(Drone Connectivity Platform)
AirborneRF is TEOCO’s connectivity data platform for beyond visual line-of-sight (BVLOS) drone operations in cellular networks.
The use of drones for commercial services in industries including agriculture, transport, insurance, telecommunications and others is expected to increase exponentially and will provide great opportunities for network operators. Between now and 2020, Goldman Sachs Research forecasts drones will be a $100 billion market opportunity.
Maintaining a line-of-sight view of a drone is often a serious limitation to what could be achieved. BVLOS drones will further improve the economics and feasibility of many use cases driving uptake. One of the major challenges with BVLOS drones however is the reliable command and control connectivity that is required for operation. In many situations, cellular is the most appropriate choice for this connectivity.
The question of ‘Where is it safe to fly BVLOS drones?’ needs answering. Or more specifically, where is there sufficient cellular connectivity and clear airspace to fly BVLOS drones? Operators can answer the cellular connectivity part of that question and drone services companies are willing to pay for that information!
AirborneRF computes the 3D radio space for safe drone operation. It delivers that information to Air Traffic Management (ATM) and UAV Traffic Management (UTM) systems in real time. By connecting cellular network with Aviation systems, AirborneRF enables safe BVLOS services.
AirborneRF is used to calculate where a drone can safely fly. It takes into account both national airspace control and the radio coverage delivered by the cellular network to define a three dimensional safety corridor which complies with air safety regulations and ensures the UAV can be reliably controlled.
AirborneRF uses the latest high-performance computational technologies to get close to real-time processing for large scale 3D radio spaces. Scalability is important as the computational problem becomes massive as you combine large areas with a significant height dimension at high resolution. AirborneRF can calculate the radio-space for a land surface area of more than 40,000 km2 to a height of 300m with a resolution of 15m in a few seconds. AirborneRF is sufficiently scalable to allow for route recalculation during flight.
Measurement-based machine learning
A drone needs sufficient radio coverage to safely complete its mission. To make sure it stays in a safe radio-space AirborneRF uses measurements from the drone and machine learning to adapt its picture of the conditions to the real-world during flight. This revised picture can then be used to recalculate a route for the drone, if necessary, so that the mission can be completed. Additionally AirborneRF uses the measurements collected by the drone to update and improve its predictive models for future flights.
To learn more about AirborneRF please contact us.