10 results about "Smart spaces" patented technology

The invention provides an intelligent space management method, apparatus and device, and a computer program product, and relates to the technical field of computers and Internet. A data acquisition and processing agent, a task planning agent, a task execution agent, an adaptive learning agent and a central server are deployed in the intelligent space, the task planning agent comprises a first task planning agent, and the data acquisition and processing agent is responsible for data collection of a specified space in the intelligent space; the method comprises the steps that a first task planning agent receives a global model from a central server; receiving local real-time data from one or more data acquisition and processing agents; processing local real-time data based on the global model to generate a task plan; and issuing the task plan to one or more task execution agents, so that the one or more task execution agents execute the task plan.

The application provides an extensible smart community knowledge graph construction method and system, relating to the technical field of artificial intelligence, the method comprising: preprocessing multi-modal sensing data collected by multiple spatial regions in a smart community; constructing a spatial topology graph with spatial regions as nodes and physical adjacency relationships as edges according to multiple spatial regions and their physical adjacency relationships in the smart community; processing the preprocessed multi-modal sensing data to generate fusion features representing dynamic events in the region, and taking the fusion features as the attributes of the corresponding nodes in the spatial topology graph to construct a fusion graph for the knowledge graph, the method uses the spatial topology structure to enhance the correlation of multi-modal data, improve the interpretability and reasoning ability of the data, and thus significantly improve the understanding and response ability of the intelligent space to complex interaction tasks.

Aspects presented herein may enable a user equipment (UE) to maintain an optimized priority list of global navigation satellite system (GNSS) signals / channels to achieve a best GNSS positioning performance with limited resources in real-time. In one aspect, a UE identifies a maximum number of GNSS signals to be used by the UE for GNSS positioning. The UE prioritizes a set of available GNSS signals for the GNSS positioning based on one or more conditions. The UE selects the maximum number of GNSS signals to be used for the GNSS positioning from the prioritized set of GNSS signals. In some implementations, the UE may detect that a number of available GNSS signals exceeds the maximum number of GNSS signals to be used by the UE for the GNSS positioning, where the prioritization of the set of GNSS signals is based on the detection.

The application discloses a kind of wisdom space equipment data transmission bus arrangement method and equipment, it is related to wisdom space wireless communication technical field, including setting target function calculation equipment position, wisdom space is divided into three-dimensional grid, for each grid allocation index, equipment coordinate is mapped to grid index, calculate grid occupancy probability, generate path occupancy flag;Directly calculate the number of sound window samples and reverberation window samples, divide direct sound energy by reverberation sound energy, calculate linear DRR, calculate the mean square vibration energy of equipment, combine path occupancy probability and average vibration energy, calculate vibration coupling energy, based on received signal strength, convert into linear power and linear signal-to-noise ratio.The application improves the accuracy of effective bandwidth estimation by fast fourier transform combined with power delay spectrum calculation, and improves the rationality of link screening by path occupancy probability combined with DRR utilization factor.

Aspects presented herein may enable a user equipment (UE) to maintain an optimized priority list of global navigation satellite system (GNSS) signals / channels to achieve a best GNSS positioning performance with limited resources in real-time. In one aspect, a UE identifies a maximum number of GNSS signals to be used by the UE for GNSS positioning. The UE prioritizes a set of available GNSS signals for the GNSS positioning based on one or more conditions. The UE selects the maximum number of GNSS signals to be used for the GNSS positioning from the prioritized set of GNSS signals. In some implementations, the UE may detect that a number of available GNSS signals exceeds the maximum number of GNSS signals to be used by the UE for the GNSS positioning, where the prioritization of the set of GNSS signals is based on the detection.

