Currently, more than 5,000 satellites orbit the earth, a large part of which are intended for earth observation (EO).
Power companies allocate a large part of their budget each year to reviewing, managing, and maintaining their power lines. Among these recurrent tasks, the pruning of the vegetation surrounding its power lines stands out in order to avoid invasions that could cause serious incidents such as fires and power cuts.
Power line automation process
Today, the work of reviewing the lines is very little automated and to carry them out requires very high costs due to the need to carry out numerous field visits in situ, as well as to carry out flights with drones where the logistics for data collection is quite complex.
As we mentioned earlier, a large part of current and future satellites focus on earth observation for different purposes, such as monitoring the different processes that occur on the continents, the oceans, and the atmosphere. A clear example is the European Copernicus program of the European Space Agency (ESA), whose mission is to generate an autonomous, high-quality, continuous Earth observation capacity whose results are freely accessible by the scientific community or any other interested person.
The different application sectors of the program are shown below:
Earth observation satellites are orbiting the entire planet acquiring different types of images every day of the year.
There are different providers and platforms from which this type of image can be downloaded either for free or through a payment depending on the type of satellite and the resolution of the images captured by it. Today it is also possible to program these satellites to acquire images at a specific place and date.
Advantages of tracking and monitoring power lines
Both due to the recurrence of images and their resolution, the use of this type of resource to track and monitor the supply lines of electricity companies is currently a reality.
Among the advantages are the following:
- Obtaining high-resolution images on a regular basis.
- Sweeping of large extensions of land from one day to the next.
- They do not require much post-processing, being available for analysis from the moment of acquisition.
- It is not necessary to carry out field visits as in the case of drones, offering possibilities of use worldwide.
- There is a large volume of free images and in turn, the current increase in providers is causing a reduction in the cost of images and the trend will continue in the coming years.
Artificial Intelligence and Deep Learning
The Imageryst platform applies artificial intelligence and deep learning algorithms to maximize the profitability of solar installations, and can also calculate the payback period to make decisions based on data.
In addition, these algorithms also allow different types of analysis to be carried out:
- Detection of the different types of vegetation as well as their degree of maturity.
- Analysis of the state of health and/or diseases of the vegetation based on different indices calculated from the different spectral bands of the images.
- Detection of the changes that have occurred in images of different dates, visually and agilely identifying the areas in which vegetation growth has occurred in the areas that, on the contrary, have been pruned.
- Detection and prediction of lateral and vertical invasions of vegetation in the easement area, creating alerts before said invasions can affect the lines.
- Calculation of the free height between the vegetation and the lines, allowing discrimination between areas where there is no danger from others where the vegetation can invade the lines.