As a curious reader, a few days back, I was reading about the most buzzing words of this century, DRONES and ARTIFICIAL INTELLIGENCE, it was completely fascinating how these two can change the coming future of human life on the earth.
That is why, I have decided to dedicate my current blog post to these two technologies, so that, together we(me and my readers) can explore the possibilities of a new era with AI Powered drones.
Drones can be termed as flying robots but currently, the majority of them are controlled by human pilots. Drones have various benefits in the multiple industries from agricultural to real estate and from defense to package delivery.
Are We Ready for Military AI? - Data Driven Investor
Today, algorithms may come in charming shapes, such as Sophia, a robot with a lovely attitude and an enlightened…
Merely flying at a low altitude is not what makes drones special. It is their capability to capture remote data, surveillance videos and also analyze it for various objectives without much human intervention is what makes drones so lucrative as dynamic sensors. Drones can also combine electric power with efficient use of transportation ability, and can ultimately help to reduce CO2 emissions and improve many services.
To reduce the human intervention in data we need to make intelligent drones that can read, calculate, analyze and predict data themselves to provide useful information. Without Humans, drones can rely on the in-built machine learning algorithms to function.
One example of this kind of process is, let us assume that we need to teach the drones like a toddler. so, How we teach a toddler? We show them the object (like an apple) and tell them its’ name, “Apple”. Now, we need to repeat this process again and again until the toddler remembers the object and its’ name. Similarly, a simple Machine learning technique is ‘supervised learning’ in this technique we can take loads of drones’ footages (dataset of drone’s images) and label them. In object detection models we can pass this dataset and the model can remember this labeled data. Now when we feed a new test image to the model, this model, on the basis of various features can predict the label of each object inside this given image.
These models are based on deep neural networks which in turn is dependent on advanced probability & statistics techniques.
Drones with its’ own eyes:
Imagine a flying object, which can fly over hours and is connected to the internet. It can take unlimited pictures and process them and will get more intelligent every day. It can refine its software to have a more precise face detection to recognize emotions. It has been found in the tests that AI-powered drones taught itself to inspect 20 different environments by trial and error in merely 40 hours of time.
Better Obstacles Tackling:
Drones can process sensor data and plan its way ahead by analyzing the obstacles on its’ way. One of the famous Machine learning algorithms that can be used for this purpose is ‘Fuzzy logic’.
In simple terms, this algorithm will detect an object and can give a value (from 0 to 1) to all the possible labels for the object and the label with the highest value will be the solution. To learn more about it you can go to this site https://www.geeksforgeeks.org/fuzzy-logic-introduction/. It has the easiest possible explanation for this algorithm.
A Drone camera lens can zoom in on the yellow flower of a tomato seedling and use these images into an artificial intelligence algorithm that predicts precisely how long it will take for the blossom to become a ripe tomato ready for picking, packing, and the produce section of a grocery store.
Drones can reportedly leverage computer vision to monitor and spray weeds on plants. Precision spraying can help prevent herbicide resistance. Precision technology eliminates 80 percent of the volume of chemicals normally sprayed on crops and can reduce herbicide expenditures by 90 percent.
Companies are leveraging deep-learning pattern recognition algorithms to process data captured by drones to monitor crop and nutrient deficiencies in the soil. An analysis is conducted by software algorithms which correlate particular foliage patterns with certain soil defects, plant pests, and diseases.
Construction & Real Estate:
In another use case, the AI-powered drones can have predictive capabilities by analyzing the past data. For example, month-long footage captured from a construction site can be used to project how the site may look like in the next week or so.
Search & Rescue:
Drones with efficient Machine learning algorithms can analyze the images of area by themselves and only send humans the images that have particular search object. For instance, a team of humans cannot keep an eye on video footage received from hundreds of drones in real time to find a missing vehicle. However, with AI, the smart algorithm can analyze the footage received from different cameras and identify the searched object in real time.
Emergency medical supplies to remote areas:
It can detect the precise location where it has to drop medicines where human cannot reach fast. Moreover, With better algorithms, it can locate the particular address and person to which the medicines have to be delivered.
Unmanned surveillance in dangerous warzones:
As we know that AI describes the capability of machines that have characteristics of human intelligence and can perform sophisticated tasks like reasoning, problem-solving, planning and learning. AI-powered armed drones can identify the target by themselves with the help of thermal imaging cameras and can attack them without human intervention.
To have precise target identification, we need large datasets to teach drones about various environments. The database is the key starting point for identification as it will be the foundation for the analysis of thousands of facial images to make the best association between environment and the thermal signature.
There are many more possibilities which are not even explored yet, like, there is actually a drone in use by some Japanese companies called T-Frend which is “designed to reduce overtime by flying around the office after hours, playing loud music and taking pictures of any staff who are still working and reporting them to management”. They can also explore the galaxy beyond the reach of timely communications from Earth in swarms of small space probes.
Most drone data analytics companies are still using traditional methods to process data acquired from drones. But the fact that all participants responded positively to the question of whether they deploy artificial intelligence tools or not shows that AI seems to be increasingly essential to them. 37% of the respondents already completely rely on machine or deep learning and all signs indicate that this will increase as time goes on.
Further utilization and development of these powerful intelligent data processing tools will help in greatly reducing the processing time of big data, which is a huge challenge today. So we can conclude that, as AI applications in the drone industry are gaining importance, highly automated flights will become more feasible and more common.