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Published: 04/04/2024

How Can Artificial Intelligence and Computer Vision Enhance the Capabilities of Your Drones?

AI-Powered Drones for the Manufacturing Industry

If you are a drone producer or enthusiast interested in AI and CV technologies in drones, this article will explain how these advancements would help you build better drones for different applications. 

The global drone market is expected to reach USD 35.28 billion in 2024 and grow at a compound annual growth rate (CAGR) of 13.90% to reach USD 67.64 billion by 2029. The share of smart drones is expected to dominate agriculture, media and entertainment, delivery and logistics sectors.Technological advancements like Artificial Intelligence (AI) and Computer Vision (CV) allow drones to be even more autonomous and versatile, saving costs and human labour. However, it also poses new challenges in the drone production segment.

How Can Artificial Intelligence and Computer Vision Enhance Drones?

Advanced technologies like AI and CV allow drones to understand and interact with their environment by identifying obstacles, classifying objects, and tracking movements during flight. This technology relies heavily on machine learning and deep learning algorithms to improve prediction accuracy and automate navigation and obstacle avoidance tasks.

AI is pivotal in processing drones’ visual and sensor data, allowing for real-time decision-making. Through advanced image processing and neural networks, drones can detect objects, perform precise tracking and classification, track objects and navigate autonomously. Neural networks, a subset of AI, analyse vast amounts of data to identify patterns and make decisions faster and more accurately than humans.

Utilising Computer Vision and Artificial Intelligence in drones creates new opportunities for you to tackle challenges in various industries. With the capacity for real-time data processing, autonomous decision-making, and versatile application across sectors, drones equipped with AI and CV can be an essential tool for business operations.

Smarter and More Reliable Drone Navigation and Autonomy with Artificial Intelligence and Computer Vision

Robust flight navigation is one of the critical aspects of an autonomous, intelligent drone. Solutions for autonomy and navigation based on CV and AI are constantly evolving, making them more reliable and accurate. For example, using liquid neural networks enables the UAVs to adapt to new data inputs and reliably make decisions in unknown domains like forests and urban landscapes. This shows that AI and computer vision can enhance drone autonomy for search and rescue, delivery, and wildlife monitoring applications.

With ongoing research and development, drones equipped with these technologies are set to become even more versatile, autonomous, and indispensable tools in addressing real-world challenges.

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Real-Time On-Board Data Processing in Drones for Increased Efficiency and Process Optimisation

Swift, real-time data processing and correct collection are essential to benefit from AI-powered drones fully.  Edge computing further augments the capabilities of drones by processing data in real-time or near the point of origin. This integration allows drones to capture and analyse data on the fly, enhancing operations in agriculture, logistics, construction, public safety, and energy and utilities.

Real-Life Application Examples of Utilising Real-Time Data Processing

  • Edge-enabled drones offer real-time insights for precision farming, improving crop yields and agricultural operational efficiency.
  • Capturing and transmitting real-time data helps to optimise delivery operations, especially last-mile delivery in logistics.
  • AI-driven advancements enable drones to identify better and mitigate threats posed by unauthorised drones, ensuring the safety of critical airspace around airports and other sensitive areas.
  • Construction benefits from improved site monitoring and safety, while public safety operations gain better situational awareness during emergencies. Similarly, energy and utility sectors use edge-enabled drones for efficient infrastructure inspection and monitoring.

Practical Applications of AI-Driven Drones Across Industries

Drone technology can find its purpose across different industries. Here are some of the industries where using drones enhanced with AI and Computer Vision can bring you fast and reliable results and, ultimately, profit.

AI-Powered Drones for the Manufacturing Industry

Large manufacturing facilities and plants face various requirements to maintain the quality, consistent flow and efficiency of operations and ensure the safety of employees. Smart drones can help automate some processes and inspections to make them obtainable. Here are some of the notable applications:

  • Visual inspections: UAVs equipped with advanced computer vision systems can excel in conducting thorough visual inspections within industrial environments, as they can access hard-to-reach and potentially hazardous areas that might be inaccessible to humans. It can be achieved through multiple cameras propelled with machine learning detection algorithms to help them recognise the objects and classify them for potential malfunctions and emergencies.
  • Improved logistics and supply management: Drones fuelled by AI and CV can use their sensors to aid in automated material handling, significantly streamlining logistics operations and cutting operational expenses.
  • Predictive maintenance: Drones with sound-sensing systems focus on object detection and differentiating between normal operational sounds and any irregular noises indicating potential failures. This innovative approach utilising AI drones supports the early detection of issues, which prevents downtime and increases safety.

