Reconnaissance across industries has begun to rely heavily on drone technology, but the development and innovation of tracking software looks to revolutionize industries from fire safety to powerline inspection. We’ve put together an overview of how our system gets its data. Take a look to learn more about how our unique, specialized tracking drone software equips users with state-of-the-art technology that’s changing the game as we know it.
Efficiency is the name of the game in most industries, and applying AI to drone software makes inspection and reconnaissance easier, safer, and more efficient- but how can we make something more efficient while simultaneously focusing on protecting our environment and staying true to our values? This last question is at the core of everything we do at Robotto. When developing or identifying new use cases, we often take a step back and ask ourselves, is this a responsible application of AI, and does it work towards making industries more sustainable?
It’s questions like this that altered our bachelor’s project’s path, moving our focus from drone software that would deliver our pizza to state-of-the-art software aimed at tracking and equipping firefighters with the information they need precisely when they need it. Pushing back on our inner craving for juicy pizza, we worked to develop software with autonomous features, data analysis, and visualization and a method of providing this data in real-time without delays.
To your average joe, equipping a drone with these features seems like a two-step process, but the development team at Robotto would beg to differ. Our team identified three different algorithms needed to ensure efficiency during the development of this software for wildfire tracking. Using a custom-built database for recognition and processing of fire data, AWRA, the Autonomous Wildfire Recognition and Analytics platform, ensures intelligent processing and visualization of data, providing it to end-users on a topical map in real-time.
Batman, is that you?
From his perch in the sky, Batman views the city, on the look-out for people in need. While he sits there considering his dominion, he notes the buildings' size, the distance between structures and predicts several possible outcomes for the situation developing below. Much like the Batman of our childhood dreams, AWRA views a developing situation from high in the sky, collects relevant data, processes this data, and provides users with proactive data that's ready for use.
Unlike the real Batman, our software relies on GPS location, a monocular camera, and several data collection and analysis systems for fast and accurate calculation of the location, size, and direction of a wildfire. While flying over wildfires, one of AWRA's core algorithms identifies the edge of the fire as well as differences in fire intensity. With this information, the software then calculates the fire's size, giving firefighters the exact size and spread of the fight ahead of them.
Autonomous is the future
While autonomous drones are still operational in many parts of the world due to strict drone regulations, we believe that future drone operations will utilize and rely on autonomous functions, including autonomous flight. From a safe distance, operators select an area on a digital map using two coordinates and two lengths to determine the rectangle's edges wherein the area navigation is to be performed. An area sweep is performed inside the designated rectangle, following a snake pattern, tracking the fire in real-time.
Utilizing autonomous features not only frees up time for the operator but removes aspects of danger from an otherwise risky job such as firefighting. Increasing efficiency and removing said danger allow operators and firefighters to spring into action with increased situational awareness, resulting in faster control of wildfires, helping protect communities and nature.
Just a few more details
We know the process the software takes to provide data in real-time, but we also know that Batman, well he can do a lot of impressive things- the same is true for AWRA. Unlike traditional fire surveillance and detection methods, drones equipped with AWRA software can view areas otherwise unreachable due to no-fly zones, heavy smoke, or night-time flight regulations. In addition to this already impressive improvement from the current situation of fire surveillance and detection, drones operating with AWRA do not rely on an internet connection, giving users the ability to collect and take action on data in remote areas with an accuracy of +/- 0.5 meters.
Testing with the best
Spain has a history of ravaging, determinantal wildfires, which pushed its government to establish a unique, elite squad of firefighters known as the GRAF Bombers. Their know-how and ability to track and analyze fires is renowned throughout the firefighting world. As programmers and AI nerds, we know how to make our technology work, but our knowledge of how fires behave was limited. This limitation encouraged us to reach out to firefighting organizations, including GRAF, letting us test our technology with the best in the field of wildfire fighting.
This is why, amid COVID-19, our team traveled to Barcelona, where we were able to test our software, displaying how drone software such as AWRA increases the situational awareness of firefighters. Used to operating drones manually, the GRAF team was limited in their efforts to extinguish the test-fire as it did not provide them a broader perspective of the direction and size of the fire. Applying AWRA, the team delivered more precise and actionable information about how the fire would spread and evolve, allowing them to spring into action quickly and tackle the fire more effectively.
The development team at Robotto has a lot up their sleeves as they work to innovate and shape the autonomous future. To follow their development, make sure to find us and subscribe on Linked In and Twitter!