399 results about "Spatial computing" patented technology

The invention belongs to the technical field of coal mine disaster early warning, and discloses a coal mine fire and gas disaster risk prediction method and system, and the method comprises the steps: collecting multi-source heterogeneous data collected at a mine site, and carrying out the data preprocessing and conversion; for the preprocessed image and video data, a Video Swin Transform model is adopted to extract spatial and temporal features, and a cross-modal association fusion Transform model is adopted to realize multi-modal feature unified fusion; mapping the fused multi-modal feature representation to a disaster-causing factor index space, calculating a risk assessment index containing a secondary interaction item, and dividing risk levels; and generating a disaster early warning strategy according to risk level analysis, issuing an early warning notice, performing regular maintenance and updating, and outputting a decision report. According to the method, unified processing and fusion representation of multi-source heterogeneous data can be realized, complex association among disaster-causing factors is accurately captured, the risk index with physical significance and engineering reference value is calculated, and high-quality decision support is provided for prevention and control of coal mine fire and gas disasters.

The invention discloses a multi-agent cooperation system and method based on spatial calculation and multi-modal AI fusion, and the method comprises the steps: collecting all real-time data of a construction site through a multi-modal data collection and fusion unit, and carrying out the processing and integration of all collected data through a multi-modal AI algorithm, and generating a unified semantic association model; a three-dimensional virtual environment of a construction site is constructed through a space calculation unit, real-time synchronous mapping is formed for the construction site, and dynamic changes in the construction process are simulated and predicted; task allocation and behavior planning are carried out on multiple agents through an agent behavior management unit; and the intelligent agents are configured to perform real-time information sharing and task cooperation through a communication protocol through the multi-intelligent-agent cooperation unit. According to the scheme, the problems of difficulty in multi-source data integration, low cross-department cooperation efficiency, insufficient construction dynamic adjustment and the like in intelligent construction in the building industry can be solved.

The invention discloses a high-accuracy threat intelligence assisted network threat tracing method, which comprises the following steps: S1, collecting and preprocessing multi-source network security data, and constructing a time-marked event sequence set; s2, constructing an optimized Transform network model, and processing an attack event sequence by using position coding and time embedding; s3, a black swan optimization algorithm is initialized, and a Transform structure hyper-parameter is dynamically optimized; s4, outputting an attack event semantic vector, and constructing an attack path semantic map; s5, the intelligence information vector is embedded into a Transform hidden space; s6, calculating semantic similarity and dependency intensity, and generating an attack source candidate set and a traceability path; s7, outputting an attack traceability path, a starting point node and an information label, and generating a structured traceability report; and S8, according to the traceability result feedback, updating the black swan algorithm and the Transform model. The method is used for realizing intelligent modeling of multi-source network attack events and high-accuracy traceability analysis of attack source nodes.

The invention discloses a power construction unmanned aerial vehicle path planning method and system, and relates to the technical field of space calculation, and the method comprises the following steps: determining a target region needing power construction and a preset construction point coordinate; obtaining a topographic map of the target area based on the geographic information database, constructing a three-dimensional map model, and marking the preset construction point coordinates; generating an initial construction path of the unmanned aerial vehicle; the method comprises the following steps: acquiring meteorological data in real time through meteorological data of a meteorological station in a target area, establishing a meteorological obstacle three-dimensional model, and dividing a preset radius threshold with a meteorological obstacle as a circle center into non-flying areas according to the severity level of the meteorological obstacle; adjusting the initial construction path based on the non-flying area; the cruise height is adjusted according to the meteorological data and topographic relief, a relief tracking path is generated, and the constant relative height is kept; and combining the battery capacity, the flight speed and the task priority, dynamically distributing inspection road sections, and generating a corresponding power construction unmanned aerial vehicle flight path.

The invention provides a PICC puncture virtual simulation training system and method constructed based on XR. A nursing skill simulation training platform and an intelligent training room based on augmented reality (XR) combine a simulation medical technology, an artificial intelligence large model, XR intelligent hardware, intelligent agent application, space calculation, computer vision and a mainstream technology of Internet of Things in scheme planning and design. According to the PICC puncture virtual simulation training platform, the ground practice, standardization, high virtual simulation and adaptive application of PICC puncture virtual simulation training are realized, and the intelligent development process and teaching concept of PICC puncture teaching are improved. According to the PICC puncture teaching system, intelligent virtual tutors, puncture teaching holographic three-dimensional sharing, virtual reality fusion technologies and the like are provided, an interactive teaching mode can be brought to PICC puncture teaching, the interest of students in teaching and clear operation guidance are improved, the theory and practice are fused, and the clinical cooperation ability is improved.

