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Drones do more than just shoot beautiful videos during travels and other memorable events. They deliver parcels, monitor objects, and can even replace people on deadly missions. Read this article to find out what businesses can use drones for and why, as well as how we help iFarm, an AgroTech startup, address business challenges using drones.
Drones, much like the Internet and GPS navigation systems, are developing beyond their military origin and becoming a powerful business tool. With technological advancements in and the rise in popularity of these small unmanned devices, the application areas of drones are growing rapidly. It’s no wonder that businesses all over the world are competing to get more out of this promising market. Research and Markets experts predict that the global UAV-based services market will grow up to $63.6 billion by .
Source: Research and Markets
Progress in the UAV industry is being spearheaded by companies such as Walmart, Amazon, Sentera, Airwood, XAG, DroneAg, among others. Together with our partner iFarm, we also explore the unmanned technologies and apply them to solve business issues.
Drones have long ceased to be merely for entertainment purposes. These days, they easily cope with tasks that were previously considered impossible, and are becoming ever more useful and indispensable. They are already used in construction, agriculture, forestry, surveying, mining, energy, logistics, real estate, security, and safety.
One of the most common uses of drones in business is to deliver parcels and cargo. During pandemics, this solution is especially relevant as delivery by drones is contactless. In the United States, Finland and Australia, consumers are already getting essential goods, food and over-the-counter medication with the help of Wing drones developed by Alphabet (Google’s parent company).
Drones equipped with computer vision and machine learning technologies help businesses:
Since the spring of , Azoft has been working with the agricultural company iFarm. We help automate the linear business processes of production. To this end, we have developed and continue to improve upon a holistic IT infrastructure.
We also apply our research in the fields of autonomous flying drones, neural networks, and machine learning to automate production. Keep reading to learn about our progress, including the tasks set for us, the difficulties encountered, our decisions, implementation details and future plans.
Within the scope of current tasks on the iFarm project, we believe that unmanned technologies are promising in two key ways:
This solution helps to avoid the problems of classical delivery methods such as rental and maintenance of warehouses as well as the processing of products for storage, among others.
Developing courier drones is an ordinary task. We need to finalize them to the cargo format and create a classic delivery infrastructure, which will include:
In this direction, we worked less actively due to restrictions on the use of airspace by Russian legislation. However, recent positive changes in laws and the urgency of the pandemic have allowed us to resume work on the creation of a test infrastructure and a dispatch center for drone delivery.
The height of such objects depends on the room where iFarm autonomous growing technologies will be used.
This task turned out to be more difficult. The main problem was navigation inside a confined space. The farms are isolated from the outside as it is required to ensure biological safety and stability of the indoor air composition. This made it impossible to use GPS or GLONASS positioning technology, which cannot operate indoors.
Using an autonomous drone is perhaps an even more challenging task. Our R&D Department has accepted the challenge to create a solution within the framework of iFarm technologies.
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Pros of using drones:
The main disadvantage, or rather challenge, is the lack of stable and affordable methods of positioning indoors. Drones for aerial photography use GPS positioning systems together with accelerometers, compasses and electronic pendant systems for cameras. Most of these systems are not available indoors, so we needed to develop a positioning system.
With the help of the drone, we can satisfy most of iFarm’s monitoring system requirements, but the main challenge we are currently working on is the indoor positioning system.
There are several standard ways to solve the problem. These are, for example, ultrasonic or broadcast sensors with a map of their installation indoors. The drone monitors the current signal strength and correlates with the frequency and signal strength of the sensors on the room map – similar to GPS in an enclosed space.
Another classic method is marker positioning combined with “optic flow” technology. We chose this as the first prototype. This method does not require the installation of additional equipment in the room. You just need to stick the markers at the control points of the drone’s movement map.
We conducted successful tests that showed decent positioning accuracy with an error of 5-10 cm for a six-motor configuration. We concluded that the design of the copter is too large and not mobile enough. To fix this, we rebuilt the drone. Its structure was made on a classic model with four engines. This, together with the drone structure changes, increased positioning accuracy to the required level, which allowed operating in a limited space. We believe that this combination can already be put into production. All that remains is to make simple changes to provide greater security for the farm and its employees, namely:
These tasks are linear. The main complex and risky tasks were made by us earlier.
The drone consists of a carbon frame, a flight microcontroller with software, brushless motors, engine speed controllers and software, propellers, a battery, peripheral power supply system, lidar and wires connecting all of the subsystems. The flight microcontroller has a built-in accelerometer, barometer, temperature sensors and other sensors that monitor the current consumption and voltage of the battery.
A brief algorithm of the flight microcontroller is as follows:
This is only part of the entire drone system. There is also a microcomputer installed on the drone. We are testing various microcomputers of an appropriate size. We have already mastered Raspberry PI, Rock Pi and Nvidia Jetson Nano. The next one is the most productive and technologically advanced in its size, the Nvidia Jetson Xavier NX, which opens up new horizons for the development of intelligence of the drone.
On such microcomputers, we perform calculations for various algorithms of computer vision, odometry and neural networks. Concurrently, we use video streams from cameras along with the sensor data provided by the flight microcontroller. Thus, the microcomputer and the microcontroller help each other stabilize the drone in space. Additionally, with the help of microcomputers, we encode and convert various formats of video streams and solve applied problems, including drone control.
At the first stage, we wanted to check whether the results were accurate enough when using the concept of marker positioning for “narrow” monitoring tasks. The drone was expected to automatically fall into the aisles between 80 cm wide rows and carry additional equipment on board. We needed to select and test the most efficient component model of the drone, its aerodynamic shape, and check a number of electronic components from Chinese, Turkish and American suppliers. After six months of work, we completed all the tasks. We are pleased with the results and, during the research process, generated many ideas for further improvement upon the design.
As for the monitoring system, we plan to work on the following areas:
As part of the task of creating a delivery system using drones, we plan to:
We are grateful to iFarm for the opportunity to apply our research to the benefit of business and industry progress. We will continue to work together with great interest and ardour to improve upon current solutions.
From fast deliveries during rush hour to scanning an inaccessible object, drones are useful anywhere a human cannot act instantly and effectively.
Improving production efficiency, reducing workload and production costs, as well as solving security problems on a large scale, are just some tasks that drones solve worldwide.
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