1342results about "Discounts/incentives" patented technology

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

An Automated AI-Driven Lifestyle Orchestration System proactively manages a user's daily life by intelligently populating calendars with relevant, time-sensitive marketing objects. This is achieved through sophisticated AI-driven analysis of user directives, preferences, and real-time location data obtained via computing devices like smartphones. The system leverages advanced media identification modules employing fingerprinting and watermarking to accurately match user-captured media (via a Percipient Sample Pack (PSP)) to specific content and associated products. It facilitates dynamic commerce through hierarchical linked lists for purchasing authentic or similar items, supported by an affiliate program. This inventive solution significantly improves personal organization and digital commerce by transforming passive interaction into a proactive, intelligent, and monetizable user experience.

A system and method for enabling real-time dispatch of flexibility resources to unlock grid capacity through AI-based orchestration. The invention addresses the challenge of connecting high energy demand users, such as data centers, to constrained electricity grids without requiring infrastructure upgrades. The system establishes a marketplace where flexible asset holders set temporal compensation prices and boundary conditions, enabling true market-based participation. An AI orchestration engine analyzes real-time grid conditions and modifies flexible asset behavior to create inverse consumption profiles that counterbalance new demand loads. The platform integrates hardware and software solutions for remote control and APIs for autonomous systems like electric vehicles. Aggregators and off-takers can establish long-term contracts for flexible capacity at agreed prices. The AI system ensures flexible assets meet user-defined boundary conditions while simultaneously masking high energy demand, making new loads invisible to the grid and enabling immediate connection of data centers essential for industrial deployment.

The present disclosure relates generally to a gaming system, device, and method supportive of rewarding responsible gaming behaviors. An illustrative method includes presenting a representation of the electronic game on a display device, where the representation of the electronic game includes displaying a plurality of game features, executing the electronic game, determining, during execution of the electronic game, that a player of the electronic game has taken an action that corresponds to a responsible gaming action, correlating the responsible gaming action to a reward for the player, and presenting information to the player that describes the reward for the player along with instructions for redeeming the reward.

System, process, and method for gamifying physical assets, digital assets, and virtual assets through advertising and e-commerce, and system and method for personalized digital twin LLM chatbot gamification in e-commerce and emotional intelligence development. The first aspect of the invention is a system and process for creating and training a personalized digital twin LLM chatbot assistant. The digital twin is personalized for a given human user using training data regarding the human user. A second aspect of the invention is a system and process of creating and playing an e-commerce game, including the mechanics of the game. The e-commerce game may be created and / or played by employing personalized digital twin LLM chatbot assistant such as that described in the first aspect of this invention. State of the art technologies such as sensors, IoT devices, wearable devices, and VR / XR / AR can be integrated into the game.

The invention relates to the technical field of fast moving consumer goods data analysis, and discloses a marketing data analysis-based big data intelligent delivery system which comprises a demand analysis unit, a scene analysis unit, a fusion unit, a division unit and a delivery unit. The method comprises the steps of generating user demand potential energy intensity, dividing the user demand potential energy intensity into three types of circle layers, accurately identifying user groups with potential consumption demands but weak current feedback, adopting differentiated delivery decisions according to types of price sensitivity, information missing degree, decision complexity and the like for main retardation factors of different circle layers, and correcting a strategy in combination with a consumption willingness value. Decision resistance of users in each circle layer can be effectively eliminated, potential consumption potential is converted, resource mismatching is avoided, and the return rate of long-term big data delivery of home fast moving consumer goods is increased.

A social media platform facilitates user interaction through digital environments called “bubbles,” which serve as customizable, collaborative spaces for content sharing and engagement. Users can participate in gamified events such as challenges, races, and raffles within these bubbles. The platform incorporates a blockchain-based reward system that issues digital assets, including tokens and non-fungible tokens (NFTs), based on user participation and performance. Each piece of content shared within a bubble can be assigned its own privacy level, independent of the user's account settings. The system supports role-based access, content moderation, and smart contract integration to ensure secure, transparent reward distribution.

An AI-based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure and coordination with distributed systems to support important use cases for a range of enterprises. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may use AI, IoT, and technologies that filter, process, and move data more effectively across communication networks. Embodiments of the platform may leverage energy market connection, communication, and transaction enablement platforms. Embodiments may employ intelligent provisioning, data aggregation, and analytics.

