AI in Drone Development is Reshaping the Future

The advent of AI in drone technology enables drones’ autonomous intelligence and decision-making process abilities, empowering them to execute complex tasks progressively with remarkable efficiency.

As a key industry use case, the unarmed vehicle sector has seen rapid growth in development, deployment, and operations nationwide, driven by its full embrace of AI and machine learning technologies.

As a result, drones have transformed from a mere remote-controlled device into intelligent, self-governing systems capable of driving positive change across various sectors. In this article, we’ll explore how AI is changing drone capabilities, the challenges it brings, and the ethical considerations surrounding its implementation.

How does AI drive drone technology?

From the broadest possible perspective, AI enables independent functioning, increased data collection, enhanced integration, and optimized flight plans. In addition, drone technology benefits from:

Enhanced perception and sensor integration

Drones gather information using cameras, LiDAR, radar, and infrared sensors. However, with the help of AI technology, drones can make sense of the data collected in real time. This helps create a very detailed and dynamic understanding of the surroundings, allowing them to identify objects, navigate complex environments, and avoid obstacles with remarkable precision.

Easy navigation and path planning

One of the most significant things about AI integration is that it allows drones to fly autonomously. By integrating data from sensors, GPS, and pre-programmed flight plans, drones can navigate to specific locations, follow predetermined paths, and even adapt their routes to real-time problems or changes in weather conditions. This level of independence is important for tasks that require aerial inspections, surveying large areas, package delivery etc.

Independent functioning

Advanced AI systems allow drones to process data and perform actions instantly without the need to have a constant connection to a remote server. This edge computing capability makes drones more independent and faster, especially in remote areas or locations that have limited network coverage.

Applications of intelligent drones in the real world

The integration of AI algorithms is expanding the application of drones in several fields. Below are the popular application areas.

Search and rescue operations: Intelligent drones are used to find missing persons or disaster survivors, even in the most challenging situations, further facilitating rescue operations, damage assessment, and optimal resource allocation.

Agriculture: AI-powered drones can monitor crop health, detect diseases, optimize irrigation, and apply fertilizers with remarkable accuracy. They provide farmers with actionable data, which further helps reduce resource wastage and increase crop yields.

Surveillance and security: AI-powered drones can monitor large areas, identify suspicious activities, and track individuals or vehicles in real time. The facial recognition and object detection algorithms enhance its ability to identify potential threats.

Delivery and logistics: By smartly adapting and planning routes, drones can navigate complex urban environments, avoid traffic congestion, and deliver packages directly to recipients’ doorsteps. Drones can even extend delivery services to remote locations that are otherwise inaccessible by traditional means.

Environmental monitoring: Environmental scientists use AI-powered drones to monitor ecosystems, track wildlife, and assess the impact of climate change. By regularly inspecting areas, scientists can identify trends and potential threats, ensuring more timely intervention.

Mining: Drones are being used in mines to create high-resolution maps and surveys of mining sites. This minimizes the need for manual intervention in potentially hazardous situations, thereby helping to save human lives and reduce costs.

AI drone examples

Skycatch Explore2 UAS

Skycatch is a US-branded and registered industrial drone solution that utilizes best-in-class hardware.

Japanese construction giant Komatsu uses Skycatch-integrated drones on more than 5,500 job sites. According to the company, the drones can generate 3D imagery that’s accurate up to five centimetres. The integrated software then takes only about 30 minutes to process aerial images, as opposed to days for humans to accomplish the same task.

Neurala

Neurala uses the Lifelong-Deep Neural Network (L-DNN)™ technology that emulates the functions of the human brain for navigation and perception. It automates the inspection process and reduces the amount of data that must be reviewed by inspectors, further helping reduce costs, improve productivity, and speed up remediation activities.

The Lindbergh Foundation’s Air Shepard initiative uses Neurala-powered drones to stop elephant and rhino poaching. The organization is effectively using this drone to research, develop, and implement a suite of technologies to stop wildlife crime.

Skydio

Skydio drones combine AI supercomputers and 13 cameras to capture video footage. The drones help public safety agencies, the federal government, and private companies serve their communities more safely and effectively by providing real-time access to information captured with high-powered cameras mounted on smart flying robots.

Skydio drones are used by every branch of the US Department of Defense, over half of all US Departments of Transportation at the state level, and more than 200 public safety agencies in 47 states.

Skydio drones are also used by allies of the United States, including the UK Ministry of Defence, the Israel Defense Forces, and the Indian Armed Forces. Skydio drones are also sold in the commercial market, where they hold a 4 percent market share as of 2021.

Key challenges/concerns in AI-driven drones

AI in drones raises several ethical and privacy concerns due to its potential impact on individuals and society. 

Privacy and data concerns

The widespread deployment of AI drones could lead to increased monitoring and control of individuals’ activities, which could raise debates about security and personal freedom. The data collected and processed by AI-driven drones is vulnerable to cyberattacks. If unauthorized parties access this data, it could be misused. Preventing data transmission is critical to prevent illegal access and misuse.

Responsibility and accountability

As AI-based drone application systems become more autonomous and complex, questions arise about accountability and liability in cases of accidents, incidents, or unintended consequences. This unclear responsibility can make drone handling tricky and complicated.

Algorithmic bias and fairness

Like other AI-based drone application systems, the algorithms and models used in AI-powered drones can exhibit biases or unfair decisions due to biased training data or flawed algorithms. This may be a cause of worry because not everyone will agree or understand the decisions made by autonomous drones.

E.g. A handful of startups are developing AI-controlled killer drones to handle wars globally. Being autonomous military drones, these machines can act decisively and quickly while calculating/recalculating and adjusting in real-time. However, a slight miscalculation can create a havoc, leading to a huge loss of human lives.

The possibility of life-or-death decisions being taken by machines that are not under the direct control of humans needs to be taken seriously.  If not, it would make the world a more dangerous place to live. 

The future of AI in drone development

Artificial intelligence is changing the way we work, and the drone industry is no exception. Advances in AI are enhancing the way drones collect data, process information, navigate the environment, and manage automated missions. However, we are only at the tip of the iceberg. As AI becomes more prevalent in the drone industry, it will deliver insights and efficiencies that are unlike anything we have seen before. Keeping up with these innovations is essential for everyone in the tech field, as they will offer both exciting opportunities and new challenges in the coming years.

Developing comprehensive guidelines that regulate the use of AI is essential. These frameworks should address concerns about autonomy, accountability, and transparency. Likewise, efforts must be made to ensure fairness, non-discrimination, and ethical decision-making. Training programs and certification courses should be conducted to equip individuals with the necessary skills and expertise to use and maintain AI-based Unmanned Aerial Vehicle (UAV).

In brief

The convergence of artificial intelligence and drones has ushered in a new era of technological innovation. With the continued advancement of AI algorithms and machines, we can expect further breakthroughs and applications that will reshape our world.