An agriculture support system that facilitates profit estimation of even a crop that is to be newly cultivated on a land. The agriculture support system is configured as a computer system including a data input unit, a data storage unit, and an arithmetic operation unit. The arithmetic operation unit has an yield estimation part adapted to estimate a crop yield on the basis of data including characteristics and environment of a land as an estimation target so as to output yield data, a crop production data storage part adapted to store crop production data on crop production, and a profit estimation part adapted to estimate profit for a case in which the crop is produced on the basis of the yield data and crop production data so as to output profit estimation data.

An advertising network includes a first network server containing real world media of consumers from a live event, a second network server containing sample media, virtual world media, and supporting meta data belonging to vendors, merchants, or service providers, a server interface to the first server distributed to consumer and third party computing appliances and a non-transitory medium resident on the first server containing machine-readable code thereon, the code instructing the first server to (a) process the real world media against sample media to identify virtual objects associated with virtual world media and supporting meta data, (b) upon recognition of a virtual object(s), retrieving associated virtual world media and supporting meta data, (c) integrating the retrieved virtual world media and supporting meta data with the real world media producing an augmented reality overlay layer, and transmitting that to a computing appliance operated by the consumer for display and interaction.

Systems and methods relate to predicting improved operating hours for a merchant. For example, a method may include determining operating hours of a target merchant; identifying one or more merchants other than the target merchant having one or more common characteristics with the target merchant; obtaining transactional data indicating customer transactions at the one or more merchants other than the target merchant; computing an estimate of potential customer transactions at the target merchant during a the period of time not within the operating hours by processing input data including the obtained transactional data using a trained machine learning model to produce the estimate, the estimate being a number or value of consumer transactions missed as a result of the target merchant being closed during the period of time; and transmitting, to the target merchant, information indicating the computed estimate.

Customers receive an incentive with use of an installed cellphone app to image an AR-bearing ad. Matches between data from the customer's accounts for each merchant are compared to the data in association with the customer's logical identifier for their cellphone, and particularly with each incidence of a rendering on their display screen of an AR view of a product advertisement containing the AR-triggering symbol to initiate the corresponding AR enhanced view of the ad. In conjunction with chronological time stamping of occurrences, a likelihood is derived that the customer's viewing of the AR enhanced product advertisement influenced the potential customer's subsequent purchase of the corresponding advertised product as evidenced within the potential customer's rich transactional data from the customer's debit and/or credit accounts. The certainty of each match is determined to further initiate the merchant's incentive to the customer which may be the merchant's donation to a community program.

Embodiments of the present disclosure provide data processing methods and devices. The method comprises determining first feature information of one or more second users corresponding to a first user and second feature information of one or more to-be-selected commodity objects; determining one or more first matching degrees in at least one first feature dimension between the one or more second users and the one or more to-be-selected commodity objects according to the first feature information and the second feature information; and determining target commodity object information corresponding to the first user according to the one or more first matching degrees.

A system and a method are disclosed for replacing a canceled accommodation for a guest user using reserved accommodations. In an embodiment, an accommodation management system retrieves information describing historical bookings and listings for accommodations in a region. The system determines common attributes of the listings and a historical cancelation rate of bookings. The system determines an amount of listings to reserve for a time period based on the historical cancelation rate and moves, from an available listing database to a reserved listing database, the amount of listings for the region, each listing including common attributes. The system sends an indication to each host user of the moved listings that the listing has become unavailable for the time period. The system receives an indication that a booking for a guest user has been canceled and books one of the listings in the reserved listing database for the guest user.

The process of obtaining an insurance quote is currently based on information provided by filing online forms. Insurance companies use the consumer input data from online the forms to provide a quote for property insurance and for insurance underwriting. To complete the underwriting, the insurance companies have to make assumptions on various factors; for example, the structure and layout of a consumer's home, what type of content the consumer owns, its value, and its condition, among several others. It is desirable to get more accurate data on the consumer content, the structure and layout of the home, as well as other factors (e.g., hazards such as whether a house is on a canyon) in an automated fashion which would let insurance companies underwrite policies with a more accurate risk profile as well as save costs by not having to send an onsite inspector.

Disclosed is a method for using a virtual representation of an indoor environment to identify contents that have been damaged (e.g., by flooding). A virtual representation of a physical scene of an indoor environment is processed to identify a list of contents in the physical scene. The virtual representation may include 2-dimensional representations of the physical scene (e.g., images or video) or a 3-dimensional representation of the physical scene (e.g., 3D digital model). A reference line is determined in the virtual representation that is indicative of a maximum vertical extent of the damage in the physical scene. The position of the reference line is compared with the position of the identified contents in the virtual representation to determine contents that are likely to be damaged. For example, the contents that are at or below a plane represented by the reference line in the virtual representation may be identified as damaged.

Systems, methods, and non-transitory computer readable media are disclosed that include operations to generate a virtual representation of a physical location with spatially localized information related to elements within the location being embedded in the virtual representation. The operations includes receiving description data (e.g., a plurality of images and videos) of the location, the description data being generated via at least one of a camera, a user interface; receive metadata associated elements within the location; generating (e.g., offline or in real-time), via a machine learning model and/or a geometric model, a 3-dimensional (3D) model of the location and elements therein; and generating, based on the 3D model of the location, an information-rich virtual representation of the location by annotating the 3D model with spatially localized metadata associated with the elements within the location and semantic information of the elements.

An electronic device that includes a display screen and circuitry is provided. The display screen displays map data and a user interface (UI) element. The circuitry receives a first user input, via the UI element. The first user input indicates a geographical region on the displayed map data. The circuitry extracts geo-location information from vehicle data associated with a vehicle. The circuitry further controls a communication of a first portion of the vehicle data with a server based on a first geo-location in the extracted geo-location information of the vehicle data and the indicated geographical region. The first portion of the vehicle data corresponds to the first geo-location.