Technology for determining the condition of overhead power lines which, by using automation, aeronautics, IT and other technologies, autonomously carries out overhead power line diagnostics and detects failures and defects within the set deadline and without human involvement, as well as form an inspection report based on the latter. Currently, the electricity lines monitoring is cost and time consuming, inaccurate and often impossible to perform due to ongoing natural disasters. Lack of reliable data about past incidents and current state of crop leads to incorrect decisions. Developed technology is based on a fusion of images, Big Data and Machine learning for automatic risk detection. It uses scouting with drone, uploading the images, analysis of images, satellite risks maps, smartphone or photocamera. It saves time and money, increase objectivity and precision of risks detection and enables collection of historical data fr prediction analysis.