Abstract: In one example embodiment, a computer-implemented method and system for immobilization of machines capable of moving are disclosed. The method for immobilization of machines capable of moving includes detecting an event by a tracking device; providing one or more rules to evaluate the detected event; evaluating the detected event using the one or more rules; and triggering an action type based on the outcome of the evaluation. The system for immobilization of machines capable of moving includes a machine capable of moving, a tracking device including at least one processor and logic, a starter relay and a fuel pump relay, wherein the tracking device detects an event; evaluates the detected event using one or more rules provided to evaluate the detected event; and triggers an action type based on the outcome of the evaluation.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.

Abstract: Some embodiments provide retail inventory identification systems, comprising: a mobile product mapping system comprising: a transport system, a tower housing, and a cluster processing system comprising: a plurality of product identifying (PI) systems each in different orientations and directed along different fields of view, and a mobile control circuit; wherein the PI systems each comprise an image capture system, and a location determination system, wherein each of the plurality of PI systems is configured to: capture images of products supported on product support systems; and locally process the images comprising applying a plurality of different machine learning modeling techniques, to infer identification of multiple products and generate product identifying information in association with location information; and the mobile control circuit is configured to generate product identifying mapping of products as the product mapping system moves; and communicate the generated product identifying mapping to

Abstract: In one aspect, the present disclosure relates to a system for improved transactional mainframes, the system comprising a processor, a database, an application programming interface (API) module, and a transaction import module. The API module can be configured to: receive transaction data comprising a transaction type, a user identifier, one or more transaction card identifiers, and one or more fields associated with the transaction card identifiers; validate the transaction data using one or more of the stored validation rules associated with the one or more transaction card identifiers; generate one or more transaction cards; and store the transaction data and transaction cards to the database. The transaction import module can be configured to submit the transaction cards to the mainframe, view the status of submitted records, and enable retrying of transaction cards that failed to process.

Abstract: In some embodiments, systems and methods are provided to recognize products in a physical facility through a portable device that comprises a decision control circuit configured to: process each frame of the subset of frames by multiple modeling techniques each relative to a corresponding image attribute and obtain a corresponding product identification probability; determine corresponding aggregated identification probabilities of the first product based on the product identification probabilities; collectively evaluate the aggregated identification probabilities and identify when a predefined relationship with a collective threshold probability exists; and cause an image of the first product to be displayed in response to identifying that one or more of the aggregated identification probabilities having the predefined relationship with the collective threshold probability.

Abstract: In some embodiments, systems and methods are provided to recognize retail products in a physical retail store through a portable device that comprises a decision control circuit configured to: process each frame of the subset of frames by multiple modeling techniques each relative to a corresponding image attribute and obtain a corresponding product identification probability; determine corresponding aggregated identification probabilities of the first product based on the product identification probabilities; collectively evaluate the aggregated identification probabilities and identify when a predefined relationship with a collective threshold probability exists; and cause an image of the first product to be displayed in response to identifying that one or more of the aggregated identification probabilities having the predefined relationship with the collective threshold probability.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.

Abstract: Aspects of the disclosure present a cooler driven by an engine turning a generator wherein the engine and the cooler are not linked by a direct drive shaft.

Abstract: In one example embodiment, a computer-implemented method and system for immobilization of machines capable of moving are disclosed. The method for immobilization of machines capable of moving includes detecting an event by a tracking device; providing one or more rules to evaluate the detected event; evaluating the detected event using the one or more rules; and triggering an action type based on the outcome of the evaluation. The system for immobilization of machines capable of moving includes a machine capable of moving, a tracking device including at least one processor and logic, a starter relay and a fuel pump relay, wherein the tracking device detects an event; evaluates the detected event using one or more rules provided to evaluate the detected event; and triggers an action type based on the outcome of the evaluation.

