AI – A need of the hour for Energy Conservation
Why is energy conservation the need of the hour? Can AI be the answer to it?
Depletion of energy resources has been a cause for concern for many countries. Coal, crude oil and natural gas. According to EIA 60% of electricity is wasted during the distribution process. AI solutions have been improving to stimulate human thinking. Social cause influencers and researchers have come up with Depletion accounting to measure the rapid draining of these resources. Interestingly, the reason behind depleting energy resources is not just the growing population but also the overuse of these resources.
Resource depletion is also causing panic across the world making energy resources like metal, crude oil expensive. While diminishing levels of these resources are making it expensive to acquire, Co2 emission caused during the procuration of metals, crude oil is another crisis to ponder on. Promoting judicious use of these resources is one way to conserve energy, since switching from natural resources to renewable is a daunting task. While revamping the energy system will take a while, AI can be applied to track the overconsumption of energy and optimizing energy distribution.
While we march on for energy conservation it is also important to track the patterns of energy consumption with Big data, IoT and artificial intelligence. Natural gas used in metallurgical processes in foundries causes high wastage and Co2 emissions. Electric furnace costs $850 to $1,500 and the installation can cost up to $1,200 to $5,975. These costs vary from furnace size, brand, labor and transportation costs. In addition to this electric While switching to an electric furnace can be an expensive affair, one can leverage emerging tech to track the use of gas with industrial artificial intelligence solutions.
By opting for an AI solution to fix the energy overutilization loose end, entrepreneurs can save their capital and natural gas to establish a sustainable business model. AI along with IoT can be applied to track use of gas
With Machine learning and neural networks (an essential branch of AI) gas utilization can be tracked using data science to sort structured and unstructured data as a means of predictive analysis of the consumption, distribution and manufacturing patterns. The predictive analysis made by AI is then converted to recommendations (prescriptive analysis) to optimise the use of resources in an effective manner.
While there are many technologies like big data, IoT sensors, being implemented to solve energy-related crises, AI moves a notch higher by offering resource forecasting, data centralization to analyse the factors causing resource drain. This will help in sketching a strategic roadmap to tackle the gas consumption to meet the demand and supply equilibrium.