Machine Learning and AI for Optimizing and Safeguarding Energy Transmission in Storms by Automatic Inspection of Electrical Wires

Storms may blow down trees and cause power line damages that lead to power outage to communities. Such damages not only bring inconvenience, but may also endanger human lives because the falling live wires pose the potential danger of electrocuting people. To save costs and protect human lives, this paper proposes various innovative and advanced AI, deep learning, statistical learning methods for optimizing and safeguarding energy transmission in storms by means of automatic inspection of electrical wires in order to mitigate potential damages before they occur. The proposed solution is preventive in essence, and this paper first reviews the representative major methods that are used to address the root cause of the major damages from the storms. Then the main problems like tree branches hanging over power lines, unstable trees near electrical wires, and aging and deteriorating infrastructure are identified and further investigated. Finally, various innovative and advanced AI, deep learning, and statistical learning methods are proposed to optimize and safeguard energy transmission in storms by means of automatic inspection of electrical wires.