The invention relates to the technical field of government and enterprise services, and discloses an intelligent adaptation system and method for government and enterprise services, and the method comprises the following steps: carrying out the structural analysis of an original policy text through a deep learning model, including word segmentation, word vector generation, dominant condition extraction and implicit condition reasoning, and finally constructing a policy knowledge graph; the multi-source heterogeneous data is integrated, dynamic enterprise feature vectors are generated through spatial-temporal feature construction, industrial association diagram modeling and spatial-temporal diagram convolution calculation, the enterprise state change gradient is detected, and the abnormal fluctuation risk is recognized; and mapping the policy condition vector and the enterprise feature to a hyperbolic space, calculating a hyperbolic distance and converting the hyperbolic distance into a matching degree, superposing timeliness attenuation, data freshness punishment and state mutation filtering, and outputting a final matching result. According to the invention, a closed-loop system of policy analysis, accurate matching, resource allocation and feedback optimization is finally constructed, the financial resource waste rate is compressed to a low level, and the government affair service efficiency is improved.

A system for providing an extended reality environment that incorporates real-world event data into 3D models representative of the real-world event within the extended reality environment includes an XR processing unit configured to dynamically download 3D hole models of the course, receive real-world live shot data of shots taken on the holes during a golf tournament; map the shot data to the 3D hole models; and cause a spatial computing device to render hole views and immersive views comprising the mapped shot data rendered directly on the 3D hole models in real-time in an interactive extended reality environment. The mapped shot data includes shot trails representative of the shots taken on the golf course, The hole views and immersive views may utilize the same source file.

An AI-powered augmented reality (AR) system for optimizing product placement and customer loyalty. The system includes: • a user interaction data collection unit configured to monitor consumer behavior in real time in any retail scenario (point-of-sale POS, online e-commerce and shopping areas within a public virtual technology space), with the unit analyzing consumer movement patterns, engagement metrics, eye-tracking and purchase intent; • an intelligent spatial mapping module to build a contextual understanding of high-traffic zones, underutilized areas and high-quality product placements using heatmap analysis, other spatial computer algorithms and the live movement of consumers; • A model-based product placement recommender based on machine learning, which uses one or more DL-based predictive models trained by importing current sales data, historical text interaction data, and consumer preference data to suggest optimal product placement so that customers see the advertisement and are likely to click through it to ensure a conversion. • a customer-centric, real-time AR visualization interface configured to allow customers to experience digitally enhanced product presentations directly via mobile AR applications, smart glasses, or in-store digital kiosks, enabling customers to preview product placements, rotate and resize objects, and visualize interactive advertising content before purchasing; • a customized advertising and sales promotion engine configured to generate augmented reality-based marketing content and provide users with tailored promotions and interactive ads based at least in part on an analysis of consumer sentiment by the system, as well as information on location data or consumer interaction history, wherein the customized advertising and sales promotion engine personalizes the configuration instructions for advertising and sales promotion to encourage consumer interaction and achieve higher sales revenues; • A secure, cloud-based data processing and analytics unit that uses an automated engagement model to link online and in-store sales information with established activity models for product placement decisions. The unit leverages AI-powered consumer insights to continuously recommend product placement changes based on a variety of programmatic retail trends; • a privacy-friendly AI module based on federated learning and on-device AI processing, providing consumer behavior analytics while complying with global data protection regulations and preventing the use of open data; • a processing framework characterized by a low-power mode suitable for AR rendering and AI calculations, and implemented via dynamic voltage scaling and energy management techniques for seamless and sustainable operation; The system according to claim 1, wherein the user interaction data capture unit further comprises an eye-tracking and sentiment analysis sub-module, wherein the sub-module detects facial expressions, emotional reactions, and attention levels of consumers in real time to determine the effectiveness of product placements and advertising strategies.

