Abstract: A system includes one or more memory units and a processor. The processor is configured to receive, from a food temperature probe, a first temperature associated with a first food item. The processor is further configured to receive, from the food temperature probe, a second temperature associated with a second food item. The processor is further configured to receive, from the food temperature probe, a third temperature that was measured by the food temperature probe after measuring the first temperature but before measuring the second temperature, the third temperature associated with a cleaning of the food temperature probe. The processor is further configured to send an alert for display on a user device when the third temperature is greater than the cleaning threshold temperature.

Abstract: A system includes a rack storing items, an interaction device that processes the items, and a master controller that is configured to receive a communication signal from the rack indicating that items have been removed from the rack and determine based on monitoring communication signals from the interaction device whether the removed items were processed by the interaction device within a pre-configured time period from the time the items were removed from the rack. In response to determining that the items were not processed by the interaction device within a pre-configured time period, the master controller transmits an alert message including a number of the items removed from the rack and an identification associated with the items.

Abstract: A system includes a rack storing a plurality of items, a shoe movably attached to the rack, a magnet coupled to the shoe and a circuit board arranged along the rack. The circuit board includes an array of sensors. Each sensor generates a value depending on a position of the magnet in relation to the sensor. The circuit board further includes a memory storing values generated by the sensors, and a processor configured to determine a position of the shoe/magnet based on the values and determine a count of the items based on the position of the shoe/magnet.

Abstract: A system includes a rack storing items, an interaction device that processes the items, and a master controller that is configured to receive a communication signal from the rack indicating that items have been removed from the rack and determine based on monitoring communication signals from the interaction device whether the removed items were processed by the interaction device within a pre-configured time period from the time the items were removed from the rack. In response to determining that the items were not processed by the interaction device within a pre-configured time period, the master controller transmits an alert message including a number of the items removed from the rack and an identification associated with the items.

Abstract: A system for determining an ambient concentration of compositions for bathroom cleaning comprises a processor operable to receive a concentration measurement from a sensor over a network within a first period of time. The processor is operable to compare the received concentration measurement to a first threshold and to a second threshold greater than the first threshold. The processor is operable to instruct a memory communicatively coupled to the processor to store an indication that a bathroom was cleaned in response to a determination that the received concentration measurement is greater than the first threshold and less than the second threshold. The processor is operable to send an alert for display on a user device indicating either that the sensor has been tampered or that a spill event has occurred in response to a determination that the received concentration measurement is greater than the second threshold.

Abstract: An image sensor is positioned such that a field-of-view of the image sensor encompasses at least a portion of an object storing items. The image sensor generates angled-view images of an object. A pixel position of a body part of a person is determined in at least a subset of the received image frames, thereby determining a set of pixel positions of the body part. An aggregated body part position is determined based on the set of pixel positions. If the aggregated body part position is determined to correspond to a position associated with the object, a trigger signal is provided indicating an interaction event has occurred.

Abstract: An object tracking system that includes a sensor and a tracking system. The sensor is configured to capture a frame of at least a portion of a rack within a global plane for a space. The tracking system is further configured to receive the frame, to determine a pixel location for the first person, and to determine a person is within the predefined zone associated with the rack. The tracking system is further configured to identify the plurality of items in a digital cart associated with the person, to identify an item from the digital cart associated with the first person, and to remove the identified item from the digital cart associated with the person.

Abstract: An object tracking system includes a sensor and a controller. The sensor captures frames for a global plane for at least a portion of a space. The controller has a memory that stores a homography associated with the sensor and a processor. The processor receives a first frame from the sensor and identifies a pixel location within the first frame. The processor determines an estimated sensor location for the sensor by applying the homography to the pixel location, and determines a location difference between the estimated sensor location and an actual sensor location for the sensor. The processor then compares the location difference to a difference threshold level, and recomputes the homography in response to determining that the location difference exceeds the difference threshold level.

Abstract: A system for refining an item identification model detects a triggering event at a platform. The system captures images of the item. The system extracts a set of features from at least one of the images. The system identifies the item based on the set of features. The system receives an indication that the item is not identified correctly. The system receives an identifier of the item. The system identifies the item based on the identifier of the item. The system feeds the identifier of the item and the images to the item identification model. The system retrains the item identification model to learn to associate the item to the images. The system updates the set of features based on the determined association between the item and the images.

Abstract: A system includes a rack storing items, an interaction device that processes the items, and a master controller that is configured to receive a communication signal from the rack indicating that items have been removed from the rack and determine based on monitoring communication signals from the interaction device whether the removed items were processed by the interaction device within a pre-configured time period from the time the items were removed from the rack. In response to determining that the items were not processed by the interaction device within a pre-configured time period, the master controller transmits an alert message including a number of the items removed from the rack and an identification associated with the items.

