512 results about "Service Interface for Real Time Information" patented technology

The invention relates to the technical field of satellite communication, in particular to a high-orbit and low-orbit satellite communication resource scheduling method and system, which collects real-time state information of high-orbit and low-orbit satellites, performs digital simulation of a satellite network based on the real-time information, constructs a satellite network management model and predicts satellite trajectory change. The method comprises the following steps: performing multi-dimensional evaluation on a satellite network management model by using a pre-constructed network evaluation framework, generating cross-orbit link evaluation information, analyzing parameters such as link quality and bandwidth, obtaining current service demand information, analyzing a communication resource allocation strategy in combination with a cross-orbit link evaluation result, and formulating a resource scheduling strategy according to strategy analysis. And a high-orbit and low-orbit satellite communication network is constructed through execution of a hierarchical network management mechanism and a cross-orbit data transmission protocol.

Systems and methods for dynamic knowledge integration in LLM systems including receiving multimodal input data comprising text, image, audio, video, and / or code data, extracting information by processing the multimodal input data through a document processor, storing the extracted information in a dynamic knowledge base, receiving a user query at a query processor, identifying knowledge domains related to the user query using domain-specific agents, retrieving real-time information from the dynamic knowledge base responsive to the identified knowledge domains, integrating the real-time information into the processing of an LLM by a dynamic knowledge integrator, and generating a response using the LLM with the real-time information.

The invention relates to the technical field of water conservancy management, and discloses a water conservancy dynamic decision-making method and system based on digital twinning and multi-source heterogeneous data, and the method comprises the steps: carrying out the real-time information capturing of a target water conservancy system, and generating a system operation information scheduling matrix based on a grid geographic model and a time dislocation mark; performing hierarchical slicing on the system operation information scheduling matrix according to a multi-scale time window to form a multi-channel flow framework of regional hydrological dynamic behaviors; analyzing the evolution trends of the water level, the flow and the water quality by using a multi-channel flowing framework and a dynamic fusion analysis operator; dividing a river reach, a reservoir and a regulation and control facility corresponding to the potential risk event as candidate scheduling areas; and based on the local risk coupling network, dynamically optimizing a scheduling strategy, a pump gate operation sequence and a data acquisition frequency, and generating a real-time scheduling and emergency response scheme of the candidate region. The method has the advantage of improving flood early warning accuracy and water supply scheduling efficiency.

The invention relates to the technical field of digital twinning equipment management, in particular to a digital twinning scientific research equipment intelligent management system integrating the Internet of Things and artificial intelligence. The system comprises a multi-source heterogeneous data acquisition unit which is used for performing real-time information acquisition on the operation environment and the equipment state of scientific research equipment; the digital twin mapping unit constructs a temperature and humidity coupling dynamic model fusing a temperature dynamic model and a humidity dynamic model by introducing a temperature and humidity coupling coefficient, and maps data collected from multi-source equipment and a laboratory environment to the temperature and humidity coupling dynamic model; the AI multi-dimensional prediction unit predicts the future running state of the equipment and the environmental risk; and the risk early warning unit analyzes the operation state of the air conditioning equipment and the environment coupling risk thereof in real time based on the prediction result of the AI multi-dimensional prediction unit, and sends out an early warning signal before potential abnormity occurs. The method is used for predicting the equipment fault risk in advance, thereby achieving the purposes of advanced prediction and active intervention.

The invention provides a data physical node isolation scheduling method and system, and belongs to the technical field of distributed storage and cloud computing. The method comprises the steps of collecting attribute information of tenants and establishing a tenant demand model; monitoring in real time and predicting the resource load of the physical node by using machine learning, and generating a resource evaluation report; formulating differentiated isolation strategies according to the data security levels of the tenants, adopting physical isolation for the tenants with high security levels, and distributing independent physical nodes for the tenants; the scheduling priority is allocated based on the business emergency degree and the resource demand of the tenant, the node load condition is combined, the high-priority tenant is preferentially scheduled to the node with the load lower than the preset threshold value, and meanwhile, the strategy is dynamically adjusted according to real-time information. The corresponding system comprises a tenant management module, a resource monitoring module, an isolation control module and a scheduling decision module. Unification of data security isolation and efficient and dynamic resource scheduling in a multi-tenant environment is achieved, data security and service quality are effectively guaranteed, and the resource utilization rate is increased.