The invention discloses a cross-platform virtual-real fusion scene construction method and system based on AI space calculation, and relates to the technical field of artificial intelligence and space calculation, and the method comprises the steps: carrying out the multi-scale feature fusion based on a received cross-modal conversion instruction set, and generating an initial image sequence; carrying out implicit field coding on a target object by combining a three-dimensional reconstruction algorithm to obtain an initial parameterized model; performing space-time alignment on the multi-view video stream, loading a digital scene asset package in combination with physical sensing data and a preset spatial index structure, and establishing a bidirectional data channel between a virtual scene and a physical sensor; performing rendering and illumination parameter adjustment on the initial parameterized model to obtain an optimized parameter model; performing differential coding processing on the optimization parameter model to obtain a target virtual-real scene fusion model; and distributing the target virtual-real scene fusion model to a preset terminal. The invention provides a virtual-real fusion construction method for end-to-end collaborative optimization, which is suitable for cross-platform live broadcast or dynamic interaction scenes.

Methods and systems enabling multimodal inputs for interacting with a live digital object are provided. The system receives the live digital object which includes a digital artifact extracted from a digital model file through a model representation. The system receives a user's security level and determines the user's access permission and modification permission to access and modify the digital artifact. The system accesses a multimodal interface configured to receive a conversational input and a spatial input, outputs the digital artifact to the multimodal interface based on tire access permission, receives from the multimodal interface a conversational input and a spatial input from tire user, and generates a modified digital artifact from the digital artifact via the digital model representation, based on the modification permission and on the conversational or spatial input. The multimodal interface may include conventional interfaces (GUIs / APIs), conversational interfaces (text / voice), and spatial computing interfaces (VR / AR / MR / gestural).

The invention provides a beach big data geographic space intelligent application service method based on a large model Agent, and relates to the technical field of geographic space data artificial intelligence processing and analysis. According to the method, a distributed platform comprising a parallel computing cluster, a spatial database and a large language model is constructed, and standardized storage and metadata management of multi-source remote sensing, vector and attribute data are supported. The system generates a spatio-temporal query instruction through natural language analysis, completes cross-source matching and spatial calculation, outputs an analysis result in a multi-modal form such as a map, a chart and a text, and realizes intelligent and interactive service of geographic data processing.

Methods and systems enabling multimodal inputs for interacting with a live digital object are provided. The system receives the live digital object which includes a digital artifact extracted from a digital model file through a model representation. The system receives a user's security level and determines the user's access permission and modification permission to access and modify the digital artifact. The system accesses a multimodal interface configured to receive a conversational input and a spatial input, outputs the digital artifact to the multimodal interface based on the access permission, receives from the multimodal interface a conversational input and a spatial input from the user, and generates a modified digital artifact from the digital artifact via the digital model representation, based on the modification permission and on the conversational or spatial input. The multimodal interface may include conventional interfaces (GUIs / APIs), conversational interfaces (text / voice), and spatial computing interfaces (VR / AR / MR / gestural).

The invention belongs to the technical field of industrial operation and maintenance term processing, and provides a big language model training method based on a knowledge graph, and the method comprises the steps: carrying out the cooperation with operation and maintenance personnel in advance to set a fault dictionary, collecting fault instances, carrying out the classification and preprocessing, extracting causal trigger words of the fault instances, and setting a text dependency relationship rule. Splitting and extracting a triple of the fault instance, and importing to form a knowledge graph; mapping the instance attribute into a node feature vector, outputting an embedded representation of a node, and fusing the embedded representation with the multi-modal feature vector to form a fused feature embedded representation; replacing semantic and degree words with fault instances in the knowledge graph to generate positive samples, randomly replacing subjects, objects and causal relationships to generate negative samples, inputting the negative samples into a semantic encoder, mapping the negative samples to the same metric space, and calculating similarity to obtain a comparison loss value to adjust graph convolutional network parameters; and after the fusion feature embedding representation retrieval of the fault instance is carried out and a subgraph is generated, maintenance suggestions are given step by step along a causal chain.

The invention provides a geographic knowledge complex question-answering method based on a space-time agent architecture. The geographic knowledge complex question-answering method comprises the following contents: natural language analysis: accurately understanding intentions of users and information contained in questions; multi-modal geographic entity recognition: processing non-text data contained in user input; generating a WKT format and injecting a prompt; knowledge graph retrieval enhancement; in the spatial computing tool chain arrangement, an LLM generates a problem solving scheme after combining multi-modal information, WKT geometry and related data resources associated with a knowledge graph, tools or functions needing to be called and an execution sequence of the tools or the functions are listed, and the series of tools adopt a model context protocol; in answer generation and response, the method can effectively solve the problems that in the prior art, when complex geographic questions and answers are processed, question input recognition is incomplete, reasoning steps are not accurate, and the answer basis is not real, and more intelligent and reliable question and answer support is provided for the field of natural resource planning and the like.

