SBIR Phase II: A software-based tool for beyond visual line of sight (BVLOS) drone's connection reliability enhancement

Award ID: 2304143

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will improve Autonomous Unmanned Aerial Systems (UAS) services used in package delivery, aerial surveillance, and infrastructure inspections. The goal of the effort is to provide UAS services beyond the visual line of sight (BVLOS) and enable reliable communication links to remote ground control stations. Existing solutions for control of BVLOS drones are based on either satellite connections with expensive subscription fees or cellular-based products with limited network availability, frequent interruptions, and high interference. The teams integrated software solution will enhance the connection reliability for BVLOS drones using the voice channel redundancy of the existing mobile network (2G/3G/4G/5G), identify and mitigate the circumstances of the link failure, and provide an accurate visualization of the network coverage for optimal route selection. The teams ubiquitous, ultrareliable, and low-latency communication technology allows cellular-connected UAS service providers to reliably control their long-range UAS, and benefit from fewer mission abortions and reduced costs compared to satellite links. The flexibility of the software solution can serve every drone use case and can get more drone companies through the regulatory approval process faster, reducing the time to enter the market. This Small Business Innovation Research (SBIR) Phase II project seeks to develop a software-based solution that provides scalable, redundant, and guaranteed cellular network connection for BVLOS drones. The proprietary software solution is based on three enabling features voice channel redundancy, a connection selection algorithm and a network mapping tool. In this project, the research and development efforts will be dedicated to 1) the development of the scalable software-only version of the data-over-voice technology operating with commercial off-the-shelf communication hardware, 2) implementation of software solutions to make drone connectivity reliable end-to-end and dynamically adapt to the requirements of drone use cases; 3) development of the aerial network coverage visualization tool to provide the drone industry with valuable insights into connectivity in airspace, 4) firmware implementation of solutions for overcoming the connectivity failures and further enhancing the network reliability, and 5) development of an application programming interface (API) which manages connectivity dashboard. The successful completion of these activities will deliver the fully functional software-only solution for BVLOS drones with its safety and performance validated with ground/air measurements, thus confirming the commercial potential. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Vincent Lee