Isa Group (Transelca) and Adintelo worked together to bring safety to the Colombian energy industry through early wildfire detectors for high-voltage power lines located in remote locations.
After winning a competition run by Ruta N, Adintelo developed an AI-powered information system that allowed Isa Group (Transelca) to monitor high-voltage power lines in remote areas of Colombia.
ISA business group, is a mixed public utility company, which provides high voltage electrical energy transportation services and offers market connection services to the National Interconnected System, Administration, Operation and Maintenance -AOM- of electrical assets and others associated with its core business.
Transelca and Adintelo, strategic allies:
Transelca needed a company not only to solve a problem with wildfires but also to develop it and implement it. Therefore, through the contest elaborated by Ruta N, they chose Adintelo as the developer of this crucial program for the Colombian energy industry.
The joint work between Adintelo and Transelca allowed the installation of early warning stations, facilitating the prevention and early response to wildfires, overgrown vegetation, and potential intruders.
As a result, the company was able to reduce the costs of infrastructure damage, protecting the country’s power supply and improving the country’s electric infrastructure.
The challenge:
The remote regions of Colombia represent a real challenge for engineering. As a result, protecting the country’s electrical infrastructure is one of the most critical aspects of the energy industry. This is due to the cost of the projects and the difficulty of access.
In order to monitor and transmit early warnings, Isa Group (Transelca) needed a self-sufficient, sustainable, and automated system.
The solution:
Adintelo find a way to constant surveillance of the power lines day and night, in an efficient and self-sustainable way, through high-level engineering, to reach this solution we implemented:
- Machine Learning: Using artificial intelligence, the cameras installed on the electric towers recognize the shapes and patterns of the smoke, overgrown vegetation, and trespassers, and send a notification informing Transelca if an issue is found.
- The early warning system, Included an IP67 cabinet integrated with two PTZ cameras of 30 x zoom and a weather station, all powered by solar panels.
- Hardware-Software: Adintelo team brought expert programmers in Python, Modbus, Django rest framework, Tensorflow, and AWS cloud to develop algorithms that automated the detection.