StreamOwl is an SME founded in 2014 in Athens, Greece, with an extensive background and expertise in computer vision-based inspection tasks and video analytics with Artificial Intelligence. StreamOwl has developed a drone platform which integrates peripheral sensors (lidar, camera, ultra-sound sensor) with an
on-board computer, which enables the autonomous flight of the drone based on environment sensing.
This platform has been employed in the development of solutions for railway vegetation management, infrastructure inspection, and defect detection in thermal insulation of building facades for energy efficiency evaluation. StreamOwl has also developed solutions for weld quality assurance based on AI-based analysis of radiographs and anomaly detection in smart energy systems. StreamOwl has experience in coordination and participation in European and National R&D projects.
Current running projects relevant to this proposal is the BonsApps project (bonsapps.eu) where StreamOwl works on deployment of AI solutions at the Deep Edge. StreamOwl has received a distinction award as a Finalist in the MIT Enterprise Forum 2016 and received the 5th place in the Business Seeds Competition of the National Bank of Greece.With operations in 8 countries, exports to over 80 markets, and more than 100 subsidiaries, the Group is a key enabler of Greece’s energy transition.
Role in Piqaso
In PiQaSo, StreamOwl will support the transportation use case, providing monitoring drone fleets and platforms towards the realization of the corresponding scenario.
Specifically, the use case will exploit a novel aerial robotic system using drones to inspect railway tracks and sidings for possible defects by performing long-range Beyond Visual Line Of Sight flights.
Once an anomaly has been detected, the drone triggers an incident on-the-fly by utilizing a wireless data link to report the anomaly at the database of the inspection system on the cloud. Then, the railroad personnel is directly notified about the detected anomaly (i.e. location, anomaly photo etc.) through a web-service in the cloud. Thus, the integration of PQC is essential to secure the communication and data integrity between drones and central monitoring system, including its data base.