AI-Driven Solutions for Energy Optimization and Environmental Conservation in Digital Business Environments

Authors

  • Aleena Varghese Software Developer, IT WorkForce (Schneider Electric), 127 E Michigan St #100, Indianapolis, IN 46204, USA

DOI:

https://doi.org/10.18034/apjee.v9i1.736

Keywords:

Energy Optimization, Environmental Conservation, Digital Business Environments, Sustainability, Smart Technologies, Renewable Energy, Eco-Friendly Operations

Abstract

The potential of AI-driven solutions for environmental preservation and energy optimization in digital business settings is examined in this paper. The main goals were to investigate how AI technologies may support sustainability, identify major obstacles and opportunities, and evaluate the policy implications for implementation. The approach thoroughly examined the literature, including research articles and case studies, to assess AI's uses in energy optimization and environmental preservation. The main conclusions show how AI technologies can revolutionize energy optimization by enabling intelligent control systems, integrating renewable energy sources, and enabling precision energy optimization. To guarantee successful implementation, constraints, including data quality problems, technological complexity, and ethical issues, need to be resolved. To encourage the ethical and responsible usage of AI-driven solutions for sustainability in digital business environments, regulators and enterprises must work together and establish clear legislative frameworks and incentives for technology adoption. This work generally advances knowledge of the potential and difficulties of utilizing AI technology for energy optimization and environmental preservation in the digital age.

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Published

2022-06-30

Issue

Vol. 9 No. 1 (2022): January - June Issue

Section

Articles

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Copyright (c) 2022 Aleena Varghese

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How to Cite

Varghese, A. (2022). AI-Driven Solutions for Energy Optimization and Environmental Conservation in Digital Business Environments. Asia Pacific Journal of Energy and Environment, 9(1), 49-60. https://doi.org/10.18034/apjee.v9i1.736

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