The invention provides an electronic acupuncture closed-loop control method and system based on multi-modal information feedback. The method comprises the following steps: acquiring long-term, short-term and real-time representation information of a testee under an initial stimulation scheme; the long-term and short-term characterization information is input into a collaborative generative network model for learning, a target stimulation scheme is output, the collaborative generative network model comprises traditional Chinese and western medicine agents, the traditional Chinese and western medicine agents learn the long-term and short-term characterization information, and a corresponding traditional Chinese medicine treatment scheme and an electrical stimulation scheme are output. The collaborative generation network model carries out collaborative training on traditional Chinese and western medicine agents; calculating an index deviation between the real-time characterization information and the standard characterization information to generate a real-time information deviation matrix; inputting the target electrical stimulation scheme and the real-time information deviation matrix into a parameter deviation prediction agent for learning and prediction; and performing parameter adjustment on the target stimulation scheme based on the predicted stimulation parameter deviation matrix to realize long / short time and real-time double-layer closed-loop control of the electronic acupuncture.

A computer-implemented method for performing searches in a document database is disclosed. The method comprises automatically detecting a line of business associated with a user, receiving a text query from the user, and generating a query embedding from the text query. The method further comprises scoring entries in a reverse index using a hybrid scoring function. The reverse index comprises titles, title embeddings, sentences, sentence embeddings, and entity tags corresponding to documents in the document database. The hybrid scoring function is used to generate a score based both on a keyword match score between the text query and the reverse index and on a cosine similarity score calculated from embeddings in the text query and in the reverse index. The method also comprises ranking scores for sentences in the document database, and displaying a sentence associated with a top score to the user.

The invention discloses a multi-channel coal quality online detection system and method based on signal enhancement, belongs to the technical field of coal quality detection, and solves the problem that the accuracy and stability of a detection result are affected as a fixed threshold rule adopted by wavelet threshold denoising in the existing method cannot adapt to noise characteristic changes in different temperature intervals. The method comprises the steps of performing signal enhancement preprocessing on a real-time information set, performing initial feature selection on a signal enhancement set based on an index identification model, and performing index collaborative correction based on a drift risk amount of an initial index set and the initial index set; according to the method, signal enhancement preprocessing is carried out on coal quality multi-channel spectral information and associated environment information which are acquired in real time, interference of environmental factors on spectral signals is considered during signal enhancement preprocessing, and interference of the environmental factors on the signals can be effectively compensated through coupling of a field three-dimensional temperature field and a self-adaptive time period; therefore, the stability and the accuracy of the signal are improved.

The invention relates to the technical field of artificial intelligence and education, and discloses an AI Agent technology-based college entrance examination voluntary reporting intelligent consultation system, which comprises a multi-Agent cooperation module, a domain knowledge graph module, a natural language processing module and a multi-source database module. According to the college entrance examination voluntary reporting intelligent consultation system based on the AI Agent technology, a college entrance examination consultation domain knowledge graph is constructed based on a Neo4j graph database through the domain knowledge graph module, the relationship between entities such as schools and majors and admission batches is stored, multi-dimensional association is efficiently processed through an entity relationship network, university and Major Recovery Agent of the multi-Agent cooperation module is combined with the knowledge graph to screen the schools and the majors, and the college entrance examination voluntary reporting intelligent consultation system based on the AI Agent technology is obtained. The Check Agent verifies data, the Web Search Agent supplements real-time information, and the problems that a traditional database is low in complex relation processing efficiency and cannot recommend in real time are solved.

The invention discloses a multiplexing method and system for improving 5G mobile communication spectrum efficiency, and belongs to the technical field of dynamic spectrum multiplexing communication. The method comprises the steps of collecting real-time information, predicting spectrum availability and inter-band interference by utilizing a neural network model, generating a dynamic spectrum multiplexing strategy, issuing the strategy, adjusting parameters and continuously monitoring and optimizing. According to the method, an intelligent prediction model fusing MLP and LSTM networks is adopted, spectrum availability and inter-band interference prediction are provided, and prediction confidence information is generated; a self-adaptive multi-target intelligent optimization algorithm is applied, and the algorithm can dynamically adjust and optimize the weight according to a real-time network; local optimality judgment is carried out by combining local real-time information through the intelligent reconstruction capability of the 5G base station; and continuous monitoring and closed-loop optimization are realized by using an online learning mechanism. According to the invention, dynamic intelligent management of 5G network spectrum resources can be realized, and the 5G mobile communication spectrum efficiency is significantly improved.

