Approaches Using Machine Learning Models and Adaptive Technology to Conserve Power

Moore's law predicts that the speed and capability of computers can be expected to double every two years. In his theory, Gordon E. Moore attributed this to an increase in the number of transistors a microchip can contain. Regardless, it is common knowledge that with the passing of time, technology, and its use, will increase as it incorporates more into the average human life. With the gradual increase in technological innovations for everyday use, power consumption and efficiency in cloud servers, large data centers, and complex systems will become more necessary for human survival and the maintenance of future societies. The need to optimize power consumption exists even today, and demand will only grow. This study highlights how various machine learning models and algorithms can be used to maximize power within centers of significant power consumption, and how modern technology can adapt to conserve a limited power supply.