The speed of the transition of drone technology from war zones to retail stores has been phenomenal, especially given the negative associations and misconceptions surrounding them.
Listed below are the key technology trends impacting the drone industry, as identified by GlobalData.
Drone manufacturers are working on scaling drone technology to deliver greater carrying capacity and endurance, and deliver low cost, small footprint drones for surveillance. The miniaturisation of sensors helps to cut down the overall size and weight of drones and reduce their power requirements.
Some prospective drone application areas including search and rescue, offshore natural resource explorations, and utilities inspection, among others demand bigger drones to support larger payloads. This factor is also driving the miniaturisation of electronic components.
Microprocessors serve as the control centres for drones, providing a platform for control and communications software that integrates with collision avoidance sensors, high definition cameras, and other sensors. Advances in chip design, driven in large measure by the mobile phone industry, are leading to smaller chips with higher performance and lower cost, which in turn helps to drive down the manufacturing cost of drones.
ARM-based processors from companies such as NXP Semiconductors and STMicroelectronics are among the most powerful in the market, with a major emphasis on low power/low cost.
The ability of 3D modelling technologies to consume drone data in the form of imagery and radar/ light detection and ranging (LIDAR) data and convert it into complete topological models makes it possible to survey and monitor the landscape and the objects within it. As a result, drones are increasingly being integrated with improved sensors, high definition cameras and computer algorithms to condense images into 3D virtual images and enable easy assessment of anomalies.
Artificial intelligence (AI)
The growing volume of data gathered by drones will create demand for increasingly sophisticated analysis of that data. AI enables ‘continued learning’ for drones through techniques like machine learning, in order to enable complex capabilities such as autonomous flying and obstacle recognition and avoidance. While the industrial sector is a significant market for drones with AI capabilities, service sector companies are also vying for AI-enabled drones to develop new business models.
Manned Unmanned Teaming
Manned Unmanned Teaming (MUM-T) capabilities are most commonly deployed on rotary platforms such as the AH-64E, which receives a range of data from unmanned platform, expanding the capabilities of the team as a whole. However, going forward these capabilities will be deployed on a number of conceptual sixth generation fighter programmes.
Drone swarm technology
The need to manage and control multiple drones in close proximity will become more acute as the number of active drones grows. Cisco is promoting the concept of connected drones that can be controlled via a cloud-based infrastructure. Currently most of the data generated by drones is transferred to cloud systems for users to access and analyse, often not in real-time. Microsoft’s Azure, Amazon Web Services (AWS), and IBM Cloud are key cloud platforms currently being used by drone companies.
Augmented reality (AR)
As the capabilities of AR technologies improve, drone makers are increasingly incorporating AR functionality into their products. The European Space Agency (ESA) has backed a French start-up, Sysveo, to integrate user made AR into a drone’s video streams.
Drone manufacturers are directly reaching out to homeland security agencies, gamers, firefighters, surveyors and construction engineers. Intel is the most notable company providing AR technologies for drones.
The widespread application of drone technology requires effective anti-collision systems to ensure that they can be operated safely in public places. As a result, different sensor payloads are being developed to satisfy regulators and insurers that drones can be operated safely and autonomously.
Most of today’s drones are powered by lithium polymer (LiPo) batteries, which are known to deliver sufficient energy required to perform standard drone flights. Growing demand for longer flight times and greater carrying capacity is driving drone manufacturers to explore alternative technologies such as hydrogen cells, gasoline powered solutions, solar batteries, gas-electric hybrid solutions, and laser solutions.
Edge and fog computing
Fog computing is a computing model which permits collected data to be analysed within the drone itself (the edge), prior to interacting with the central point of control.
As the volume of data that is gathered and analysed by drone increases, the ability to perform this analysis at the point of collection will grow in importance. A range of industry participants are working on technology that allows a greater proportion of the data analysis and processing to take place on board the drone itself.
The use of fog computing will enable drone operators to reduce latency and limit the amount of data that needs to be transmitted from the drone to the controlling application.
Drones as a service (DaaS)
Over the next two years a number of specialist service companies will emerge, offering a turnkey solution for drone-based surveying, monitoring, and delivery. As a result, organisations will rent drone services on an as-needed basis.
Unmanned aircraft system traffic management (UTM)
As the adoption and application of drone technology becomes more widespread, the need for autonomous UTM system, which can ensure safety, security and control of drones in low-altitude airspaces, will grow significantly. The need for UTM is also identified as a key enabler for future autonomous passenger drones, vertical take-off and landing (VTOL) air systems and BVLOS operations.
Some of the notable initiatives underway currently for development of UTM are being led by NASA, the European Aviation Safety Agency (EASA) and the Civil Aviation Administration of China (CAAC).
Drone delivery is the most anticipated, and hyped, commercial application of drone technology. Encouraged by Amazon’s vision of drone powered package deliveries, the global drone community has shown great interest in this new model of distribution.
Some companies are also looking at hyper-local/hyper-personal drone delivery by applying AI, 3D, and AR. For instance, IBM’s drones can recognise a person’s need for coffee using inputs from his/her wearable gadget and deliver it from a nearby coffee counter.
This is an edited extract from the Drones in Aerospace and Defense – Thematic Research report produced by GlobalData Thematic Research.