Various embodiments described herein disclose an endpoint modeling and grouping management system that can collect data from endpoint computer devices in a network. In some embodiments, agents installed on the endpoints can collect real-time information at the kernel level providing the system with deep visibility. In some embodiments, the endpoint modeling and grouping management system can identify similarities in behavior in response to assessing the data collected by the agents. In some embodiments, the endpoint modeling and grouping management system can dynamically model groups such as logical groups, and cluster endpoints based on the similarities and / or differences in behavior of the endpoints. In some embodiments, the endpoint modeling and grouping management system transmits the behavioral models to the agents to allow the agents to identify anomalies and / or security threats autonomously.

The invention proposes a robot path planning algorithm based on a particle swarm optimization algorithm and a dynamic window method, and relates to the field of control theories and electronic information, and the method comprises the steps: introducing an inertia weight updating strategy based on a state factor, setting adaptive parameters and crossover and mutation operators to improve the global search capability, increase the population diversity, and improve the robot path planning precision. On-line self-adaptive updating of inertia weight and learning factors is realized on line in combination with Q-learning, gene combination modes are enriched through crossover operators, convergence and exploratory performance of the algorithm are improved, an obstacle avoidance strategy of a traditional DWA algorithm is improved, weight parameters of a dynamic window evaluation function are dynamically adjusted according to real-time information of a target and an obstacle, and an obstacle avoidance algorithm is established. According to the method, the global planning is adopted, the path points generated through global planning are adopted as temporary targets, fusion of MOQLCOPSO and the improved DWA algorithm is achieved, local optimum is effectively avoided, the planning efficiency and path safety are improved, and the method is suitable for mobile robot navigation under the complex three-dimensional terrain.

The invention relates to the technical field of data processing, and discloses an operation and maintenance task processing intelligent distribution management system and method based on data analysis, and the system comprises a data collection module; a life cycle analysis module; a task plan making module; an operation and maintenance personnel task distribution module; and a path planning and dynamic adjusting module. Based on data analysis, in combination with the equipment operation state, the skill of the operation and maintenance personnel and the load condition, the execution sequence and route of the operation and maintenance tasks are optimized through intelligent allocation and route planning, task allocation and route can be dynamically adjusted according to the health condition of the equipment, the task priority and the real-time information of the operation and maintenance personnel, and the operation and maintenance efficiency is improved. The operation and maintenance task is efficiently and accurately completed, and the overall working efficiency and the resource utilization rate are improved.

The invention discloses an under-actuated unmanned surface vehicle safe formation tracking control method based on robust obstacle control. The method comprises the following steps: establishing a multi-unmanned ship group and performing real-time communication, and enabling each follower to follow a leader according to a formation configuration and to avoid an obstacle; a safe formation tracking control framework of the underactuated unmanned surface vehicle is established, during formation tracking, followers input state information into the control framework, processing is carried out according to a reference trajectory of a leader and real-time information of a current follower and an obstacle, and forward and steering control torque instructions are output to control the current follower. Obstacles are avoided and formation configuration is restored to continue following the leader. According to the method, the underactuation characteristic problem of the unmanned surface vehicle is solved, the worst case error generated when the neural network approaches the unknown dynamic state can be effectively compensated, it is ensured that the unmanned surface vehicle can strictly avoid collision with the obstacle in the complex environment, and meanwhile the formation tracking performance is optimally kept.

The invention relates to the technical field of intelligent traffic systems, in particular to a personalized traffic travel route recommendation method based on multi-source data. The method mainly solves the problem that in the prior art, real-time collaborative optimization of a dynamic traffic environment and user personalized requirements is difficult. Real-time information is collected through a multi-source heterogeneous traffic data acquisition module, and a standardized data set is generated through data fusion processing; a dynamic user portrait is constructed in combination with machine learning modeling; adopting a multi-target constraint path to search and calculate personalized candidate routes; dynamically re-planning an optimal route based on the real-time traffic flow; and finally, continuously updating the user portrait through an interactive feedback closed loop. The collaborative optimization of traffic state perception and user preference dynamic matching is realized, and the accuracy and timeliness of route recommendation are remarkably improved.

