An intelligent cooling
system for
dynamic monitoring, prediction and optimization of storage conditions in real time, consisting of: a refrigerator with heat-insulated walls; a
sensor array in the refrigerator comprising temperature sensors,
humidity sensors, pressure sensors, and
pathogen detection biosensors, the
sensor array being configured to continuously monitor internal environmental parameters in the refrigerator and external environmental conditions; a control
dashboard configured to display real-time
environmental data and enable remote monitoring and manual adjustment of the environment in the refrigerator; an
Internet of Things (IoT) communication module configured to transmit the monitored internal and external
environmental data to the control
dashboard; a proportional-integral-derivative (PID) controller operatively connected to the IoT communication module and configured to analyze the monitored data and calculate correction factors to maintain optimal environmental conditions; a plurality of actuators within the refrigerator, the plurality of actuators comprising a temperature
actuator, a
humidity actuator, and a pressure
actuator, the actuators being configured to independently adjust temperature,
humidity, and pressure within the refrigerator based on the control instructions; a processor configured to execute
machine learning algorithms to analyze historical and real-time sensor data, predict optimal environmental conditions based on the analyzed data, and generate control instructions for the actuators based on the predicted optimal environmental conditions and the calculated correction factors; and a
solar power supply configured to provide energy for operating the
system.