Hawai.tech Automated Drone Mission Planning: Real-Time AI and Multi-Vehicle Type Support #ces2025

Posted by – January 19, 2025
Category: Exclusive videos

Hawai.tech, a French startup specializing in drone mission planning, is revolutionizing drone operations through advanced automation. Led by CEO and co-founder Rafael, the company focuses on making drone missions more efficient by automating waypoint planning. This eliminates the need for manual pilot input, a process that can be both time-consuming and prone to errors. Hawai.tech’s solutions are designed to adapt to a future where autonomous drones dominate, optimizing efficiency and reliability for diverse applications. Learn more about their work at https://hawai.tech.

At the core of their technology is a mapping system that enables users to import and fuse multiple data layers. By combining these layers into a single comprehensive map, users can prioritize areas of interest and define exclusion zones based on mission objectives. For example, in a gas leak detection scenario, buildings may be marked as exclusion zones, while pipelines and old infrastructure, prone to leaks, become priority areas. This layered approach ensures precise mission planning tailored to specific needs.

Hawai.tech’s solution extends beyond aerial drones to include naval, terrestrial, and even submarine drones, demonstrating the versatility of their AI-powered tools. Their software provides the necessary waypoints for various vehicles, streamlining operations for industries ranging from environmental monitoring to infrastructure maintenance. By integrating AI, the system calculates optimal paths, saving time and reducing operational costs compared to traditional piloted methods.

In a live demonstration, Rafael showcased the real-time capabilities of their software. The platform runs smoothly on a laptop or browser, enabling users to select mission areas and adjust parameters dynamically. As layers appear on the map, users can modify weights and visualize the importance of different factors, such as old pipelines or known problem areas. This interactivity highlights the tool’s adaptability and user-friendly design.

The software’s precision eliminates the inefficiencies of manual piloting. Previously, operators needed to navigate drones manually, often leading to unreliable results. Hawai.tech’s AI-driven approach ensures consistent, accurate waypoint planning, allowing drones to execute missions autonomously and with high reliability. This technology significantly reduces the cost and complexity of drone operations.

Hawai.tech’s focus on real-world applications is evident in their collaboration with drone manufacturers and end-users. By providing a flexible platform compatible with multiple drone types, they address a wide range of operational challenges. From aerial surveillance to underwater inspections, their solutions exemplify the potential of AI-driven autonomy in diverse environments.

The future of mission planning lies in automation, and Hawai.tech is at the forefront of this transformation. Their technology promises to enhance safety and efficiency, enabling drones to handle complex tasks without human intervention. With scalable applications across industries, the company is setting a new standard for autonomous operations.

Hawai.tech’s innovation not only advances drone technology but also underscores the potential of AI in reshaping industries. Their focus on practical, reliable solutions positions them as a leader in the field of autonomous mission planning. As the demand for efficient and cost-effective drone operations grows, Hawai.tech is poised to play a pivotal role in driving this evolution.

Description by Chatgpt.

My full video coverage from #CES2025 in Las Vegas USA is sponsored by Synaptics, check out all my Synaptics videos here: https://www.youtube.com/playlist?list=PL7xXqJFxvYvhAbQoe9YN4c84SqXxIY3fQ

This video was filmed at CES 2025 in Las Vegas USA, check out all my CES 2025 videos here: https://www.youtube.com/playlist?list=PL7xXqJFxvYvglnj4eE-BVnVzrj9XyerqI

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