The invention relates to the technical field of power equipment operation and maintenance and state monitoring, in particular to an optical fiber transformer health state assessment method and system based on feature fusion. According to the invention, sampling signals of a plurality of optical fiber current transformers are collected and preprocessed; constructing a historical data matrix for principal component analysis, establishing a principal component space and calculating a square prediction error control limit value; constructing a simulated fault data set and projecting the simulated fault data set to a principal component space to calculate a square prediction error time sequence; performing wavelet packet decomposition on the square prediction error time sequence to extract a normalized energy feature vector, and training a one-dimensional convolutional neural network model; projecting the real-time sampling signal to a principal component space to judge whether the real-time sampling signal exceeds the limit or not; if yes, the health state level is output through the trained model. According to the invention, accurate grading and real-time online evaluation of the health state of the optical fiber transformer are realized.

The invention discloses a robot redundant attitude planning method and system based on position and obstacle constraints, and the method comprises the following steps: generating a planning path of a robot based on a redundant attitude space and a known robot path position point, the planning path being represented by a position space and an attitude space; constructing an approximate key collision plane; calculating a feasible attitude area based on the obstacle information and the redundant attitude space on the approximate key collision plane; estimating a preferential sampling attitude area; continuously sampling in the position space and the attitude space, acquiring a pose node to expand the random search tree until a target node is reached, and acquiring a target path; and iterating the random search tree extension operation to obtain more target paths, and selecting a target path with the lowest total cost from all the obtained target paths. According to the method, the exploration efficiency of redundant attitude planning can be improved, the integrity and safety of the process are ensured, and the method has relatively high applicability.

The invention discloses a stiffness matrix compression storage method and system based on block symmetry characteristics and a medium, and the method comprises the following steps: constructing a geometric model, and obtaining material attribute parameters; dividing finite element analysis grids according to the geometric model, and numbering units, nodes and degrees of freedom; setting boundary conditions and load applying conditions; a storage space is applied based on the block symmetry characteristic of the global stiffness matrix; calculating an element stiffness matrix, assembling element stiffness matrix information to a global stiffness matrix, and applying a boundary condition; and solving a finite element equation corresponding to the compressed and stored global stiffness matrix by adopting a numerical solution method. According to the method, the reducibility of the stiffness matrix is kept, redundant information stored in the stiffness matrix is reduced, and the time complexity of the stiffness matrix and vector multiplication and other matrix operation is also reduced, so that the solving performance of the linear equation set is effectively improved.

System and method for managing information compliance and relevance using autonomous artificial intelligence (AI) agents in data transfer and communication environments. Some embodiments may include a core orchestration engine with multiple autonomous AI agents configured to manage and evaluate the compliance and relevance of information in communication and data transfer environments. The system may use weighted metrics to assess if information and actions comply with regulations and are pertinent to recipients, monitor email and data transfer, ensure regulatory compliance, and enhance information and knowledge sharing within organizations. The system may use semantic embeddings, part-of-speech analysis, and language models to extract and apply regulatory rules efficiently. These features may significantly reduce search space, computational overhead, and manual effort while improving security and accuracy.

Systems and methods for immersive data management in spatial computing are disclosed. A method may include: (1) requesting from an identity and access management service executed in a cloud environment, an access token; (2) receiving, from an identity and access management service, the access token comprising user entitlements to access a plurality of elements in a plurality of scenes; (3) requesting one of the plurality of scenes from a scene filtering service, the request comprising the access token; (4) identifying the user entitlements from the access token; (5) retrieving the requested scene comprising a subset of the elements; (6) adding the elements that the user is entitled to based on the user entitlements to a scene to be displayed; (7) returning the scene to be displayed to the computer program; and (8) displaying the scene to be displayed.

The invention discloses a power load prediction method based on a dynamic expert pool and a load balancing mechanism MoE, and belongs to the field of power load prediction, and the method comprises the following steps: collecting multi-dimensional input data needed by power load prediction, detecting and repairing an abnormal value in the input data, and obtaining a power load prediction result; constructing a time-feature matrix by using the repair data; projecting the time feature matrix into three subspaces of Q, K and V, calculating attention weights among feature dimensions, and obtaining enhanced features through attention weighting; the enhanced features are input into a routing layer of the MoE model, selection probability distribution of experts is calculated, the MoE model adopts a dynamic expert pool and introduces a load balancing mechanism, and a Top-2 expert selection strategy is randomly distributed in the reasoning stage; and when the MoE model is migrated to a new scene, updating the attention weight of the MoE model by adopting a meta-learning strategy. According to the method, complex factors influencing the power load can be comprehensively captured, and the power load prediction precision and the cross-scene adaptive capacity are remarkably improved.

