Abstract: Disclosed systems, methods, and computer program products address issues of parking and vehicular traffic at a facility, such as a warehouse or a merchandise distribution hub, and provide improved supply chain logistics for transportation and distribution of goods. Disclosed systems include a processor circuit that is configured to generating schedules for a plurality of shipments, to receive location tracking information regarding positions of vehicles, to perform shipping operations, and to dynamically update schedules based on received input. Received input may include information regarding warehouse labor and equipment availability, location tracking information, and/or information regarding weather and traffic conditions. Systems may be configured to send alerts to vehicle drivers provided updated scheduling information and instructions regarding shipments and to send alerts to warehouse workers provided updated scheduling information and instructions regarding shipments.

Abstract: A system and associated interfaces are provided that permit the monitoring of workers within the workplace environment. In one aspect, a monitor having various sensing capabilities may be assigned to a monitored subject that records various parameters that are personal to the worker. For instance, it is appreciated that there may be sensor that can be attached to the monitored subject that is adapted to monitor certain parameters associated with the worker's environment. For instance, a sensor assigned to the monitored subject may be capable of determining the location of the subject, along with motion, impacts, altitude, and other environmental parameters that could affect the health or other condition of the worker.

Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: A control system for a machine operating on a worksite includes a telemetry module associated with the machine. The telemetry module generates signals indicative of operational data of the machine. A controller communicably coupled to the telemetry module receives the signals indicative of the operational data from the telemetry module. The controller processes the received signals to create a data model. The controller identifies multiple operational zones over the worksite based at least on an analysis of the created data model. The controller determines occurrence of work cycles of the machine over the worksite based at least on the identified operational zones. The controller determines productivity data of the worksite based at least on the identified work cycles. The controller controls the machine based on the determined productivity data.

Abstract: A service appointment can be mapped to an automobile. Mapping a service appointment to an automobile can include receiving the diagnostic trouble code (DTC) from the automobile, interpreting, via a computing device, a service operation that resolves the DTC, and updating, via the computing device, the plurality of attributes of the plurality of service centers. Mapping the service appointment to an automobile can also include mapping, via the computing device, the service operation to a selected service center from the plurality of service centers based on the plurality of attributes of the selected service center and scheduling an appointment with the service center.

Abstract: Systems and methods for providing AI-based relocation cost estimates for services and products are disclosed. The method may comprise receiving description data of a location, the description data generated via at least one or more of a camera, a user interface, and/or one or more environment sensors. The method may generate an inventory list comprising a plurality of items, utilizing the machine learning model, based on the description data, the inventory list further comprising inventory attributes associated with the plurality of items related to a context of the plurality of items in the location. The method may generate, utilizing the machine learning models, one or more interactive quotes for relocation cost estimates comprising at least one or more offers for products and/or services based on the plurality of items in the inventory list and the inventory attributes.

Abstract: Systems and methods of crowd sourcing by distributing a task over a network to multiple workers for completion while providing quality control are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of identifying an attribute of the task, the task including multiple unit jobs, determining target accuracy in completion of the task by the multiple workers, computing a number of results to be collected for a unit job of the task based on the target accuracy, setting a wage amount that is offered to a worker for completing a unit job of the task based on the attribute and the target accuracy, and/or collecting and aggregating statistics of the workers completing the select unit jobs for quality control.

Abstract: A method and system for monitoring an e-commerce platform using artificial intelligence and fixing malfunctions on the e-commerce platform. The method includes: receiving, by a computing device, a feedback submitted by a user through the e-commerce platform; generating a vector based on content of the feedback, context of the feedback and profile of the user using AI processors; and classifying the vector to determine function corresponding to the feedback and status of the function using AI classifiers. The content includes text, voice, image and video; the context includes time, location and submission channel of the feedback; the profile includes attributes, history and preference of the user. Dimensions of the vector respectively corresponding to the text, voice, image, video, time, location, submission channel, attributes, history, and preference of the user.

Abstract: A service appointment can be scheduled with a service center. Scheduling a service appointment can include reading a diagnostic trouble code (DTC) of an automobile stored in an electronic memory and providing via a network interface, the DTC to a scheduling system. Scheduling a service appointment can include receiving a potential service appointment with a service center to resolve the DTC and acknowledging the potential service appointment to schedule the potential service appointment with the service center.

Abstract: The present invention relates generally to dispatching transportation to a business location. More specifically, an autonomous vehicle may be dispatched to pick up a passenger and transport that passenger to the business location.

Abstract: A system and method for generating an agent behavioral analytics including extracting text-based features, sentiment-based features, and prosody-based features from tagged calls; training a machine learning behavioral model, based on the text-based features, the sentiment-based features, and the prosody-based features extracted from the tagged calls and an at least one score associated with an at least one behavioral metric of the tagged calls, to produce a trained machine learning behavioral model; extracting text-based features, sentiment-based features, and prosody-based features from an incoming call; and using the trained machine learning behavioral model to produce an at least one behavioral label for the agent in the incoming call for the at least one behavioral metric, based on the text-based features of the incoming call, the sentiment-based features of the incoming call and the prosody-based features of the incoming call.