The invention relates to the technical field of vehicles, and discloses an engine intelligent layered thermal management system and method based on multivariable predictive control, and the system comprises a thermal management execution module, an information sensing module and an intelligent control module; the information sensing module is used for collecting real-time information and sending the real-time information to the intelligent control module; the information sensing module comprises a plurality of sensors and a communication interface, the plurality of sensors at least cover a temperature sensor, a pressure sensor and a flow sensor, and the communication interface is used for obtaining engine torque, rotating speed, fuel injection amount, boost pressure and vehicle speed information; the intelligent control module receives the real-time information sent by the information sensing module, performs thermal load prediction and multi-target optimization calculation to obtain an optimal control sequence, and sends the optimal control sequence to the thermal management execution module; and the thermal management execution module receives the optimal control sequence and calls an execution element to execute a thermal management action.

This invention relates to a method for visually recognising and tracking objects and events in 3D space with high accuracy, reduced computational load and fast setup, using virtual sensors that are designed to ensure high reliability and reduce costs by maximising their potential for accurate object recognition for given visual input data. The main task of a virtual sensor is to provide cost-effective and reliable data and replace the use of humans and / or hardware sensors to detect and recognise objects or events that are important to a given entity, such as an industrial enterprise and various business entities. The solution is well suited for industrial applications, especially for tracking larger objects of known shape or appearance, such as in large industrial halls, warehouses without fixed racking systems, container docks, train docks, car parks, etc. It is particularly suitable for tracking coils, metal pieces and larger building components. The method provides a reliable source of i data for obtaining a digital twin of the monitored objects, which represents real-time information about each stock keeping unit (SKU) in the warehouse (WH), bringing significant benefits to WH managers and thus saving human labour spent on searching for materials, improving management flow, reducing overall equipment effectiveness (OEE) of vehicles, improving throughput, quality, etc.

The invention relates to a navigation aid decision-making method based on a large model, which comprises the following steps of: constructing a scene knowledge model of real-time information such as intelligent navigation situation awareness, situation cognition and intelligent navigation design operation conditions, and designing entities, attributes and relationships between the scene knowledge model and navigation knowledge to form a navigation knowledge aid decision-making graph mode; collecting and preprocessing navigation knowledge data, and constructing a user-defined navigation knowledge data set; performing fine tuning on the pre-trained general large model through the knowledge graph extraction data set, and constructing a knowledge graph knowledge extraction large model; performing fine tuning on the pre-trained general large model through the knowledge question-answer fine tuning data set, and constructing a navigation knowledge question-answer large model; constructing a navigation knowledge aided decision-making knowledge graph; based on the navigation knowledge question and answer large model and the navigation knowledge aid decision knowledge graph, constructing a navigation aid decision generation model based on reinforcement learning; and designing the navigation aid decision-making device based on the intelligent voice interaction mode. The method can provide auxiliary decision support for ship navigation.

The invention relates to the technical field of scenic spot route planning, and provides a scenic spot global collaborative touring planning method and system, and the method comprises the steps: constructing a scenic spot environment depth model, and deploying an ant colony algorithm on the constructed scenic spot environment depth model through key parameter initialization and tabu table initialization; path selection is carried out by executing ant colony movement, and real-time information updating and ant colony collaborative obstacle avoidance are carried out in the movement process; constructing a pheromone updating rule to update global pheromones, and judging and outputting an optimal path through iterative convergence; and performing multi-dimensional verification on the output optimal path, and generating a personalized touring scheme according to the path passing the verification. According to the invention, collaborative planning and dynamic optimization of the scenic spot sightseeing path are realized, the sightseeing efficiency of tourists is effectively improved, the queuing time is reduced, the information interaction comprehensiveness is enhanced, and the overall operation efficiency and tourist experience of the scenic spot are remarkably improved.

The invention provides a technology transfer industry chain management method and system adopting a dynamic matching algorithm, and relates to the technical field of industry chain management, and the method comprises the steps: constructing feature vectors of a technology supplier, a demand side and an intermediary node, and obtaining a node feature vector set; obtaining an initial transfer path based on the node feature vector set in combination with a directed acyclic graph method; carrying out real-time information collection, and constructing a multi-level atlas comprising a plurality of transfer nodes and a cooperative relationship; obtaining a transfer prediction result in combination with the historical transfer data and the node attribute information; and according to the transfer prediction result, combining the upstream and downstream dynamic information of the industrial chain, performing path optimization by using a multi-target dynamic matching algorithm, obtaining a target technology transfer path, and executing technology transfer industrial chain management according to the target technology transfer path. The technical problems of prominent capability bottleneck and low conversion success rate of technology transfer industry chain management in the prior art are solved.