A method is provided herein for evaluating a physical building, utilizing an automated image capture apparatus, a spatial computing apparatus, a machine learning model, a blockchain network, and a computer processor, the method including capturing and analyzing images of the building, dividing the building into sections, identifying defective characteristic(s) in and assigning a status to each section, sharing the images and status identifiers with a remote user, the remote user reviewing the images and identifiers, and receiving feedback from the remote user. When a section lacks sufficient images to determine whether a defect is present, the section may be flagged, and a supplemental image(s) may be captured and provided by the remote user. When no additional images are needed, the section may be indicated as completed. Otherwise, the section may retain its flagged status, and the aforementioned steps may be repeated as necessary.

Disclosed are methods, systems, and computer program products that present, by a spatial computing system, an extended reality presentation to a user, wherein the extended reality presentation comprises virtual object(s) generated by a spatial computing system and transmitted to one or both eyes of the user and a physical environment that includes a first physical object and a second physical object and is perceived by the user via light reflected from the physical environment. The extended-reality representation is rendered for an object interaction between the first physical object and the first virtual object or the user. A physics-based effect on the first physical object by the object interaction is determined by using at least a stereoscopic model for the first physical object based at least in part upon the object interaction. The extended reality presentation into an undated extended reality presentation based at least in part upon the physics-based effect.

Various implementations disclosed herein include devices, systems, and methods that convert a mono image to a stereo image pair. For example, a process may obtain an input image including appearance values at pixel positions. The input image corresponds to an appearance of a scene from a first viewpoint. The process may further determine a depth image comprising depth values at original pixel positions that are mapped to corresponding pixel positions of the input image. The process may further generate a first output image corresponding to a second viewpoint of the scene different than the first viewpoint and a second output image corresponding to a third viewpoint of the scene different than the second viewpoint. The process may further enable comfort-based 3D style presets for adjusting comfort parameters for viewing a stereo image pair.

The invention discloses a multi-person interaction method based on a large-space computing technology, and relates to the technical field of multi-person interaction. In order to solve the technical problem that in the prior art, most of existing multi-user virtual interaction systems depend on a single interaction area, so that the user experience is poor when multiple users interact at the same time, the technical scheme provided by the invention is as follows: a multi-user interaction method based on a large-space computing technology is provided. Comprising the following steps: dividing a virtual space into a plurality of functional areas; controlling the temperature of the interaction area and the non-interaction area in real time; sharing of virtual roles is realized through the cloud computing platform; a sharing conflict coordination mechanism is introduced, an operation request of a user for a virtual role is managed, and conflicts are coordinated; creating a virtual computing space and dynamically allocating computing resources by combining distributed computing and a cloud platform; a digital co-construction and sharing platform is built through a 5G network and a holographic image technology, and multi-user interaction and co-construction and sharing of virtual articles are achieved. The method is suitable for being applied to virtual reality scene building work of multi-person interaction.

The present application provides an oral treatment table training system and method based on spatial computing technology, which relates to augmented reality technology and is used to solve the problems that existing simulators only support single-person use and only perform training based on oral models, lack full-process doctor-patient communication, and have low simulation authenticity. With the help of spatial computing technology, the virtual-reality integrated head-mounted viewer obtains the positioning data of entities and the dental chair of the treatment table in the real space, and the situation observation server arranges virtual entities and generates a scene file. The simulation computer generates a virtual-reality integrated treatment scene, virtual patients, and treatment tools according to the scene file, and can simulate the whole process of the patient from entry to treatment. And generate force sense information to control the force sense tool in the force sense information and match the pose of the virtual treatment tool with the force feedback tool. The user wears the virtual-reality integrated head-mounted viewer to perform treatment operations. With the help of network synchronization technology, it supports multiple people to watch the operation process of the same treatment table. The present application improves the comprehensive simulation authenticity.

