object, a plant, a drug or a person.
10. The method of claim 1 , comprising a module to identify a custodian location from one or more of: a seed grower facility, a plant harvester facility, a processing facility, a distribution facility, a retail facility.
11. The device of claim 1 , comprising a sensor to perform one of: photonic, magnetic, x-ray, radio frequency, chemical, microcode, florescence, genetic, electronic analysis, spectroscopy analysis, wherein the analysis is placed on the blockchain.
12. The device of claim 1 , comprising one or more identification tags mixed or dispersed within a facility or plant.
13. The device of claim 1 , comprising medical dispensing machine to provide blockchain data on location and time of each event associated with a medication.
14. The device of claim 1 , comprising a module to trace food or drug from production to distribution to consumption using the blockchain.
15. The device of claim 1 , wherein the blockchain comprises Ethereum or Bitcoin, and the wireless transceiver comprises a cellular transceiver or 802 transceiver.
16. The device of claim 1 , comprising a module to link blockchain addresses to a store, sign cryptocurrency transactions and check a store status.
17. The device of claim 1 , comprising a distributed application (dApp).
18. The device of claim 1 , comprising a module to process a smart contract.
19. The device of claim 1 , comprising a module to transfer currency in a smart contract.
20. The device of claim 1 , comprising a smart phone with a wallet.
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( en )
Cited By (4)
* Cited by examiner, â Cited by third party
Publication number
Priority date
Publication date
Assignee
Title
US20210232662A1
( en )
*
2020-01-29
2021-07-29
Nusantao, Inc.
Methods to protect stakeholders' algorithms and information in untrusted environments
US20230027100A1
( en )
*
2019-12-24
2023-01-26
Geromics Ltd
Method and system for digital attestation
US20240119534A1
( en )
*
2022-10-05
2024-04-11
State Farm Mutual Automobile Insurance Company
Systems and methods for generating, maintaining, and using portable data on a blockchain
US12050962B1
( en )
2023-07-13
2024-07-30
Bank Of America Corporation
System and method for implementing dynamic operation identifier
Families Citing this family (298)
* Cited by examiner, â Cited by third party
Publication number
Priority date
Publication date
Assignee
Title
US8874477B2
( en )
2005-10-04
2014-10-28
Steven Mark Hoffberg
Multifactorial optimization system and method
US10303035B2
( en )
2009-12-22
2019-05-28
View, Inc.
Self-contained EC IGU
US11592723B2
( en )
2009-12-22
2023-02-28
View, Inc.
Automated commissioning of controllers in a window network
US20210063836A1
( en )
2017-04-26
2021-03-04
View, Inc.
Building network
US10852069B2
( en )
2010-05-04
2020-12-01
Fractal Heatsink Technologies, LLC
System and method for maintaining efficiency of a fractal heat sink
US10989977B2
( en )
2011-03-16
2021-04-27
View, Inc.
Onboard controller for multistate windows
US12400651B2
( en )
2012-04-13
2025-08-26
View Operating Corporation
Controlling optically-switchable devices
CN109003398B
( en )
2012-06-14
2022-04-29
ç¾å©æ¸¸æææ¯æéå ¬å¸
System and method for augmented reality games
US12576309B2
( en )
2012-07-31
2026-03-17
Peloton Interactive, Inc.
Coordinating workouts across remote exercise machines
US11064913B2
( en )
2013-10-25
2021-07-20
Force Impact Technologies, Inc.
Impact sensing wearable device and method
US11868103B2
( en )
2014-03-05
2024-01-09
View, Inc.
Site monitoring system
KR102336168B1
( en )
2014-03-05
2021-12-07
ë·°, ì¸í¬.
Monitoring sites containing switchable optical devices and controllers
US10481459B2
( en )
2014-06-30
2019-11-19
View, Inc.
Control methods and systems for networks of optically switchable windows during reduced power availability
US11740948B2
( en )
2014-12-08
2023-08-29
View, Inc.
Multiple interacting systems at a site
US9774604B2
( en )
2015-01-16
2017-09-26
Zingbox, Ltd.
Private cloud control
US10212178B2
( en )
2015-04-07
2019-02-19
Zingbox, Ltd.
Packet analysis based IoT management
US10210527B2
( en )
*
2015-06-04
2019-02-19
Chronicled, Inc.