Aerial Inspections with AI Drone Technology for Large-Scale Farming

In the face of global climate change, properly surveilling plant and livestock health on large-scale farms is essential. 

  • Livestock safety monitoring: Drones with AI enhancements and advanced vision systems can completely transform identifying fence breaches, safeguarding the livestock from potential escape.
  • Plant health monitoring and crop yield prediction: AI-powered drones with multispectral sensors offer a new approach to precision farming. Our AI drone applications delve deep into vine health assessment, crop yield prediction, and disease detection, offering unparalleled optimisation for agricultural operations.
  • 3D mapping and planning: Drone technology can also elevate construction project planning and management. With advancements like LiDAR, UAVs can generate detailed 3D maps, providing insights for improved project accuracy and efficiency and speeding up construction projects and enhancements across farms.

Drone Operations for Safer and Smarter Cities

AI drones can introduce a significant change to urban landscapes and operations. With city lives becoming increasingly busier and more advanced technologically, modern, highly-populated can benefit from using intelligent drones to increase routine city maintenance and safety among thousands or even millions of citizens.

  • Maintaining cleanliness in cities: Using machine learning algorithms and sensors enables litter detection and ensures the immaculate state of city landscapes. AI-powered drones help to redefine city maintenance for cleaner and more livable urban areas.
  • Faster and better-coordinated emergency responses: Thermal imaging capabilities allow the new generation of AI drones to revolutionise emergency response strategies and search and rescue missions. These flying robots are capable of quick damage assessment and swift action deployment to minimise operational risk and downtime and increase safety measures in critical situations, allowing first responders speedy reaction. 
  • Construction site monitoring and safety: Drones can be an ideal tool for the surveillance and inspection of large construction sites, helping to track progress and look for potential threats and elements lacking in quality, allowing for appropriate action to fix the problem early before further progress makes it impossible.
  • Supporting safety in cities: Moreover, AI-driven drones can significantly improve city safety monitoring thanks to their surveillance capabilities. Night-time surveillance can help increase the safety and response of emergency services by quickly notifying them about compliance breaches or dangerous situations that may occur.
Drone Operations for Safer and Smarter Cities

Technical Limitations and Industry Challenges of AI-Powered Drones and Technologies to Overcome Them

The benefits of utilising artificial intelligence drones across different sectors and their development come with unique challenges. AI drones face several industry-specific challenges that could concern you as a producer, including:

  • Energy efficiency and battery weight for endurance and long flights
  • Low-signal areas that can influence the correct navigation and detection processes
  • Communication stutters in various environments

Fortunately, there are technological advancements that allow us to overcome these challenges effectively, ensuring seamless AI drone operations. Here are some of the solutions to the abovementioned issues.

Addressing the Problem of Heavy Batteries for Long Drone Flights with Hydrogen Fuel Cells

The heavy batteries that power drones limit their flight duration. Longer drone flights and reliable energy sources are essential for seamless operations and ensuring that drones can perform their tasks reliably at all times.

One proposed solution to the endurance problem is using hydrogen fuel cells, extending flight times up to three times longer than traditional battery-powered aircraft, operating silently, and only emitting water, offering a quick refuelling process.

The continued advancement of hydrogen fuel cell technology, alongside developments in AI for optimised flight path planning and energy management, can significantly extend the endurance of drones. This would open up new possibilities for their use in various applications, from environmental monitoring to delivering goods over long distances.

Good optimisation of onboard systems and data storage and processing capabilities for drones can enable sustainable energy consumption, allowing reliable operations endurance.

Technologies that Help AI Drones Maintain Correct Navigation in Low-Signal Areas

Autonomous drones typically rely on GPS for accurate positioning during flight. The absence of the GPS signal can challenge correct navigation when flying. Enhancing navigation capabilities is essential for improving drone operations’ autonomy, efficiency, and safety, especially drone flights in complex and dynamic environments.

Technologies like Internal Measurement Unit (IMU), optical flow sensors and Simultaneous Localisation and Mapping (SLAM) enable drones to maintain course and avoid obstacles in GPS-denied environments, allowing drones to navigate through complex indoor spaces or densely packed urban areas.

Adopting Different Communication Methods for AI Drones to Maintain Constant Connection and Reduce the Risk of Signal Loss in Different Environments

To function correctly, drones must remain in constant communication or employ edge devices to ensure no essential data is lost. Lack of reliable communication can severely handicap the outcome of drone operations. Fortunately, there are different ways to ensure your AI drones stay connected.