The invention discloses a smart space-oriented camera inspection planning method, and relates to the technical field of inspection planning, and the method comprises the steps: obtaining historical inspection data, constructing a spatial association topology containing spatial adjacency, abnormal co-occurrence and activity association relationships, mining regional association weights through a graph neural network, and combining historical abnormal distribution features to obtain a spatial association topology; calculating a camera space value index, and finishing inspection area grading based on a statistical confidence interval; constructing a regional risk assessment model, embedding a regional hierarchical constraint factor, outputting a predicted risk value, dynamically adjusting the routing inspection priority, and triggering an emergency queue jumping mechanism; the risk coverage efficiency, the computing power load balance degree and the inspection response time delay are taken as targets, the inspection polling interval, the staying duration and the cooperation strategy are jointly optimized, and an inspection scheme is generated by adopting dual-mode updating; through edge node local parameter adaptive updating and federated learning aggregation, continuous self-optimization under model privacy protection is realized, and inspection accuracy and adaptability are improved.

A smart space system includes: a cabin, including: a bottom surface; and a first screen, located on a side wall of the cabin and connected to the bottom surface; an interactive human-machine interface, including: a display system, having an imaging device, wherein the imaging device is configured to project multiple multimedia images onto the first screen; and a controller, signal-connected to the interactive human-machine interface to issue a control command to the interactive human-machine interface, so that the multimedia images are connected to form a first continuous image, so that images of the first continuous image appear coherent on the first screen.

This invention relates to the field of smart space operation and maintenance technology, and discloses a smart space operation and maintenance optimization method and device based on data elements. The method includes: collecting operational data from IoT terminals, edge nodes, and a cloud platform within the smart space, and fusing the operational data to obtain fused data; identifying and encrypting sensitive information in the fused data to obtain encrypted data; inputting the encrypted data into the local models of each edge node to extract device operational features, and integrating the device operational feature set in a cloud aggregation server; identifying anomalies based on the device operational feature set to obtain device abnormal status information; and conducting anomaly cause tracing analysis based on the device abnormal status information to obtain a smart space abnormal situation report. This invention provides operation and maintenance personnel with an interpretable anomaly analysis path and a comprehensive situational awareness report, significantly improving fault handling efficiency and realizing intelligent operation and maintenance management of smart spaces.

The application relates to the technical field of intelligent space layout generation, and discloses an indoor layout generation method and system based on double-track constraints, wherein the method comprises the following steps: acquiring indoor space structure data; constructing a current layout state and a candidate action set; scoring the candidate action based on a conditional scoring model; generating a score sequence after hard constraint modulation; calculating soft constraint energy; generating a candidate action probability distribution; and performing a step-by-step indoor layout generation task. Compared with the prior art which mainly relies on a single scoring model for layout generation, especially in a complex indoor scene with clear space non-placing areas and traffic constraints, it is difficult to guarantee layout legality and generation diversity at the same time. Due to the double-track constraint mechanism of hard constraint Boolean gate modulation and soft constraint energy hierarchical accumulation, the application realizes the probabilistic modeling of the prior legality screening and subsequent rationality differentiation of the candidate layout action, and improves the overall indoor layout generation quality.

The application discloses a kind of star-ground collaborative intelligent remote sensing computing method and system based on generalized dynamic guidance, it is related to spatial information technology, artificial intelligence and edge computing cross technical field.The method is through ground guidance center to contain intelligent space mask, task self-adapting prompt vector and collaborative reasoning instruction generalized dynamic guidance information;Satellite-borne processing unit is combined with real-time resource state according to guidance information, and using local focusing calculation and conditional early retirement mechanism realizes self-adapting focusing processing;While constructing the closed loop optimization system of heaven and earth, continuously optimizes guiding strategy by result feedback.The application realizes the mode change from full image processing to focusing calculation, significantly improves the on-board processing efficiency, reduces the amount of calculation by 70-90% while ensuring accuracy, reduces star-ground communication data volume by more than 95%, effectively solves the problem of limited on-board resources and data transmission bandwidth bottleneck, and has important value in remote sensing application scenarios such as disaster emergency and environmental monitoring.