Open registry for identity of things including social record feature
CN108140137A
( en )
2015-06-04
2018-06-08
ç¼å¹´å²å ¬å¸
Open Registry for Thing Identity
US20170011460A1
( en )
*
2015-07-09
2017-01-12
Ouisa, LLC
Systems and methods for trading, clearing and settling securities transactions using blockchain technology
US12366111B2
( en )
2015-09-18
2025-07-22
View Operating Corporation
Trunk line window controllers
CN108139988B
( en )
*
2015-10-20
2021-07-30
ç´¢å°¼å ¬å¸
Information processing system and information processing method
JP6528008B2
( en )
2016-02-23
2019-06-12
ã¨ããã§ã¼ã³ ãã¼ã«ãã£ã³ã°ã¹ ãªããããï¼®ï½ï½ï½ï½ï½ Ｈï½ï½ï½ï½ï½ï½ï½ Ｌï½ï½ï½ï½ï½ ï½
Personal Device Security Using Elliptic Curve Cryptography for Secret Sharing
US11521185B1
( en )
*
2016-05-19
2022-12-06
Citibank, N.A.
Distributed private ledger systems and methods
US11107088B2
( en )
2016-05-27
2021-08-31
Chronicled, Inc.
Open registry for internet of things
WO2017212659A1
( en )
*
2016-06-07
2017-12-14
ï¼£ï½ï½ï½ï½ ï½ï½ï½ ï½ ï¼¤ï½ ï½ï½ï½ï½æ ªå¼ä¼ç¤¾
Management device, control method, and program
US11256828B1
( en )
*
2016-07-05
2022-02-22
Wells Fargo Bank, N.A.
Method and apparatus for controlling IoT devices by agent device
CA3064810A1
( en )
*
2016-07-20
2018-01-25
Michael RUDAN
Material for enhancing the effects of exercise
US20190173884A1
( en )
*
2016-07-29
2019-06-06
nChain Holdings Limited
Blockchain-implemented method and system
WO2018020369A1
( en )
2016-07-29
2018-02-01
nChain Holdings Limited
Blockchain-implemented method and system
US10185550B2
( en )
2016-09-28
2019-01-22
Mcafee, Inc.
Device-driven auto-recovery using multiple recovery sources
US11282137B2
( en )
*
2016-10-07
2022-03-22
The Toronto-Dominion Bank
Secure element method for distributed electronic ledger
KR101849918B1
( en )
*
2016-10-26
2018-04-19
주ìíì¬ ì½ì¸íë¬ê·¸
Method for issuing and paying money in use of unspent transaction output based protocol, and server using the same
US10380348B2
( en )
2016-11-21
2019-08-13
ZingBox, Inc.
IoT device risk assessment
US11128528B2
( en )
2016-12-30
2021-09-21
Intel Corporation
Decentralized data storage and processing for IoT devices
US11468439B2
( en )
*
2017-01-12
2022-10-11
American Express Travel Related Services Company, Inc.
Systems and methods for blockchain based proof of payment
US10824759B1
( en )
2017-01-25
2020-11-03
State Farm Mutual Automobile Insurance Company
Systems and methods for verifying agent sales data via blockchain
US10419225B2
( en )
2017-01-30
2019-09-17
Factom, Inc.
Validating documents via blockchain
US11121857B2
( en )
*
2017-02-27
2021-09-14
Walmart Apollo, Llc
Systems, devices, and methods for in-field authenticating of autonomous robots
US10817873B2
( en )
2017-03-22
2020-10-27
Factom, Inc.
Auditing of electronic documents
US10531065B2
( en )
*
2017-03-30
2020-01-07
Microsoft Technology Licensing, Llc
Coarse relocalization using signal fingerprints
US10466953B2
( en )
2017-03-30
2019-11-05
Microsoft Technology Licensing, Llc
Sharing neighboring map data across devices
US10600252B2
( en )
*
2017-03-30
2020-03-24
Microsoft Technology Licensing, Llc
Coarse relocalization using signal fingerprints
US12603091B2
( en )
2017-04-26
2026-04-14
View Operating Corporation
Immersive collaboration of remote participants via media displays
US12147142B2
( en )
2017-04-26
2024-11-19
View, Inc.
Remote management of a facility
US10270599B2
( en )
2017-04-27
2019-04-23
Factom, Inc.
Data reproducibility using blockchains
JP6871379B2
( en )
*
2017-07-07
2021-05-12
ãã é«æ¨
Treatment and / or Exercise Guidance Process Management Systems, Programs, Computer Devices, and Methods for Treatment and / or Exercise Guidance Process Management
WO2019018494A1
( en )
*
2017-07-21
2019-01-24
Walmart Apollo, Llc
Rfid system printer and method
EP3662635A4
( en )
2017-07-31
2021-04-28
Chronicled, Inc.
A secure and confidential custodial transaction system, method and device using zero-knowledge protocol
US11018870B2
( en )
*
2017-08-10
2021-05-25
Visa International Service Association
Biometric verification process using certification token
US10930377B2
( en )
*
2017-08-29
2021-02-23
International Business Machines Corporation
Dental health tracking via blockchain
US10873457B1
( en )
2017-09-13
2020-12-22
Inveniam.io, LLC
Data structure having internal self-references suitable for immutably representing and verifying data generated over time
US11528147B2
( en )
*
2017-09-13
2022-12-13
Vijay Madisetti
Verifying integrity and secure operations of cloud-based software services
US11070568B2
( en )
2017-09-27
2021-07-20
Palo Alto Networks, Inc.
