This invention discloses an energy-saving method and
system based on data sensing, belonging to the field of energy-saving optimization technology. The method includes: using a
sensor array to collect raw multi-source sensor data, performing data preprocessing and
feature extraction to generate room occupancy status and a
state vector; based on the room occupancy status, inputting the
state vector into a macroscopic decision-making agent constructed based on a
reinforcement learning algorithm to generate an optimal dynamic
weight coefficient vector; based on the optimal dynamic
weight coefficient vector, using an improved Hippo optimization
algorithm to solve a multi-objective optimization function to generate an optimal equipment control parameter vector; executing the optimal equipment control parameter vector, returning to the sensor
data acquisition step, calculating the immediate
reward value after the decision, and updating the macroscopic decision-making agent using the corresponding state transition data. This invention solves the problems of poor flexibility, low optimization accuracy, and difficulty in balancing multiple objectives in existing energy-saving control strategies.