In AI-powered drones, communications are pivotal in ensuring seamless operation, data transmission, and integration into the broader network infrastructure. Effective communication systems allow drones to send and receive critical information in real-time, facilitating tasks such as navigation, obstacle avoidance, payload delivery, and data collection.

Satellite Communication in AI Drones that Require Long-Distance Coverage

Satellites’ global coverage allows drones to operate in remote areas, including oceans, deserts, and high-altitude environments. This is particularly useful for operations in remote or challenging environments where traditional communication networks are unavailable. 

However, high latency and the cost of satellite bandwidth are significant challenges. Additionally, satellite communication equipment’s weight and power requirements can impact the drone’s payload capacity and endurance. 

That’s why optimising other components and aspects is good before deciding on satellite communications, such as adjusting the network scale and onboard systems and choosing the optimal option for satellite communications. For example, Low-Earth Orbit satellites offer lower latency and higher bandwidth than Medum-Earth Orbit or Geostationary ones.

Keeping Drones Connected in Urban Areas with the Use of Cellular Networks

Utilising existing cellular networks, such as 4G/LTE and the emerging 5G, drones can achieve reliable and high-speed data transmission over considerable distances. Cellular networks offer a readily available infrastructure with extensive coverage in populated areas. High data rates suitable for video streaming and real-time data analytics are crucial advantages of using cellular networks.

However, coverage can be inconsistent, especially in rural or undeveloped areas. The vertical coverage of cellular networks, designed primarily for ground users, can also be limited, potentially affecting connectivity at higher altitudes. Therefore, this communication method is the best for city maintenance and monitoring efforts, as it allows the drones to thrive in such environments.

Cost-Effective Wi-Fi and Radio Frequency (RF) Communications for Drones Operating Locally

Short-range communication technologies like Wi-Fi and RF are commonly used for local operations, such as recreational flying, indoor navigation, and proximity surveillance. It’s a low-cost and widely available technology suitable for various applications. It supports high data rates for short distances and is ideal for transmitting video feeds and telemetry data within a localised area.

However, it displays limited range and susceptibility to interference from other wireless devices. Signal degradation can significantly impact performance in densely populated areas or environments with many obstacles. However, there are several ways to overcome this challenge, for example, adjusting the frequencies to minimise the interference from other nearby devices, using advanced communication protocols or integrating other communication methods like cellular or mesh networks to support Wi-Fi and radio connections.

Communicating Multiple Drones and Boosting Connection Resilience  via Mesh Networks

Mesh networking allows multiple drones to communicate with each other and create a distributed network. This can extend the communication range by using drones as relay points and improve the redundancy and resilience of the network. It facilitates scalable and flexible operations, especially for drone swarms and collaborative missions. Mesh networks can dynamically adapt to changing conditions and maintain connectivity even if some nodes fail.

The challenge of operating with these networks comes from complex management and the need for sophisticated algorithms. There’s also a trade-off between network performance and the computational overhead necessary for maintaining the mesh. However, with experts like ours, it will be possible and manageable. We’ll optimise the onboard systems and scale the network to support reasonable energy consumption levels, allowing the connected drones to maintain constant communication for longer periods.

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Step-by-Step Guide on How We Will Help You Build Smart AI-Driven Drones

If you produce drones and would like to collaborate with technological experts who will deliver the technology that will drive your UAV efforts to the next level with artificial intelligence and computer vision, here’s how we can work together:

  • We’ll meet at a discovery workshop to help us understand your needs, define them, and learn our methods and proposed solutions. We will tailor the best options for your needs; even if you don’t have them wholly established, we will also help you put them into words.
  • Once we understand your goals and establish agreement on the technologies and solutions, we’ll take several weeks to develop a Proof of Concept (PoC) to showcase the idea and how it would work. It will give you insight into the solution at an early stage and help you voice your concerns, which we will be happy to address. It will also help us build mutual trust for our team and methods.
  • Once you approve the PoC, we will plan and estimate the following stages of the project and how we’ll work on each aspect until its successful conclusion.

Naturally, we will stay in contact at every step and in between, always available whenever you need. Our experts will answer your questions in a way you’ll always understand. So don’t hesitate to leave us a message. Let’s talk and build your future together.

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Katarzyna Świątek

Content Specialist at DAC.digital

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