IoT device management visualization
USD870774S1
( en )
*
2017-09-29
2019-12-24
Apple Inc.
Wearable device with animated graphical user interface
US11082296B2
( en )
2017-10-27
2021-08-03
Palo Alto Networks, Inc.
IoT device grouping and labeling
EP3704607A1
( en )
2017-11-02
2020-09-09
Nchain Holdings Limited
Computer-implemented systems and methods for linking a blockchain to a digital twin
CN109744999A
( en )
*
2017-11-03
2019-05-14
å å®çµå(广å·)æéå ¬å¸
Wearable system, wearable device and its cloud server and operating method
US12288168B2
( en )
*
2017-11-20
2025-04-29
Obook Holdings Inc.
Blockchain-based room inventory management system and method
EP3723877B1
( en )
*
2017-12-14
2023-08-30
Peloton Interactive, Inc.
Coordinating workouts across remote exercise machines
US20200349653A1
( en )
*
2018-02-08
2020-11-05
2Bc Innovations, Llc
Servicing a portfolio of blockchain-encoded rived longevity-contingent instruments
US20200364708A1
( en )
*
2018-02-08
2020-11-19
2Bc Innovations, Llc
Generating a portfolio of blockchain-encoded rived longevity-contingent instruments
US11507540B1
( en )
*
2018-02-15
2022-11-22
EMC IP Holding Company LLC
Decentralized file system and message bus architecture for processing training sets in multi-cloud computing environment
US11283872B1
( en )
*
2018-03-12
2022-03-22
United Services Automobile Association
Media triggered device control
US11263656B1
( en )
*
2018-04-17
2022-03-01
Walgreen Co.
Coupon clearinghouse with blockchain
MX2020011144A
( en )
*
2018-04-23
2021-02-26
Overcast Holdings Llc
Automated authentication systems and methods including automated waste management system with automated weight ticket and authentication.
CN108615150A
( en )
*
2018-04-24
2018-10-02
æ·±å³å¸è½±è¾è½¦èæ°æ®ææ¯æéå ¬å¸
Vehicle related information processing method and processing device based on block chain
US10855448B2
( en )
*
2018-05-03
2020-12-01
Honeywell International Inc.
Apparatus and method for using blockchains to establish trust between nodes in industrial control systems or other systems
US11257081B2
( en )
*
2018-05-08
2022-02-22
Oracle International Corporation
Integrating a blockchain ledger with an application external to the blockchain ledger
US11170366B2
( en )
2018-05-18
2021-11-09
Inveniam Capital Partners, Inc.
Private blockchain services
US10783164B2
( en )
2018-05-18
2020-09-22
Factom, Inc.
Import and export in blockchain environments
US11134120B2
( en )
2018-05-18
2021-09-28
Inveniam Capital Partners, Inc.
Load balancing in blockchain environments
US11403444B1
( en )
*
2018-05-30
2022-08-02
Callaway Golf Company
Golf club face thickness optimization method
US11475398B2
( en )
*
2018-05-30
2022-10-18
Ncr Corporation
Product traceability processing
US11642183B2
( en )
*
2018-06-06
2023-05-09
Verily Life Sciences Llc
Systems and methods for fleet management of robotic surgical systems
US10409783B1
( en )
2018-06-06
2019-09-10
Capital One Services, Llc
Distributed work data management
WO2019246169A1
( en )
2018-06-18
2019-12-26
ZingBox, Inc.
Pattern match-based detection in iot security
JP7326707B2
( en )
*
2018-06-21
2023-08-16
ã«ã·ãªè¨ç®æ©æ ªå¼ä¼ç¤¾
Robot, robot control method and program
US12455778B2
( en )
2018-07-06
2025-10-28
Capital One Services, Llc
Systems and methods for data stream simulation
US11250466B2
( en )
2018-07-30
2022-02-15
Hewlett Packard Enterprise Development Lp
Systems and methods for using secured representations of user, asset, and location distributed ledger addresses to prove user custody of assets at a location and time
US11270403B2
( en )
2018-07-30
2022-03-08
Hewlett Packard Enterprise Development Lp
Systems and methods of obtaining verifiable image of entity by embedding secured representation of entity's distributed ledger address in image
US11488160B2
( en )
2018-07-30
2022-11-01
Hewlett Packard Enterprise Development Lp
Systems and methods for using captured time series of secured representations of distributed ledger addresses and smart contract deployed on distributed ledger network to prove compliance
US11403674B2
( en )
*
2018-07-30
2022-08-02
Hewlett Packard Enterprise Development Lp
Systems and methods for capturing time series dataset over time that includes secured representations of distributed ledger addresses
US11356443B2
( en )
2018-07-30
2022-06-07
Hewlett Packard Enterprise Development Lp
Systems and methods for associating a user claim proven using a distributed ledger identity with a centralized identity of the user
US11184175B2
( en )
2018-07-30
2021-11-23
Hewlett Packard Enterprise Development Lp
Systems and methods for using secured representations of location and user distributed ledger addresses to prove user presence at a location and time
US11233641B2
( en )
2018-07-31
2022-01-25
Hewlett Packard Enterprise Development Lp
Systems and methods for using distributed attestation to verify claim of attestation holder
US11271908B2
( en )
2018-07-31
2022-03-08
Hewlett Packard Enterprise Development Lp
Systems and methods for hiding identity of transacting party in distributed ledger transaction by hashing distributed ledger transaction ID using secured representation of distributed ledger address of transacting party as a key
US11488161B2
( en )
2018-07-31
2022-11-01
Hewlett Packard Enterprise Development Lp
Systems and methods for providing transaction provenance of off-chain transactions using distributed ledger transactions with secured representations of distributed ledger addresses of transacting parties
US11348098B2
( en )
*
2018-08-06
2022-05-31
Inveniam Capital Partners, Inc.
