4results about How to "Reduced response time" patented technology

The application discloses a kind of heat supply system risk prevention and control and emergency decision-making method considering N-1 working condition scene, comprising: first, preset source side, net side, station side N-1 working condition scene, based on end heat user label aggregation generates heat supply area label and assesses the degree of influence.Second, analyze system operating parameters under different scenarios, build N-1 working condition scene analysis library and risk assessment system.Third, based on analysis library and load demand, safety constraints, deduce full-quantity feasible emergency dispatching scheme and construct emergency plan library;At the same time, combined with structural defects and supply and demand trend, design long-period network frame structure time sequence planning scheme and optimize using risk assessment system.Then, based on emergency plan library, historical data and base large model, according to the chain of thought of online alarm, scheme matching, emergency command trains full-quantity emergency dispatching large model.Finally, when N-1 condition occurs, call the large model to automatically execute emergency dispatching.

This invention discloses a smart community management method and system based on a 3D scene. The invention relates to the field of smart community management and includes the following steps: S1: Dynamic twin construction of the 3D scene, creating a dynamic 3D scene synchronized with the physical community in seconds, rather than a static model, ensuring accurate implementation of management actions; S2: Triggered perception and linkage of the 3D scene; S3: Dynamic resource scheduling optimization of the 3D scene, dynamically adjusting the community management resource configuration based on the real-time status of the 3D scene; S4: Iterative optimization of the 3D scene management effect. This invention's smart community management method and system based on a 3D scene, through dynamic twin modeling and scene-linked perception and early warning, constructs a synchronization system between the physical community and the 3D scene, replacing the manual inspection trigger mode. Abnormal situations can be automatically located, instructions generated, and synchronously fed back, thus significantly shortening the early warning and response time and improving technical linkage.

The invention belongs to the technical field of signal devices, and particularly discloses a smart park multi-source sensing security early warning system, which comprises a multi-source heterogeneous data sensing device used for collecting physical environment multi-dimensional original sensing data and performing synchronization processing; the digital twin virtual simulation device is used for constructing a virtual mapping model and restoring a situation for strategy deduction; the dynamic game decision analysis device is used for generating an optimal guide strategy and a blocking plan based on a non-cooperative game model; the Internet of Things facility linkage execution device is used for executing intervention action and path induction of a physical space through the scheduling park facility; and the mobile situation monitoring terminal is used for providing a visual interaction interface and issuing a tactical guidance instruction. Through deep fusion of the game algorithm and the digital twinning technology, upgrading from passive defense to active induction is realized, the response time is shortened, non-contact management and control are realized, and the law enforcement risk is reduced.

This invention relates to the field of Markov model technology, specifically to a dietary plan iterative generation system based on Markov models. The system receives time-series physiological data collected by the user's vital signs sensors as an observation sequence, maps a pre-defined food ingredient library and a nutrient standard library into a fixed-length feature hash space, constructs a dimensionality-reduced Hidden Markov state transition matrix in the feature hash space, compresses high-dimensional food ingredient combination states into low-dimensional hash index states, executes the Viterbi decoding algorithm in the low-dimensional hash index states to obtain the optimal hidden state sequence, and restores the low-dimensional hash index sequence in the optimal hidden state sequence to the food ingredient combination sequence according to the reverse mapping table corresponding to the hash collision handling strategy, and outputs the dietary plan. This reduces the storage space occupied by the Hidden Markov state transition matrix, eliminates the risk of memory overflow caused by high-dimensional state space traversal, and shortens the response time from the input of the observation sequence to the completion of the decoding of the optimal hidden state sequence.