The invention provides an integral shopping mall order rolling processing optimization method and system based on big data, and the method comprises the steps: employing a dynamic priority adjustment mechanism for a conflict order list, and adjusting the order processing priority based on the user behavior track data, including historical exchange preference, and obtaining a resource distribution scheme; integrating the order sequence through a queue reordering mechanism, reordering based on the resource allocation scheme to obtain a final processing sequence, preferentially executing the high-priority request, and maintaining the queue stability at the same time; if residual conflicts exist in the final processing sequence, supplementary resources are extracted from a preset standby inventory through a standby resource set scheduling mechanism, a complete execution plan is obtained, and the plan covers all order processing paths; and on the basis of the complete execution plan, monitoring the order processing progress, and obtaining a stable operation order flow through progress tracking and anomaly detection, real-time state feedback and iterative adjustment.

The invention relates to the technical field of information, and particularly discloses an online mall platform intelligent management method and system, and the method comprises the following steps: S1, constructing a data collection system, and obtaining platform operation data, user behavior data and external market data in real time; s2, acquiring historical sales data, analyzing the historical sales data by adopting a Prophet time sequence model, predicting a future sales trend and inventory requirements, and generating a dynamic replenishment suggestion; s3, optimizing inventory management through a dynamic programming algorithm, calculating an optimal inventory threshold value in combination with external market data, and performing automatic replenishment triggering; s4, establishing a user portrait according to the user behavior data, and generating a personalized coupon strategy based on a collaborative filtering algorithm; s5, dynamically matching the work order and the customer service according to a multi-attribute decision algorithm; and S6, storing quality assurance information, and ensuring non-tampering and traceability of construction time, material batches and technician ID data. Therefore, the operation efficiency and the user experience of the shopping mall platform are improved.

An RFID transponder including a Bluetooth® compatible transceiver (BLEET) is described. The Bluetooth® compatible transceiver may be configured to set data that is transmitted via one or more RFID transceivers in the transponder and to return data received by the RFID transceiver(s) to a client application running, for example, on a user's smart phone. The BLEET may be used for electronic vehicle tracking or tolling. Vehicle occupancy data may be set by the user with the client application via a Bluetooth® connection in connection with high occupancy vehicle tolling and express lane incentive programs. The BLEET may be used in a congestion pricing (CP) toll area, wherein the smart phone determines a toll rate based on the location, when triggered by the BLEET, that the BLEET was read by an RFID reader located on a boundary of the CP toll area.

An NFT processing server may cooperate with a first device to communicate a notification of a digital promotion having an acceptance rule set associated therewith. A tethered non-fungible token (tNFT) representative of the promotion may be generated and stored on a blockchain network. The tNFT may have an immutable attribute including a reference to the rule set, and a mutable attribute indicative of rule set acceptance. A first shopper may be prompted for rule set acceptance, and, thereupon, the server may set the mutable attribute to be indicative of the acceptance, permit transfer of the digital promotion to a second device, and transfer the promotion on the blockchain network to the second device by transferring the tNFT to a digital wallet. The server may also prompt a second shopper for acceptance of the rule set, and thereupon, set the mutable attribute to be indicative of the acceptance.

An example operation includes one or more of storing preferences of an occupant of a vehicle within a database, receiving data from signage that is within a field of view of the occupant as the vehicle is travelling along a route that includes the signage, generating a message directed to the occupant of the vehicle based on the preferences of the occupant and the data from the signage, where the message includes an action to be performed by the occupant within a period of time, and displaying the message on a display device within the vehicle which is associated with the occupant.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver- the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

A method of managing digital assets is provided. The method includes receiving an input identifying a first digital wallet. One or more non-fungible tokens associated with the first digital wallet are identified. From the one or more non-fungible tokens, sustainability tokens are selected, each of the sustainability tokens being associated with a corresponding sustainability digital asset. For each of the sustainability tokens, a uniform resource indicator for the corresponding sustainability digital asset is retrieved from a distributed blockchain ledger and based on the uniform resource indicator, attributes of the corresponding sustainability digital asset are retrieved. A composite sustainability score is generated based on the attributes of the sustainability digital assets associated with the sustainability tokens, which is compared to a first benefit criteria and when the composite sustainability score meets the benefit criteria, a first benefit is provided to an owner of the first digital wallet.

The invention relates to the technical field of artificial intelligence, and discloses a dialogue text mining method and system based on code scanning consumption cash back of big data, and the system comprises a consumption data collection module, a multi-modal analysis module, a strategy decision engine and a dynamic execution module. When code scanning consumption cash-back strategy decision making is carried out, real-time dialogue text semantics and consumption time-space behavior data are fused, a deep association mechanism of consumption intentions and payment scenes is established, the matching deviation of user language expression and actual consumption behaviors can be eliminated in real time, the consistency of a cash-back strategy and real consumption appeals is ensured, and the payment efficiency is improved. The problem of strategy mismatching caused by semantic understanding isolation in a traditional system is effectively avoided, the precision of personalized marketing is improved, double feedback of dialogue emotion tendency and historical strategy effects is dynamically analyzed, the deviation value of strategy feature matching is corrected in real time, and the system can actively adjust weight distribution of feature combinations in a strategy library.

