Drones in Construction: Technology Trends
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Drones in Construction: Technology Trends

By GlobalData Thematic Research 09 Jun 2021 (Last Updated June 9th, 2021 14:42)

The construction industry is now reported to be one of the largest drivers of growth in the commercial drone sector.

Drones in Construction: Technology Trends
Credits: Andy Dean Photography/Shutterstock.com.

There are a number of potential uses for drones within construction, such as the ability to survey projects through the use of drones in comparison to more traditional means of surveying.

Technology Trends

Listed below are the key technology trends impacting the drones industry theme, as identified by GlobalData.


To improve flight performance and expand the capabilities of their drones, drone manufacturers are working on scaling drone technology up on one hand, to deliver greater carrying capacity and endurance, and down on the other to 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.

Processor chips

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.

3D Technology

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. Whether the application is the surveying of structures like bridges, buildings or the monitoring of farmland or forestry, drones are increasingly being integrated with improved sensors, high definition cameras and computer algorithms that can condense the 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. To effectively process incoming sensor data and draw meaningful conclusions drone solutions need to make use of the latest data analytics technologies. Additionally, AI enables ‘continued learning’ for drones through techniques like machine learning, in order to enable complex capabilities like autonomous flying and obstacle recognition and avoidance.

Manned Unmanned Teaming (MUM-T)

MUM-T is described by the US Army Aviation Centre (USAACE) as: ‘The synchronised employment of soldier, manned and unmanned air and ground vehicles, robotics, and sensors to achieve enhanced situational understanding, greater lethality, and improved survivability.’ Currently, 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.

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. The company argues that the ability to manage multiple drones simultaneously will enable faster data collection over vast areas, coupled with simultaneous data processing to deliver timely and accurate data. Currently most of the data generated by drones is transferred to cloud systems for users to access and analyse, often not in real-time.

Augmented reality (AR)

As the capabilities of AR technologies improve, drone makers are increasingly incorporating AR functionality into their products to enhance the user experience and make the application of drone technology more effective. The European Space Agency (ESA) has backed a French start-up, Sysveo, to integrate user made AR into a drone’s video streams. This integration is intended to enable the real-time analysis of gathered data to improve operational efficiency and also provide enhanced anti-collision measures.

Anti-collision technology

While the relatively small scale of today’s commercial drone deployments means that there is currently little risk of collision between drones, the widespread application of drone technology will require effective anti-collision systems to ensure that they can be operated safely in public places. Different sensor payloads are being developed to establish improved management and control of drones, in order to satisfy regulators and insurers that drones can be operated safely and autonomously.

Battery technology

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. However, the ability to transport increasingly heavy payloads and to conduct more demanding operations in varied environments, is constrained by the fact that current drones are limited in terms of their endurance. 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. The cost, complexity, and latency involved in transmitting large volumes of sensor data from drones to a central point for analysis means that there can be a significant delay between an event being sensed and action taken as a result of it. 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. So rather than having to develop drone capabilities in-house, organisations will be able to 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. In addition, the need for UTM is identified as a key enabler for future autonomous passenger drones, vertical take-off and landing (VTOL) air systems and BVLOS operations.

Drone delivery

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. With numerous initiatives currently in pilot testing worldwide, proponents promise that it will cause significant disruption to existing industrial distribution channels.

This is an edited extract from the Drones in Construction – Thematic Research report produced by GlobalData Thematic Research.

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