Abstract: In one example embodiment, a computer-implemented method and system for immobilization of machines capable of moving are disclosed. The method for immobilization of machines capable of moving includes detecting an event by a tracking device; providing one or more rules to evaluate the detected event; evaluating the detected event using the one or more rules; and triggering an action type based on the outcome of the evaluation. The system for immobilization of machines capable of moving includes a machine capable of moving, a tracking device including at least one processor and logic, a starter relay and a fuel pump relay, wherein the tracking device detects an event; evaluates the detected event using one or more rules provided to evaluate the detected event; and triggers an action type based on the outcome of the evaluation.

Abstract: Systems, apparatuses, devices, applications, and methods are provided herein useful to provide retrieval of products within a retail store and control a point of sale system to execute purchase of a product list in conjunction with a mobile device. A device control circuit of the mobile device is configured to receive a proposed product list from a respective customer; determine a suggested product list based on the proposed product list and a weighted average of a plurality of variables; determine a shopping route for the suggested product list, reduce the duration of the shopping route if possible, acquire payment from the respective customer for products on a final product list, and control the point of sale system to execute purchase of the products on the final product list on behalf of the respective customer.

Abstract: In one aspect, the present disclosure relates to a system for improved transactional mainframes, the system comprising a processor, a database, an application programming interface (API) module, and a transaction import module. The API module can be configured to: receive transaction data comprising a transaction type, a user identifier, one or more transaction card identifiers, and one or more fields associated with the transaction card identifiers; validate the transaction data using one or more of the stored validation rules associated with the one or more transaction card identifiers; generate one or more transaction cards; and store the transaction data and transaction cards to the database. The transaction import module can be configured to submit the transaction cards to the mainframe, view the status of submitted records, and enable retrying of transaction cards that failed to process.

Abstract: A track lighting device includes a clamp assembly having a dual engagement mechanism for coupling to a track. For example, the clamp assembly includes a collar rotatable about a collar axis, and a cam follower having a cam-pin received by a first groove of a cam. The cam also includes a second groove and a first engagement member. The first groove translates a rotational movement of the collar and the cam follower into a linear movement along the collar axis to releasably couple the first engagement member to the track. The clamp assembly also includes a latch assembly having a second engagement member and a latch-pin in communication with the second groove of the cam. At least a portion of the latch assembly pivots about a latch axis based on movement of the latch-pin relative to the second groove to couple the second engagement member to the track.

Abstract: In one aspect, the present disclosure relates to a system for improved transactional mainframes, the system comprising a processor, a database, an application programming interface (API) module, and a transaction import module. The API module can be configured to: receive transaction data comprising a transaction type, a user identifier, one or more transaction card identifiers, and one or more fields associated with the transaction card identifiers; validate the transaction data using one or more of the stored validation rules associated with the one or more transaction card identifiers; generate one or more transaction cards; and store the transaction data and transaction cards to the database. The transaction import module can be configured to submit the transaction cards to the mainframe, view the status of submitted records, and enable retrying of transaction cards that failed to process.

Abstract: An automated laboratory system includes a vertical shelving system including a frame and at least one shelf movably mounted to the frame such that the at least one shelf is movable relative to the frame between a docked position and an undocked position, the at least one shelf being configured to carry at least one instrument. The system also includes a robotic device proximate the vertical shelving system and being configured to access the at least one instrument carried by the at least one shelf.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.

Abstract: An array of pixels, wherein each pixel comprises: a CHEMFET sensor; and a sigma delta ADC.

Abstract: In one or more embodiments, method, system and computer program product for providing secure access to device data and/or device operations by an application are disclosed. The method for providing secure access to one or more devices by an application includes receiving application information for the application; receiving device information for the one or more devices to which the application is requesting access; receiving rules for allowing the application to access the one or more devices, wherein the access to the one or more devices includes device data, one or more device operations or a combination thereof; and allowing the application to access the device based on the rules.

Abstract: In some embodiments, systems and methods are provided to recognize retail products, comprising: a model training system configured to: identify a customer; access an associated customer profile; access and apply a set of filtering rules to a product database based on customer data; generate a listing of products specific to the customer; access and apply a model training set of rules to train a machine learning model based on the listing of products and corresponding image data for each of the products in the listing of products; and communicate the trained model to the portable user device associated with first customer.