The invention relates to the technical field of automobile charging station load systems, in particular to a new energy automobile charging station dynamic load optimization integration system and method based on multi-source data collaboration and elastic compensation. According to the system, charging pile power, meteorological data and user behavior information are fused in real time through a multi-source time sequence data set construction module, an LSTM neural network optimized by an improved sparrow algorithm is adopted to predict the remaining power capacity of a charging station, and Bootstrap resampling is combined to generate a confidence interval to realize safety boundary control; the self-adaptive firefly algorithm dynamically adjusts the charging pile power, establishes a multi-dimensional priority queue including SOC emergency degree, compensation willingness and social value, and guides users to charge in a peak shifting manner; the system comprises a 5G communication gateway, an IGBT power control module and a three-level early warning mechanism, and millisecond-level flexible adjustment of charging power is realized. The utilization rate of the transformer is improved to 91%, the peak-valley load ratio is reduced to 1.7: 1, the user waiting time is shortened by 63.5%, and a dynamic load management system of power grid-station-user collaborative optimization is formed.

According to an aspect there is provided an ambient commerce system. The ambient commerce system may include a sensor at an ambient commerce premises. The ambient commerce system may further include a processor coupled to the sensor and a memory coupled to the processor. The memory may store processor-executable instructions which, when executed, cause the processor to: detect, based on an output of the sensor at the ambient commerce premises, engagement of an entity with a first item satisfying first predetermined criteria; identify the entity; determine based on account data for the identified entity, a resource parameter for the identified entity; and when the resource parameter satisfies second predetermined criteria, generate a notification on an electronic device associated with the entity. Identifying the entity may include image recognition, such as facial recognition.

The invention discloses a risk control management method and system combining discount coupons with rights and interests in the financial field. The method comprises the steps of data preprocessing, feature engineering, model training, dynamic risk management of discount coupons and rights and interests, real-time risk monitoring, early warning, disposal and the like. According to the invention, an artificial intelligence technology is adopted, a coupon and right risk assessment model is established, and the effectiveness of risk management is improved by identifying potential risks in real time and taking corresponding measures. By monitoring and evaluating the use conditions of coupons and rights in real time, the management cost of the coupons and the rights can be effectively reduced; according to the method, issuing and recycling strategies of coupons and rights and interests are automatically adjusted according to user behaviors and risk levels, and personalized management and refined operation are realized.

Along with continuous development of technologies such as deep learning and natural language processing, the AI model shows powerful capabilities in the aspects of understanding user intentions, processing complex information, realizing accurate matching and the like. The large star model is a large AI model which is developed by China Telecom and is based on an advanced Transform architecture. The Transformer architecture obtains significant results in the fields of natural language processing, image recognition and the like due to good expandability and strong performance of the Transformer architecture. When the method is applied to a customer service scene, the large star model can deeply understand the appeal of the user. Through natural language processing and semantic understanding technologies, the model can accurately identify and analyze questions of a user and quickly give corresponding answers or suggestions. In addition, the large star model also has strong copywriting generation ability and knowledge question-answering ability, can provide personalized exchange recommendation and shopping preferential information for the user, and further improves the user experience.

The present application relates to an integrated customer service method and system based on multiple agents, wherein the method includes: processing consulting questions raised by active incoming users through a dialogue management agent, obtaining multi-dimensional data information and generating dialogue responses to the consulting questions; based on the feedback of the active incoming users after the dialogue response, obtaining the consulting intention of the active incoming users through analysis by an intention recognition agent; based on the consulting intention and recent activity records of the active incoming users, determining the outgoing call operation to be performed through an outgoing decision agent; and then executing the outgoing call operation through an outgoing execution agent. Through the present application, integrated customer service of multiple agents is realized, and the collaborative division of labor of multiple different agents is achieved, each focusing on its specific business process, thereby providing better services to customers. It is also possible to proactively contact customers by analyzing customer data, track customer issues or conduct proactive marketing, and effectively improve customer satisfaction.

A system includes a sensor at a first location proximate a polluting system to collect environmental data of a first type and an energy consumption monitoring platform at the first location to generate energy consumption data associated with the polluting system. The system includes a controller coupled to the sensor and the monitoring platform to direct communication of environmental data and energy consumption data to a remote computing server. A direct air capture (DAC) system at a second location removes a selected pollutant from ambient air and isolates a concentrated form of the pollutant as a raw material. A derivative product creation (DPC) system at a third location produces a derivative product from the raw material. The remote computing system accumulates pollutant credits based on removal of the selected pollutant by the DAC system and dissipates pollutant credits based on some of the energy consumption data.

