Analysing and Optimizing the Refrigeration System Using Machine Learning Algorithm

The Cold chain/Refrigeration plays an important role for preserving vaccines as per the vaccine storage and guidelines prescribed by World Health Organizations it is better than most of other preservation methods. primary goal adopting phase change material to increase performance, cooling duration, capacity storage, sustain steady effect a longer length time during power outages. In experimental set up decoded use Inorganic Eutectic materials which encapsulated in plastic containers inside storage. project will involve collecting data from sensors installed cabinet using machine learning algorithms analyse generate insights. results can be used inform best practices contribute development more efficient effective management systems. This explores techniques optimize cabinet. Proper critical maintain efficacy, therefore ensure that temperature humidity are kept within specific ranges. Machine models trained predict levels cold rooms detect anomalies may indicate potential problem. help improve monitoring maintenance reduce risk spoilage. Learning like Regression Classification on web-app because they provide us with continuous well discrete value output. Libraries pandas, Numpy, sklearn, matplotlib along visualization possible forecast actual aspects humidity. User Interface has also been developed acquires input any user displays according user’s inputs.