Decisional architectures in blockchain environments
US11989208B2
( en )
2018-08-06
2024-05-21
Inveniam Capital Partners, Inc.
Transactional sharding of blockchain transactions
US11044095B2
( en )
*
2018-08-06
2021-06-22
Factom, Inc.
Debt recordation to blockchains
US11227282B2
( en )
2018-08-20
2022-01-18
Probloch LLC
Time-bounded activity chains with multiple authenticated agent participation bound by distributed single-source-of-truth networks that can enforce automated value transfer
WO2020041127A1
( en )
*
2018-08-23
2020-02-27
Providentia Worldwide, Llc
Systems and methods for blockchain interlinking and relationships
US10528776B1
( en )
*
2018-08-28
2020-01-07
Digiprint Ip Llc
Tracking and authentication of products via distributed ledgers and NFC tags
US10572855B1
( en )
2018-08-28
2020-02-25
Digiprint Ip Llc
Tracking and authentication of inventory via distributed ledgers and NFC tags
US10250395B1
( en )
2018-08-29
2019-04-02
Accenture Global Solutions Limited
Cryptologic blockchain interoperation
US10824988B2
( en )
*
2018-08-30
2020-11-03
Ncr Corporation
Automated inventory management including blockchain smart contracting
EP3847571A4
( en )
2018-09-04
2022-06-01
Palo Alto Networks, Inc.
IoT APPLICATION LEARNING
US11442926B2
( en )
*
2018-09-05
2022-09-13
Nhn Corporation
Method and system for storing driving record data based on block chain
US11803923B1
( en )
2018-09-06
2023-10-31
Side, Inc.
Blockchain-based system and method for purchase document transformation and accountability
US10752207B2
( en )
*
2018-09-07
2020-08-25
Ford Global Technologies, Llc
Multi-factor authentication of a hardware assembly
EP3627253A1
( en )
*
2018-09-18
2020-03-25
Siemens Aktiengesellschaft
Data structure product and product kit
US10250394B1
( en )
2018-09-20
2019-04-02
Accenture Global Solutions Limited
Cryptologic self-executing blockchain export commitment
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( en )
*
2018-09-24
2022-03-04
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WO2020071409A1
( en )
*
2018-10-02
2020-04-09
ããã½ãã㯠ã¤ã³ãã¬ã¯ãã¥ã¢ã« ãããã㣠ã³ã¼ãã¬ã¼ã·ã§ã³ ãªã ã¢ã¡ãªã«
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KR102086005B1
( en )
*
2018-10-08
2020-04-23
ìµìì
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IT201800009359A1
( en )
*
2018-10-11
2020-04-11
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MX2021004168A
( en )
*
2018-10-12
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Systems and methods for using a machine-readable code in relation to a cannabis product.
CN113424157B
( en )
2018-10-15
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å¸æ´é¿å°æç½ç»å ¬å¸
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GB201816936D0
( en )
2018-10-17
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US20200126075A1
( en )
*
2018-10-18
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Confidential transaction auditing using an authenticated data structure
WO2020084446A1
( en )
*
2018-10-22
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Radient Technologies Innovations Inc.
Supply chain tracking
JP7847985B2
( en )
*
2018-10-25
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ã½ãã¼ã°ã«ã¼ãæ ªå¼ä¼ç¤¾
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US10499202B1
( en )
*
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Contact list for the internet of things
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( en )
*
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é®é
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CN109568897B
( en )
*
2018-11-03
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å¦é¨æ³¢è模å设计æéè´£ä»»å ¬å¸
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US11615882B2
( en )
*
2018-11-07
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US12008503B2
( en )
*
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