According to the model training method and device, the task execution method and device, the electronic equipment and the storage medium, in the method, the prompt content, the reply content output by the target model for the prompt content and the process data for generating the reply content can be firstly obtained, and then the prompt content, the reply content and the process data are input into the reward system; therefore, the reward value of each reasoning step in the process data is obtained, and finally, the target model is iteratively trained based on the reward value of each reasoning step. The reward system of the method no longer generates the reward value for the token of the sample, but generates the reward value for each reasoning step in the process data, so that the target model can pay attention to the integrity and logicality of the reply content in the training process, and then the performance and stability of the target model in a complex task and the robustness of the model are improved.

The invention relates to the technical field of computers, and discloses a user behavior response method and device, a storage medium and computer equipment, and the method can be applied to high-interaction-frequency business scenes such as insurance, financial management and credit loan, and comprises the following steps: responding to an operation behavior of a user for a target business; the method comprises the following steps: generating a user operation identifier, collecting user behavior characteristic data, determining a decision buffer period based on the user behavior characteristic data, then obtaining a behavior response strategy corresponding to a behavior response stage in the decision buffer period, and sequentially pushing a plurality of behavior response strategies to a user terminal. And obtaining an operation decision result of the user for the target business after the decision buffer period is ended. According to the method, the user behavior feature data is collected, the decision buffer period is constructed, intelligent pushing of the staged response strategy is combined, accurate recognition and timely intervention of the user behavior intention are achieved before the user executes key operation, and the user retention rate is increased.

The invention discloses an operator data-based point dynamic recommendation system, and the system comprises a data collection module which is used for collecting multi-dimensional data of a user according to user information and external environment information; the data processing module is used for carrying out data cleaning, data integration and storage on the collected multi-dimensional data; the user portrait module is used for performing feature extraction and coding on the processed data and analyzing the extracted features to obtain a user portrait; the dynamic recommendation engine module is used for dynamically selecting an optimal strategy or strategy combination according to different user portraits; collecting feedback data of the user, and dynamically updating the user portrait; and the precise touch engine module is used for pushing the recommended content to the user according to the selected strategy or strategy combination. Mass data resources of an operator can be fully utilized, and intelligent identification of user behaviors and accurate prediction and accurate pushing of personalized demands are realized through deep learning and data mining technologies.

The invention discloses a smart marketing system and device and a medium, and belongs to the field of big data analysis. The system comprises a data support layer used for collecting multi-source heterogeneous data including equipment data, user behavior data and third-party data, and forming data assets by preprocessing the multi-source heterogeneous data; the intelligent decision-making layer is used for identifying the life cycle stage of the current user based on an intelligent model matrix and the data assets, predicting the transition stage of the life cycle of the user and generating a precision marketing strategy and a channel selection scheme of each stage; and the business application layer is used for converting the precision marketing strategy and the channel selection scheme into a specific marketing task, monitoring marketing effect data and feeding back the marketing effect data to the data support layer and the intelligent decision-making layer. According to the system, the intelligent marketing process of full-link data fusion, dynamic life cycle management and automatic marketing closed loop can be realized.

A driver monitoring (DM) computing device for monitoring driving behavior of a driver in real-time is provided. The DM computing device detects a user computer device associated with a driver inside the vehicle. The DM computing device collects state data of the user computer device. The state data includes data as to a state of the user computer device during a currently occurring trip. The DM computing device collects vehicle operation data of the vehicle while the driver and the user computer device are inside the vehicle. The DM computing device compares the collected vehicle operation data and the state data of the user computer device to determine whether the user computer device was activated during the currently occurring trip. The DM computing device causes a driving reward to be applied to an account associated with the driver for inactivity of the user computer device during the currently occurring trip.

The invention belongs to the technical field of electric digital data processing, and discloses a dynamic strategy configuration-based cancel-after-verification process automation system, which comprises the steps of obtaining cancel-after-verification interaction information, performing scene feature extraction and strategy element deconstruction, and forming a strategy element knowledge base; analyzing the voucher identification code, performing multi-dimensional voucher attribute deconstruction and type portrait description, and generating a voucher intelligent portrait; performing rule matching degree evaluation and strategy source tracing, and locking an applicable strategy rule set; performing strategy conflict harmonic analysis and rule priority ranking to generate a cancel-after-verification execution instruction chain; performing flow wave crest prediction and resource scheduling arrangement to form a load balancing strategy table; performing intelligent channel shunting scheduling, and establishing a cancel-after-verification process execution network; according to the invention, the intelligent automation of the cancel-after-verification process is realized, the system processing efficiency is improved, and the method can adapt to complex and changeable business scene requirements.