What is the future of drone?

 Drone, unmanned aerial vehicles (UAVs), including quadcopters, multirotor, or unmanned aerial systems (UAS). It's been over 100 years since its inception, but recent breakthroughs in hardware, software, and data processing have allowed UAVs to become commercially mainstream. In the U.S. alone, the Federal Aviation Administration (FAA) predicts a tenfold increase in the commercial drone fleet from 42,000 to 420,000 between 2016 and 2021, and European authorities expect similar growth. 

What developments in drone technology and its applications can be foreseen in the future? Consider the following examples.

 

01 The power of UAVs

Drones need an adequate power source. Many companies and research institutes are exploring many directions, one is to solve the problem from the power supply of the battery itself, which can extend the time of flight time.

(1) Solar panels charge the batteries during flight.

② hydrogen fuel cells that allow longer flight times and heavier payloads.

(3) Lasers for wireless transmission of electricity.

(4) nanotube and aerogel batteries, whose performance far exceeds that of lithium-ion polymer batteries currently in use.

Another direction is finding a way to make the drone truly unmanned, called drone dock, which can make drone charging automatically and truly unattended. Drone box like a home base and control station. The manufactures like percepto, sunflower labs, HEISHATECH released the drone in the box products.

02 Drones will embrace big data

Drone manufacturers are working to develop automated obstacle avoidance systems that process drone sensor data to avoid collisions or allow automated takeoffs and landings. The technology is currently used in a small number of devices and is constantly being improved. Boston-based American Robotics and other companies have developed fully automated drone systems that can repeatedly, reliably perform well-defined tasks without pilot intervention.

Smarter drone sensors, combined with machine learning and artificial intelligence, allow companies to apply predictive analytics to numerous business problems. For example, researchers at Purdue University have successfully combined drones and deep learning techniques to detect cracks in the steel components of nuclear power plants. The system automatically identifies cracks based on the changing texture around the steel surface and informs technicians of potential threats. The process takes about a minute. This not only saves technicians' time, but also allows work to be distributed more efficiently and reduces unknown risks. U.S. drone manufacturer and service provider (Kespry) is targeting the inspection and insurance markets by building a machine learning system that can calculate hailstorm strikes on roofs.

By combining drone technology with machine learning, drones are able to automate the collection of photos, live video, thermal or ortho aerial imagery and radiometric data. Building and infrastructure managers can now identify quality defects, failures or design flaws faster and at a lower cost. Automated drones are also being used to inspect power plants and transmission lines and provide real-time analysis of infrastructure conditions. Farmers are also using similar technology to automatically count crops, identify weeds, and determine when crops need water and fertilizer. Numerous other applications exist for automated drones.

Drone missions - current and future

Current.

Drone flights are usually within visual range missions conducted under the control of certified operators. Flight paths and altitude ceilings are limited by government legislation and current insurance provisions. A typical flight lasts less than an hour and one or two sensors collect several gigabytes of data. The data is stored on board the aircraft and retrieved and processed after the flight.

Future.

Drones will use detection and barrier technology for highly autonomous missions. Drone traffic control centers will identify and track drones in critical airspace. Flights will become more widespread due to improved legislation and insurance. Multiple onboard sensors will transmit data in real time over 4G/5G cellular networks. Operator control centers applying machine learning and artificial intelligence will use this data to automatically modify drone missions and drive a large number of commercial applications.

Drone applications

Mining. Drones will be used in conjunction with Internet of Things (IoT) sensors to digitally manage mine operations. Drones can provide data on truck, ore and supply flows on and off the mine site to optimize daily operations, as well as provide data to aid in pit design.

Agriculture. Drones are currently used for land surveys and other data collection applications. In the future, they may be used to support precision agriculture, which relies on data about conditions in different parts of the field to more precisely manage irrigation and pesticide spraying. The goal is to increase crop yields while reducing the use of expensive inputs.

Energy and utilities. Drones can be used to automate inspections of offshore drilling rigs and refineries, reduce risk and enable preventive maintenance, and avoid costly disruptions due to equipment failure. For utilities, drones can not only be used to better and more timely monitor transmission lines and solar farms, but also to reduce theft.

Insurance. Drones can be dispatched to record digital video of post-storm damage to homes and buildings, as well as cars at crash sites. These capabilities can reduce claims processing costs, speed up customer service and generate additional coverage data. By combining drones with machine learning, insurers will be able to improve their damage predictions. By assessing risk better than ever before, insurers will be able to set premiums more accurately.

Enforcement. Drones can be used to monitor traffic accidents, capture crime scene photos, search for missing items and people, track suspicious people or vehicles, monitor crowds during protests and sporting events, replace or replenish security, support border security, perform maritime surveillance, and many other tasks.

Meteorology. Drones can provide highly accurate meteorological data on a very short time scale and on a local scale. The combination of drone and satellite data helps produce more accurate weather forecasts.

Communications. In the future, drones will be used to broadcast telecommunication signals such as radio, television, and the Internet, both for permanent and temporary missions. For example, drones could form portable mobile cell sites to provide temporary wireless network coverage for locations where cellular data coverage is low or impaired, such as during major public events or natural disasters.