Methods and systems for sensor fusion in a production line environment are disclosed. An example system for data collection in an industrial production environment may include an industrial production system comprising a plurality of components, and a plurality of sensors each operatively coupled to at least one of the components; a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group; and a data analysis circuit to detect an operating condition of the industrial production system based at least in part on a portion of the sensor data values; and a response circuit to modify a production related operating parameter of the industrial production system in response to the detected operating condition.

A focus group system for determining the user’s mood or reaction as the user views content based at least in part on physiological indicators measured by a physiological monitoring system and feedback from the user. The system may receive sensor data including physiological data of a user captured while the user is consuming content and receive feedback of the user associated with a reaction of the user when the sensor data was captured. The system may then determine, based at least in part on the sensor data and the feedback, a direction and magnitude of the reaction of the user to the content.

A system for monetizing animal data includes a source of animal data that can be transmitted electronically. Characteristically, the source of animal data includes at least one sensor. An intermediary server receives and collects the animal data such that collected data has attached thereto metadata. The metadata includes at least one of the origination of the animal data or personal attributes of individuals from which the animal data originated. The intermediary server provides requested animal data to a data acquirer for consideration. The requested animal data may include simulated animal data. The intermediary server will also distribute at least a portion of the consideration to at least one stakeholder. The intermediary server includes a single computer server or a plurality of interacting computer servers.

The Max AllowanceⓇ system is an on-line system that connects customers seeking to sell/trade an automobile with auto-dealers seeking to purchase used automobiles. By utilizing the “retail-down, considerate cash offer” approach of the on-line system, auto-dealers are able to formulate an offer for the customers’ automobile(s) that serves to entice them to contact the auto-dealers because said offer is more considered than offers generated using the common “wholesale-up” approach. The MAX AllowanceⓇ system gives auto-dealers confidence that they will be able to compare online disclosure against in-person vehicle inspection condition and improve their percentage of vehicle acquisitions while maintaining a desired amount of profit upon resale of the acquired vehicles. Depending on how a customer has entered into the system, multiple auto-dealers may provide offers to the customer, enhancing the customer’s confidence that the offers received are fair, further enticing the customer to contact the auto-dealers that provided the offers.

A process for determining open interest in an artwork and creating an emerging demand graph or chart is described. This is done by displaying information on the artwork for the public to view. An absentee bidding period is set wherein the online platform accepts absentee bids for the artwork. Certain absentee bids are used to calculate an open interest index in the artwork which is used to adjust the emerging demand graph. This open interest index can be used to measure interest in the artwork before the actual auction of the artwork begins. The actual auction is a modified Dutch auction that uses data from the absentee bidding period, such as the highest absentee bid.

A training set may be created to train a machine learning engine, such as an artificial neural network (ANN), to value a target domain name using data from previously sold domain names. The training set may comprise a plurality of word features vector of real numbers (information related to the words or tokens within the sold domain names), a plurality of word embedding vector of real numbers (word embedding of the words within the sold domain names), a plurality of context embedding vector of real numbers (sale context, i.e., location and date of a sale of a sold domain name), a plurality of DNS embedding vector of real number (DNS information of the sold domain name) and/or a plurality of domain name features vector of real numbers (data regarding the sold domain name). The ANN may then be trained on the training set, using the methods of gradient descent and back propagation, to value a target domain name.

The battery residual value display device includes: a battery information receiving module; an attenuation function determining module; a second residual value determining module; a graph output module configured to output a graph of which one axis indicates residual values of a battery and another axis indicates information on an elapsed time from a time of manufacture of the battery; and a display unit. The graph output module is configured to output: in the graph, a display indicating a first residual value; a display indicating boundaries between a plurality of residual value ranks obtained by dividing the residual values in accordance with a level of a second residual value; and a display indicating boundaries between a plurality of groups, indicating types of applications in which the battery can be used, obtained by dividing the plurality of residual value ranks in accordance with the level of the second residual value.

A system and method for generating a real estate appraisal. Characteristics of a property of interest are compared with the characteristics of different real estate properties to determine a set of comparable real estate properties. The sales prices associated with the set of comparable real estate properties are then adjusted based on predetermined criteria and a final valuation of the property of interest is generated based on these adjusted sales prices.

A merchandise trading method according to one aspect of the present invention comprises the steps of: predicting a secondhand price at the time of a return for the merchandise a buyer wants to purchase, calculating a virtual asset corresponding to the predicted secondhand price, and, when a purchase is determined by the buyer, concluding a return agreement that includes the time of return and the calculated virtual asset and processing trading of the merchandise; allowing the buyer to determine whether to return the purchased merchandise at the time of return according to the return agreement; and, when returning of the merchandise is determined at the time of return, paying the virtual asset included in the return agreement to the buyer.

A residual value calculation system is for an air conditioner including an indoor unit and an outdoor unit. The residual value calculation system includes a management device that manages the air conditioner. The management device includes an obtaining unit and a calculating unit. The obtaining unit obtains first environment information related to an installation environment of the indoor unit, and second environment information related to an installation environment of the outdoor unit. The calculating unit calculates a residual value of the air conditioner after use over a set period based on the first environment information and the second environment information, the residual value including at least one of an initial estimation residual value and an actual estimation residual value based on actual use.