Vegetation in power lines security zones poses a significant threat to grid reliability and can lead to power outages.

Participants are tasked with developing a computer vision algorithm capable of detecting vegetation in power lines security zones using point cloud data. The algorithm must also accurately classify power line support structures (intermediate and anchor) and wires to prevent negative impacts of vegetation on power line operation.

Students of Data Science and related fields

Data Science, Deep Learning, Computer Vision, Image Retrieval, and ML specialists

format

Online

Start of the hackathon

15 November 2024

Teams of 1 to 4 people can participate

Dates

15 November 2024 – 25 November 2024

Price

Free participation

Changing the competition test dataset. Submission Deadline

Hackathon opening ceremony. Welcome webinar. Expert Q&A

Summarizing the results, presentation of the results, hackathon closing ceremony

PhD, Professor, Head of the Energy Center at Innopolis University. 15 years of experience in creating new solutions in energy and power engineering.

Developer of the Product Development Laboratory for Artificial Intelligence in Industry at Innopolis University.

Lead programmer-mathematician of the Product Development Laboratory for Artificial Intelligence in Industry at Innopolis University.

Head of Digital Modeling at the Energy Center of Innopolis University. 17 years of experience in developing innovative solutions for diagnostics and condition monitoring of critical infrastructure elements.

AI-powered automated transmission line inspections in security zones

If you have a question about participation, contact us Liliya, the hackathon organizer