The invention provides an intelligent question and answer method, system and device and a medium, and belongs to the technical field of artificial intelligence. The method comprises the steps that a natural language question input by a user is obtained through a front-end interaction interface, and a user question is generated after structured packaging; calling a search engine interface, performing information retrieval according to the user question, and generating corresponding webpage content; performing structured analysis and cleaning on the webpage content to generate a structured text; and based on the user question and the structured text, generating cue words according to the cue word template, and inputting the cue words into the large language model to generate answers. By combining the natural language understanding and processing capability of the large model and the real-time information acquisition capability of the retrieval enhancement technology, the search content is deeply integrated and refined, and more efficient and accurate question and answer experience can be provided for the user.

The invention discloses an intelligent fire-fighting resource dynamic scheduling method based on the Internet of Things, and relates to the technical field of fire-fighting emergency intelligent scheduling, and the method comprises the steps: collecting fire-fighting global situation awareness data, synchronizing the data to a central database through an encryption protocol, and constructing a fire-fighting real-time commanding combat information system; based on a combat information system of fire-fighting real-time commanding, a combat guarantee scheme is formulated, meanwhile, fire-fighting power information, geographical and meteorological information and field real-time information are collected, and a dynamic dispatching instruction is generated; dynamically mapping the dynamic scheduling instruction to a fire-fighting resource state, generating a resource state mapping table, optimizing resource allocation through a resource priority scoring function and a linear programming model, and generating a resource scheduling scheme; performing Bayesian verification and rating processing on professional pointing information in execution of the resource scheduling scheme to generate a targeted action instruction; according to the method, the continuous evolution capability of the scheduling model is realized through a multi-agent voxel learning parameter adjustment framework of the empirical rule base.

The invention discloses a power distribution overhead line icing thickness detection method, system and device and a storage medium, and relates to the field of icing thickness detection.The method comprises the steps that multi-source detection data of a power distribution overhead line is collected, self-adaptive interpolation completion is conducted based on data distribution characteristics, for example, bilinear interpolation is conducted on a two-dimensional image, linear interpolation is conducted on sequence data, and the detection result is obtained; complementing point cloud data in combination with information such as wind direction; performing multi-source icing thickness detection on the detection data set, and calculating a detection sequence based on image pixel gradient, point cloud intensity and the like; performing multi-source fusion by adopting Bayesian inference to obtain an accurate detection value and a confidence interval; predicting an icing trend in combination with historical data, and performing real-time monitoring and early warning; according to the invention, image edges and ice layer boundaries can be protected, so that interpolation better conforms to physical phenomena, and the detection precision is improved; icing thickness features are described from different aspects, posterior probability distribution can be updated by combining prior and real-time information, the icing thickness is accurately estimated, uncertainty is quantified, and powerful support is provided for decision making.

The invention relates to the technical field of business and financial management, in particular to a business and financial fusion analysis decision management system and method based on multi-modal AI, and the method comprises the steps: configuring deep learning and testing according to financial use and formation information, and obtaining a multi-source contact analysis record; according to the multi-source connection analysis record, feature line and non-feature line difference is configured, and a fusion decision result is obtained; according to the fusion decision result, configuring information-driven machine learning and clustering analysis to obtain a decision value decision record; configuring real-time information analysis according to the real-time decision plan to obtain a real-time financial analysis record; configuring flow analysis according to the real-time financial analysis record to obtain a flow decision result; and configuring real-time information flow analysis and personalized management according to a process decision result to obtain a real-time management result. According to the method, the capability of effectively integrating different information sources is achieved, and the real-time decision-making and long-term financial demand evaluation effects are good.

