A method for monitoring operation of a machine includes receiving machine operation data including a first data channel indicative of a sensed condition at a first location on the machine, wherein the machine operation data is collected during one or more work cycles of the machine, and extracting at least a portion of the machine operation data, including data associated with the first data channel. The method also includes classifying the extracted machine operation data to identify one or more types of events that occurred during the one or more work cycles of the machine and involving an environment in which the machine operates during the one or more work cycles of the machine, estimating a condition at a second location on the machine during the one or more work cycles of the machine based on the identified one or more types of events, and logging the identified one or more types of events with a plurality of additional identified types of events to represent a plurality of work cycles during operation of the machine over time.

A method for monitoring operation of a machine includes receiving machine operation data including a first data channel indicative of a sensed condition at a first location on the machine, wherein the machine operation data is collected during one or more work cycles of the machine, and extracting at least a portion of the machine operation data, including data associated with the first data channel. The method also includes classifying the extracted machine operation data to identify one or more types of events that occurred during the one or more work cycles of the machine and involving an environment in which the machine operates during the one or more work cycles of the machine, estimating a condition at a second location on the machine during the one or more work cycles of the machine based on the identified one or more types of events, and logging the identified one or more types of events with a plurality of additional identified types of events to represent a plurality of work cycles during operation of the machine over time.

A multi-mode microwave waveguide blade sensing system includes a transceiver, a waveguide, and a probe sensor. The transceiver generates a microwave energy signal having a first waveguide mode and a different second waveguide mode. The waveguide includes a first end that receives the microwave energy signal. The probe sensor includes a proximate end that receives the microwave energy signal from the transceiver and a distal end including an aperture that outputs the microwave energy signal. The probe sensor directs the microwave energy signal at a first direction based on the first waveguide mode and a different second direction different based on the second waveguide mode. The probe sensor receives different levels of reflected microwave energy based at least in part on a location at which the at least one microwave energy signal is reflected from the machine.

A multi-mode microwave waveguide blade sensing system includes a transceiver, a waveguide, and a probe sensor. The transceiver generates a microwave energy signal having a first waveguide mode and a different second waveguide mode. The waveguide includes a first end that receives the microwave energy signal. The probe sensor includes a proximate end that receives the microwave energy signal from the transceiver and a distal end including an aperture that outputs the microwave energy signal. The probe sensor directs the microwave energy signal at a first direction based on the first waveguide mode and a different second direction different based on the second waveguide mode. The probe sensor receives different levels of reflected microwave energy based at least in part on a location at which the at least one microwave energy signal is reflected from the machine.

In some implementations, a system for validating products that are placed in a shopping cart includes a shopping cart configured to retain products and to be operated by a user in a retail environment. The shopping cart includes product validation hardware and a controller. The product validation hardware includes motion sensors positioned along a top perimeter of the shopping cart and at least one sound sensor positioned inside the shopping cart. The shopping cart is configured to receive, from the motion sensors, motion data when a product enters a top horizontal plane of the shopping cart, and to receive, from the sound sensor, audio data that is collected in real-time as the product is placed in the shopping cart. An audio signature is generated for the product, and is used to validate the product that is placed in the shopping cart.

In some implementations, a system for validating products that are placed in a shopping cart includes a shopping cart configured to retain products and to be operated by a user in a retail environment. The shopping cart includes product validation hardware and a controller. The product validation hardware includes motion sensors positioned along a top perimeter of the shopping cart and at least one sound sensor positioned inside the shopping cart. The shopping cart is configured to receive, from the motion sensors, motion data when a product enters a top horizontal plane of the shopping cart, and to receive, from the sound sensor, audio data that is collected in real-time as the product is placed in the shopping cart. An audio signature is generated for the product, and is used to validate the product that is placed in the shopping cart.

A posture estimation method includes calculating a posture change amount of an object based on an output of an angular velocity sensor, predicting posture information of the object by using the posture change amount, limiting a bias error in a manner of limiting a bias error component of an angular velocity around a reference vector in error information, and correcting the predicted posture information of the object based on the error information, the reference vector, and an output of a reference observation sensor.

A posture estimation method includes calculating a posture change amount of an object based on an output of an angular velocity sensor, predicting posture information of the object by using the posture change amount, limiting a bias error in a manner of limiting a bias error component of an angular velocity around a reference vector in error information, and correcting the predicted posture information of the object based on the error information, the reference vector, and an output of a reference observation sensor.

The invention concerns a device for measuring instantaneous sprint velocity, said device consisting of at least one position and/or one velocity sensor and one IMU sensor that respectively provide position and/or velocity and acceleration signals and wherein said signals are fused. The invention also concerns a method for measuring instantaneous sprint velocity comprising the use of at least one position and/or one velocity sensor and one IMU sensor that respectively provide position and/or velocity and acceleration signals and wherein said signals are fused.

The invention concerns a device for measuring instantaneous sprint velocity, said device consisting of at least one position and/or one velocity sensor and one IMU sensor that respectively provide position and/or velocity and acceleration signals and wherein said signals are fused. The invention also concerns a method for measuring instantaneous sprint velocity comprising the use of at least one position and/or one velocity sensor and one IMU sensor that respectively provide position and/or velocity and acceleration signals and wherein said signals are fused.