Drone and Drone Analytics: The Digital Surveyor
Drones are revolutionizing the concept of surveillance and reconnaissance in warfare. But drones are much more than that. Drone analytics has made it possible for drones to be employed in almost all sectors. Be it agriculture or urban planning, drone analytics has both literally and metaphorically provided experts with a bird’s eye-view on the subject. It has expanded vast opportunities of research and has furthered the range of data science and data analytics.
Precision warfare, agriculture, mining and oil extraction, property inspection, leak detection, stockpile volume calculation, digital surveying, and what not. Drones are deployed almost in every sector. Drones have become, sort of our eyes and ears from the sky that too without actually flying. Drone or technically known as the Unmanned Aerial Vehicle (UAV), is basically an aircraft without any human piloting it. Unmanned aerial vehicles are generally operated through a remote control by humans on the ground. Hence, sometimes, unmanned aerial vehicles or drones are also known as remotely piloted aerial vehicles (RPAV).
Drones are basically deployed to scan, survey and gather relevant information of an area. This data can then be used to undertake any necessary course of action depending on the nature of work the drone performs, and the area it has surveyed. Thus, the nature of the work defines what kind of information the drone will accumulate; meaning, though every drone performs the basic function of collecting data, the manner in which it collects the data and the way in which it processes the data, differs significantly. Also, the data, drone collects is asynchronous and unstructured. For drones, to collect this function-specific data and then structure it, a drone analytics software is necessary.
What is Drone Analytics?
Basic function of a drone is to hover over an area which is to be surveyed and collect necessary data. So as to enable the drone hardware to collect the data, a drone analytics software is necessary. Drone analytics, thus, includes tracking of flight of the drone, creating 2D and 3D visualizations of the area or the site which is being surveyed, and processing the visualizations in such a way, so that the user can view and edit it to suit his/her needs. The data thus processed is, in general terms, known as geospatial data.
5 Areas Where Drone Analytics is Used
Drone analytics enables a drone to survey, examine, capture, and process a piece of data according to its nature of work. This can be as basic as calculating the area of an agricultural field over which it is hovering or can be as complex as complete reconnaissance of an enemy or terrorist base camp. Here are some sectors which employ drone analytics to expand their scope of data processing:
- Agriculture: Data analytics can be used in this sector to map and plot the agricultural fields and to register their owners accordingly. Drones and drone analytics can also be employed to assess the quality of soil in a particular region, or to plan an irrigation mechanism by mapping a river, or water source nearby to the field. In case of crop failures, this technology can be used to assess the extent of the failure so as to remunerate the farmers.
- Mining: Mining or quarrying companies may deploy drones and engage in drone analytics to measure the total volume of the minerals underground. The nature and depth of the mines can thus be chalked out so as to minimize the dangers and maximize the output from the mines. Oil and petroleum companies can assess the amount of crude oil present beneath the surface, be it land or sea, before setting up an oil field in that place.
- Disaster Management: A Science Direct study has shown the opportunities presented by drone analytics in this field of remote sensing of natural hazards. According to this study, disaster management authorities can employ the services of drone analytics to assess the area or region which is hit by a certain natural disaster. This will help them in analyzing which is the most-affected area where help should reach first and will help them plan their rescue operations, if any, accordingly.
- Urban Planning: Recently, urban planning is one of the areas which has been using drone analytics, the most. Right from plotting residential and commercial areas to mapping roads and positions of streetlights, drone analytics has substantially eased the job of urban planners and architects. Property inspectors also use the drone analytics technology, to ensure whether all compliance codes are adhered to.
- Military: The drone technology and the associated drone analytics was first employed for military purpose. From locating enemy bases or terrorist camps to hitting the intended targets, drone analytics has evolved to a great extent. Predator drones is one such example of use of drone analytics in military affairs.
The increasing and varied use of drone analytics has, thus, resulted in massive surge in the drone analytics market. The global drone analytics market is expected to put up an impressive CAGR of 17.1% for the 2021-2028 timeframe.
Future of Drone Analytics
The word ‘future’ has become synonymous with artificial intelligence (AI). Drones with AI-powered drone analytics system, are being deployed in various operations. R&D is underway in agricultural use of drone analytics, so as to develop low-flying drones with AI-powered drone analytics system, that will not only assess the soil fertility, but will also recommend addition of certain fertilizers to it, so as to increase soil’s productivity. Some drones with AI-powered drone analytics system, are being developed in such way that, they will recommend the cropping patterns that should be followed to maintain the quality and productivity of the soil. Plans are being chalked out to employ new-age drones in disaster management roles, to help not only in rescue operations, but also to suggest area-specific measures to prevent the future occurrence of such disasters.
Drone analytics, thus, help to map the present world and guide its future. Further research in image processing and data sciences will augment its capabilities and help in increasing its area of operations.
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