Abstract: Providing contextual help in an interactive voice system includes receiving a plurality of user interaction events during a user interaction window, wherein each of the user interaction events comprises one of a low quality voice transcription event from a speech-to-text (STT) service or a no-intent matching event from a natural language processing (NLP) service and receiving a respective transcription confidence score from the STT service for each of the plurality of user interaction events. For a one of the plurality of user interaction events, a determination is made of how to respond to a user providing the user interaction events based on how many events comprise the plurality of events and the transcription confidence score for the one event; and then instructions are provided to cause the determined response to be presented to the user in accordance with the determination of how to respond.

Abstract: An approach is provided for using a machine learning model to reduce food waste. Estimation models for food items are created by using a machine learning model. The estimation models have prediction functions specifying timelines during which the food items are not spoiled and are in a condition for consumption. Prediction function solutions are generated for a food item inventory to indicate menu items for respective time periods. Each menu item includes food item(s) which are in condition for consumption based on the estimation models. Menu recommendations corresponding to the time periods are generated. Each menu includes menu item(s) indicated by the prediction function solutions. The menu recommendations reduce a waste of the food items through spoilage by increasing a likelihood of consumption of the food items within the respective timelines.

Abstract: Embodiments generally relate to securing a geophysical presence of a user. In some embodiments, a method includes receiving information associated with the user in a physical environment. The method further includes generating a unique pattern in response to receiving the information associated with the user. The method further includes sending encoded information containing the unique pattern to a landmark device in the physical environment, where the encoded information causes the landmark device to present the unique pattern. The method further includes receiving captured data from the physical environment. The method further includes verifying an identity and a physical presence of the user in the physical environment based on the captured data, where the captured data includes the landmark device.

Abstract: Embodiments generally relate to securing a geophysical presence of a user. In some embodiments, a method includes receiving information associated with the user in a physical environment. The method further includes generating a unique pattern in response to receiving the information associated with the user. The method further includes sending encoded information containing the unique pattern to a landmark device in the physical environment, where the encoded information causes the landmark device to present the unique pattern. The method further includes receiving captured data from the physical environment. The method further includes verifying an identity and a physical presence of the user in the physical environment based on the captured data, where the captured data includes the landmark device.

Abstract: An example operation may include one or more of receiving edge data that has been captured by one or more edge devices in an Internet of Things (IoT) network, encrypting the received edge data and storing the encrypted edge data as one or more transactions within a blockchain, determining, by a blockchain node, that an event has been captured by the received edge data based on metadata of the received edge data, and in response to determining that the event has been captured, generating a notification associated with the event being captured and outputting the generated notification for display on a user device.

Abstract: An approach is provided for using a machine learning model to reduce food waste. Estimation models for food items are created by using a machine learning model. The estimation models have prediction functions specifying timelines during which the food items are not spoiled and are in a condition for consumption. Prediction function solutions are generated for a food item inventory to indicate menu items for respective time periods. Each menu item includes food item(s) which are in condition for consumption based on the estimation models. Menu recommendations corresponding to the time periods are generated. Each menu includes menu item(s) indicated by the prediction function solutions. The menu recommendations reduce a waste of the food items through spoilage by increasing a likelihood of consumption of the food items within the respective timelines.

Abstract: An example operation may include one or more of storing encrypted IoT data as transactions in a blockchain, the IoT data being captured by one or more edge devices of an IoT network, receiving an identification of an event, and in response, retrieving encrypted IoT transaction data stored in the blockchain which is associated with the event, decrypting, via a blockchain node, the retrieved IoT transaction data associated with the event and generating anonymized data of the event from the decrypted IoT transaction data in which personally identifiable information is anonymized, and outputting information concerning the anonymized data of the event to one or more of a user device and a display device.

Abstract: Providing contextual help in an interactive voice system includes receiving a plurality of user interaction events during a user interaction window, wherein each of the user interaction events comprises one of a low quality voice transcription event from a speech-to-text (STT) service or a no-intent matching event from a natural language processing (NLP) service and receiving a respective transcription confidence score from the STT service for each of the plurality of user interaction events. For a one of the plurality of user interaction events, a determination is made of how to respond to a user providing the user interaction events based on how many events comprise the plurality of events and the transcription confidence score for the one event; and then instructions are provided to cause the determined response to be presented to the user in accordance with the determination of how to respond.

Abstract: Embodiments generally relate to securing a geophysical presence of a user. In some embodiments, a method includes receiving information associated with the user in a physical environment. The method further includes generating a unique pattern in response to receiving the information associated with the user. The method further includes sending encoded information containing the unique pattern to a landmark device in the physical environment, where the encoded information causes the landmark device to present the unique pattern. The method further includes receiving captured data from the physical environment. The method further includes verifying an identity and a physical presence of the user in the physical environment based on the captured data, where the captured data includes the landmark device.

Abstract: Embodiments generally relate to securing a geophysical presence of a user. In some embodiments, a method includes receiving information associated with the user in a physical environment. The method further includes generating a unique pattern in response to receiving the information associated with the user. The method further includes sending encoded information containing the unique pattern to a landmark device in the physical environment, where the encoded information causes the landmark device to present the unique pattern. The method further includes receiving captured data from the physical environment. The method further includes verifying an identity and a physical presence of the user in the physical environment based on the captured data, where the captured data includes the landmark device.

Abstract: An example operation may include one or more of storing encrypted IoT data as transactions in a blockchain, the IoT data being captured by one or more edge devices of an IoT network, receiving an identification of an event, and in response, retrieving encrypted IoT transaction data stored in the blockchain which is associated with the event, decrypting, via a blockchain node, the retrieved IoT transaction data associated with the event and generating anonymized data of the event from the decrypted IoT transaction data in which personally identifiable information is anonymized, and outputting information concerning the anonymized data of the event to one or more of a user device and a display device.

Abstract: An example operation may include one or more of receiving edge data that has been captured by one or more edge devices in an Internet of Things (IoT) network, encrypting the received edge data and storing the encrypted edge data as one or more transactions within a blockchain, determining, by a blockchain node, that an event has been captured by the received edge data based on metadata of the received edge data, and in response to determining that the event has been captured, generating a notification associated with the event being captured and outputting the generated notification for display on a user device.

Abstract: A screed assembly includes a screed assembly frame and a screed plate removably connected to the screed assembly frame to define a space between the screed assembly frame and the screed plate. A heating element and a hold down device for securing the heating element can be provided in the space between the screed assembly frame and the screed plate. The heating element is configured to be removed from the space by sliding the heating element out of the space and disengaging the heating element from the hold down device without removing the screed plate from the screed assembly frame.

Abstract: A screed assembly includes a screed assembly frame and a screed plate removably connected to the screed assembly frame to define a space between the screed assembly frame and the screed plate. A heating element and a hold down device for securing the heating element can be provided in the space between the screed assembly frame and the screed plate. The heating element is configured to be removed from the space by sliding the heating element out of the space and disengaging the heating element from the hold down device without removing the screed plate from the screed assembly frame.