Abstract: Aspects disclosed herein may utilize neural embedding techniques to model session activity. A dataset may be collected from on online market place, such as an app store. The data set may include one or more user sessions comprising sequential click actions and/or item purchases. Models may be generated to represent session activity and, therefore, may be utilized for contextual recommendations of apps in an online app store. As such, the various aspects disclosed herein may also generate purchase predictions based on click-purchase relations in a sequence. The item similarities and purchase predictions may be used to provide real-time aid to users navigating an online marketplace.

Abstract: Provided herein are systems and methods for determining a refined oilfield location area from a notified oilfield location. The methods and systems access notifications of intent to obtain a notified oilfield location record that includes at least a notified place name, a notified distance from a place associated with the notified place name and a notified approximate direction from the place associated with the notified place name. The methods and systems further determine a candidate location area based on the notified distance and the notified approximate direction. The methods and system further obtain auxiliary information associated with information identified within the notification of intent. The methods and systems further determine a second candidate location area based on the auxiliary information and determine the refined location area based on an intersection of the first candidate location area and the second candidate location area.

Abstract: The present invention relates to a computer implemented method of determining optimal business metrics from a product mix constrained by at least physical shelf space and selectively by at least one business rule. The computer implemented method comprising the steps of defining a boundary constrained shelf space, placing, physically, a product mix within the boundary constrained shelf space, and creating a product mix ranking based, in part, on prior sales of each of the product type. The computer implemented method continues by using a data processing device to develop, through algorithmic autonomous learning, achievable business metric performance of the boundary constrained shelf space. In this regard, a group of similar product mix/ranking is optimized to create an ideal product mix/ranking which is then use to inform changes to make to the product mix to achieve the desired OPTIMAL BUSINESS METRIC.

Abstract: The present disclosure generally provides techniques for analyzing and displaying the order execution quality of market instruments traded during a relevant period, or lifetime, of the order. The utilization of quote information in calculating a normalization factor allows for comparisons across instruments, orders, and days for instruments with a publically available price irrespective of executed volume. A calculated Z score illustrates the quality of an order execution for a specific traded time as compared to all possible random executions. Moreover, the techniques disclosed herein allow for the comparison of execution quality across market instruments, orders sizes, and other variables via a graphical user interface and other data visualization tools, and can encapsulate evaluation methods using other adjusted Z score thresholds and/or alternatively take into account desirable volume weighting when calculating the standard deviation.

Abstract: A non-transitory storage medium having stored thereon instructions, the instructions being executable by one or more processors to perform operations comprising responsive to a trigger, generating a model based on extracted features from a first selection of data from a dataset, testing the predictive appointment model based on a second selection of data from the dataset. Applying the predictive appointment model to the dataset to generate customer preference probabilities. Aggregating a list of available appointments. Predicting and proactively contacting customers most likely to accept one or more available appointments based on the customer preference probabilities.

Abstract: The disclosed embodiments provide computer-implemented systems and methods for batch picking optimization. They system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions to receive an order comprising one or more items for picking. Additionally, the system may calculate one or more high density areas in a fulfillment center by calculating distances between a first item in the one or more items and at least one other item in the one or more items using a search algorithm. Additionally, the system may calculate nearest neighboring items for the one or more items and generate a high density area by choosing a plurality of the nearest neighboring items.

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of receiving an external catalog comprising external attributes for each product of a plurality of products, mapping the external attributes from the external catalog to internal attributes for each product of the plurality of products in an internal catalog for an online retailer using an ensemble learning technique comprising a plurality of algorithms, incorporating the external attributes of the external catalog into the internal attributes in the internal catalog as mapped, and coordinating displaying of the external attributes and the internal attributes on a website of the online retailer.

Abstract: A system and associated interfaces are provided that permit the monitoring of workers and equipment within the workplace environment. In one aspect, an equipment sensor having various sensing capabilities may be assigned to a piece of equipment that records various parameters that are specific to the piece of equipment. For instance, it is appreciated that there may be an equipment sensor that can be attached to the piece of equipment that is adapted to monitor certain parameters associated with the piece of equipment and its environment. For instance, an equipment sensor assigned to the piece of equipment may be capable of determining the location of the piece of equipment, along with motion, altitude, and the presence of an operator of the piece of equipment.

Abstract: The present disclosure is directed to a system and method for generating, securely storing, retrieving, and processing sales receipts for the purchase of goods and services using any convenient method of payment. All buyer purchases are linked to their receipt account or account. The method includes the generation of both physical and electronic receipts with any receipt being readily identifiable by a purchaser, seller, credit card issuer, employer, financial institution, or other party or entity having a need to access the receipt and information included on it. The system and method also utilize a taxonomy to characterize attributes of purchase receipts and employs and an analytics capability useful by buyers, sellers, and third parties.