The invention relates to the field of railway shunting management and control, and provides a field intelligent shunting management and control method and device.The method comprises the steps that field real-time information is obtained, and the field real-time information comprises a vehicle license plate picture, laser ranging information and an original signal collected by a track circuit; the field section real-time information is recognized, modeling information is obtained, and the modeling information comprises vehicle identity information, vehicle position coordinates and real-time station track occupancy states; establishing a digital twinborn model according to the modeling information; performing dynamic planning algorithm processing according to the digital twinborn model in combination with preset vehicle target distribution, station track capacity limitation and locomotive performance parameters to obtain a shunting coupler plan; the turnout position is adjusted to the preset angle according to the shunting coupler plan, the overall efficiency of shunting operation and the accuracy of the plan can be remarkably improved, and the safety and reliability of the operation process are effectively enhanced.

A method for using contextual searching, such as intelligent search engines, to search for specialized machine learning models, such as customized LLMs (LLMs) tailored to individuals, organizations, and entities, to provide users with access to real-time data, static data, and advanced search capabilities. Therefore, methods and systems are described herein for ensuring precise and efficient information retrieval by identifying relevant artificial intelligence models, such as custom large-language models.

The present invention relates to the technical field of industrial device detection, and discloses a device damage intelligent monitoring method and system based on mechanism and working condition big data. The monitoring method comprises: first, setting various damage modes of a device, constructing a mechanism model sample of each damage mode on the basis of a technical standard and an engineering case, and constructing a working condition big data sample of each damage mode on the basis of field data; then, using the mechanism model sample and the working condition big data sample as data sets for model training so as to respectively construct a mechanism model and a working condition model; and finally, inputting real-time text data to be predicted and real-time working condition data to be predicted into the mechanism model and the working condition model, respectively, calculating the possibility that the real-time text data belongs to various damage modes and the possibility that the real-time working condition data belongs to various damage modes, and generating a device damage monitoring result on the basis of the two possibilities. The present invention effectively improves the utilization rate of real-time information during damage monitoring of a pressure-bearing device, so that the monitoring result is more accurate.

The invention discloses a method and a device for reporting equipment information. The method comprises the steps that when it is determined that target intelligent equipment executes equipment information reporting operation according to an initial information reporting strategy, actual equipment related data of the target intelligent equipment is acquired, and the initial information reporting strategy is a reporting strategy determined according to historical equipment related data of the target intelligent equipment; the historical equipment related data is data related to the use of the target intelligent equipment; adjusting the initial information reporting strategy according to the actual equipment related data to obtain a real-time information reporting strategy; and issuing the real-time information reporting strategy to the target intelligent equipment, so that the target intelligent equipment reports the equipment information according to the real-time information reporting strategy. According to the method and the device, the technical problem that in the related technology, the Internet of Things equipment reports the state to the cloud server at a fixed time, and when the quantity of the equipment is large and the access quantity of a third-party cloud platform is large, the reporting mode is easy to bring pressure to the server is solved.

The invention belongs to the technical field of intelligent path planning, and particularly relates to a hazardous chemical substance transportation path planning method based on an improved ant colony algorithm, and the method comprises the steps: S1, data collection and preprocessing; s2, constructing a transportation network model; s3, parameters of the improved ant colony algorithm are initialized; s4, ant path searching; s5, updating the pheromones; s6, dynamic path adjustment; in the transportation process, according to new road condition information and transportation requirements, recalculating the attribute and weight of each path, correspondingly adjusting the position of the ant and the taboo table, and then continuing to perform path search and pheromone updating to find a new optimal or sub-optimal path; and S7, evaluating and optimizing the path. According to the method, hazardous chemical substance characteristics, road safety conditions and surrounding risk sources are fully considered in path planning; in combination with traffic real-time information and a dynamic path adjustment mechanism, a congested road section and a sudden accident area can be avoided in time, and it is ensured that the transport vehicle always selects an optimal or suboptimal path for driving.

Secure blockchain (BC)-based tokens are issued and linked to payment cards and / or devices of customers. Custom conditions associated with the tokens are stored in smart contracts on a BC. The tokens are stored in a cloud-based key vault and / or in the BC. Validation of a token for access a smart contract on the BC can only be made by a financial institution (FI) to the key vault. Real-time information for a transaction device, for transaction information, and / or for the customer is provided as input data to the smart contract for evaluation of the conditions. After the token is authenticated by the key vault, the real-time information is gathered and passed to the corresponding smart contract on the BC for evaluation. The FI receives transaction authorization or transaction denial based on the smart contract's evaluation of the conditions.