Abstract: An object tracking system that includes a first sensor and a second sensor that are each configured to capture frames of at least a portion of a global plane for a space. The system is configured to identify a first pixel location for a marker within a first frame and to determine an (x,y) coordinate for the marker using a first homography. The system is further configured to identify a second pixel location for the marker in the second sensor using a second homography, to identify a third pixel location using a disparity mapping, and to determine a distance difference between the second pixel location and the third pixel location. The system is further configured to compare the distance difference to a difference threshold level and to recompute the first homography and/or the second homography in response to determining that the distance difference exceeds the difference threshold level.

Abstract: A system includes a longitudinal rack storing a plurality of items, a shoe movably attached to the rack, a magnet coupled to the shoe and a longitudinal circuit board arranged along the length of the rack. The circuit board includes an array of sensors along the length of the rack. Each sensor generates a value depending on a position of the magnet in relation to the sensor. The circuit board further includes a memory storing values generated by the sensors, and a processor configured to determine a position of the shoe/magnet based on the values and determine a count of the items based on the position of the shoe/magnet.

Abstract: An image sensor is positioned such that a field-of-view of the image sensor encompasses at least a portion of a rack storing items. The image sensor generates angled-view images of an object. A pixel position of a body part of a person is determined in at least a subset of the received image frames, thereby determining a set of pixel positions of the body part. An aggregated body part position is determined based on the set of pixel positions. If the aggregated body part position is determined to correspond to a position associated with the object, a trigger signal is provided indicating an interaction event has occurred.

Abstract: A system for refining an item identification model detects a triggering event at a platform. The system captures images of the item. The system extracts a set of features from at least one of the images. The system identifies the item based on the set of features. The system receives an indication that the item is not identified correctly. The system receives an identifier of the item. The system identifies the item based on the identifier of the item. The system feeds the identifier of the item and the images to the item identification model. The system retrains the item identification model to learn to associate the item to the images. The system updates the set of features based on the determined association between the item and the images.

Abstract: A system for updating a training dataset of an item identification model determines that an item is not included in a training dataset. In response to determining that the item is not included in the training dataset, the system obtains an identifier of the item. The system detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features associated with the item from the images. The system associates the item to the identifier and the set of features. The system adds a new entry to the training dataset, where the new entry represents the item labeled with the identifier and the set of features.

Abstract: A device is configured to identify a first pixel location within a first plurality of pixels corresponding with an item in a first image and to determine a first (x,y) coordinate. The device is further configured to identify a second pixel location within a second plurality of pixels corresponding with the item in a second image and to determine a second (x,y) coordinate. The device is further configured to determine that the distance between the first (x,y) coordinate and the second (x,y) coordinate is less than or equal to the distance threshold value, to associate the first plurality of pixels and the second plurality of pixels with a cluster for the item, and to output the first plurality of pixels and the second plurality of pixels.

Abstract: A device configured to capture a first overhead depth image of the platform using a three-dimensional (3D) sensor at a first time instance and a second overhead depth image of a first object using the 3D sensor at a second time instance. The device is further configured to determine that a first portion of the first object is within a region-of-interest and a second portion of the first object is outside the region-of-interest in the second overhead depth image. The device is further configured to capture a third overhead depth image of a second object on the platform using the 3D sensor at a third time instance. The device is further configured to capture a first image of the second object using a camera.

Abstract: An object tracking system that includes a sensor and a tracking system. The sensor is configured to capture a frame of at least a portion of a rack within a global plane for a space. The tracking system is further configured to receive the frame, to determine a pixel location for the first person, and to determine a person is within the predefined zone associated with the rack. The tracking system is further configured to identify the plurality of items in a digital cart associated with the person, to identify an item from the digital cart associated with the first person, and to remove the identified item from the digital cart associated with the person.

Abstract: A device configured to identify a first pixel location within a first plurality of pixels corresponding with an item in a first image and to apply a first homography to the first pixel location to determine a first (x,y) coordinate. The device is further configured to identify a second pixel location within a second plurality of pixels corresponding with the item in a second image and to apply a second homography to the second pixel location to determine a second (x,y) coordinate. The device is further configured to determine that the distance between the first (x,y) coordinate and the second (x,y) coordinate is less than or equal to the distance threshold value, to associate the first plurality of pixels and the second plurality of pixels with a cluster for the item, and to output the first plurality of pixels and the second plurality of pixels.

Abstract: A device configured to detect a triggering event corresponding with a user placing a first item on the platform, to capture a first image of the first item on the platform using a camera, and to input the first image into a machine learning model that is configured to output a first encoded vector based on features of the first item that are present in the first image. The device is further configured to identify a second encoded vector in an encoded vector library that most closely matches the first encoded vector and to identify a first item identifier in the encoded vector library that is associated with the second encoded vector. The device is further configured to identify the user, to identify an account that is associated with the user, and to associate the first item identifier with the account of the user.