The invention relates to the technical field of clean energy fault positioning, and discloses a fault positioning method and system for abnormal operation of a clean energy station. A signal collecting and processing module of the system collects a multi-source operation state signal in real time, and a smooth signal is reconstructed after high-frequency noise is removed through self-adaptive filtering; the operation state analysis module extracts time-frequency characteristics of the smooth signal, identifies the operation state stage of the station, and generates a fault characteristic spectrum based on preset parameters and real-time frequency data when the station is abnormal; the three-dimensional station modeling module analyzes terrain detection signals in a multi-scale manner, and constructs a three-dimensional model containing equipment space coordinates, topological connection relations and environment characteristics; the fault prediction module maps the fault characteristic spectrum to a three-dimensional model, divides equipment area subspaces, calculates fault probability distribution and generates a fault thermodynamic diagram and a density gradient field; and the optimization decision module initializes particle swarm optimization algorithm parameters, constructs an operation stability objective function, and generates an optimal fault positioning path scheme in combination with equipment health state constraints.

The invention discloses a virtual power plant and resource matching method and system based on cooperation preference in the field of virtual power plant resource matching, and the method comprises the steps: building a photovoltaic, energy storage and air conditioning load multi-mode cooperation preference scoring model, and quantifying the economic effectiveness, equipment loss, user comfort and other multi-dimensional features; a double-tower representation and contrast learning technology is adopted, and resource attributes and service requirements are mapped to a unified semantic space to calculate the matching degree; in combination with an entropy regular optimal transmission algorithm, many-to-many flexible matching is realized on the premise of considering grid power flow safety constraints; and a rolling multi-cycle optimization mechanism is introduced, and a Bayesian update and reinforcement learning dynamic adjustment strategy is adopted, so that the technical problems of insufficient cooperation intention quantification, complex cross-time constraint and difficult security risk control in distributed resource scheduling under high-proportion new energy access can be solved, and the economy and security of virtual power plant scheduling can be effectively improved. And the performance stability of the system under the new energy fluctuation is enhanced.

The embodiment of the invention provides a method and device for generating a space visual interaction medium based on space calculation, and relates to the field of space intelligence and space audiovisual, and the method comprises the steps: carrying out the preprocessing of an original image, and obtaining first information; performing focal plane simulation processing on the first information to obtain second information; extracting complex data of the first information, and performing wavelet transform on the complex data to obtain a feature set; performing depth estimation and view synthesis on the second information to obtain third information; performing spatial visual interaction on the complex data and the third information to generate a new viewpoint depth map; and determining a spatial video according to the first information, the feature set and the new viewpoint depth map. According to the method, the two-dimensional information is converted into the three-dimensional interaction space video, and the interaction experience of the user is improved.

The invention provides a digital twin enabling air-ground integrated dual power supply network supply-demand game method and system, and belongs to the technical field of intelligent management and control of energy and communication convergence networks. Comprising the following steps: constructing a digital twin system of an energy-communication fusion network, and accessing and mapping dynamic data from an energy network and a communication network in real time; based on the dynamic data, an energy side observation space and a communication side observation space are defined in the digital twin system, and the comprehensive supply and demand imbalance degree of the system is calculated; the energy side intelligent agent and the communication side intelligent agent output control instructions in a continuous action space according to respective observation spaces, and respectively aim at maximizing own long-term accumulated benefits; a final solution of the coordinated game framework is an optimal strategy combination meeting a Nash equilibrium condition; carrying out centralized training and distributed execution on the coordinated game framework by adopting a multi-agent depth deterministic strategy gradient algorithm based on supply and demand perception; and the intelligent agent carries out collaborative decision making based on the global supply-demand imbalance degree and local observation.

The invention discloses a hybrid office efficiency optimization system based on digital twinning and space calculation, and relates to the technical field of computer science and technology, and the system comprises a data collection module which captures the station layout parameters, the personnel movement track, the equipment use state and the environment parameters of an entity office space in real time through an Internet of Things sensor array, and transmits the parameters to a server; the sensor array comprises a positioning base station, a thermal imager, an intelligent electric meter and an acoustic sensor. The hybrid office efficiency optimization system provided by the invention can accurately and comprehensively map the office environment through the real-time data acquisition and multi-source fusion technology, solves the problem of single data acquisition of the traditional system, and improves the efficiency of the office by utilizing the space calculation and three-dimensional modeling technology. According to the system, a three-dimensional space model comprising an interactive station unit, an equipment entity and a personnel virtual avatar is constructed, a basis is provided for dynamic modeling and intelligent optimization, and a multi-objective optimization algorithm and a genetic algorithm are combined, so that the system can be under complex constraint conditions.