Iris Automation, a Vancouver-based startup, raised $1.5M to bring their technology to industrial-type drones. Using NVIDIA GPUs on the Amazon cloud to train…
Overview
Iris Automation, a Vancouver-based startup, has developed AI technology that enables drones to sense and avoid obstacles, raising $1.5M to enhance industrial drone capabilities. Their system utilizes NVIDIA GPUs and Jetson TX1 to analyze video data in real-time, achieving a detection range of over 500 meters.
What You'll Learn
1
How to implement AI technology for obstacle detection in drones
2
Why specialized collision avoidance systems are necessary for industrial drones
3
When to apply AI for situational awareness in various vehicles
Key Questions Answered
What technology does Iris Automation use for drone obstacle avoidance?
Iris Automation utilizes NVIDIA GPUs on the Amazon cloud to train deep learning models and employs the Jetson TX1 onboard the UAV for real-time video analysis. This technology allows drones to detect obstacles at a range of over 500 meters, mimicking human pilot decision-making.
How does Iris Automation's system differ from consumer drone systems?
Iris Automation's collision avoidance system is specifically designed for industrial drones, which require advanced capabilities to cover long distances and monitor expansive infrastructure that may not be represented on standard maps. This includes adapting to changes like weather or new construction.
What potential applications does Iris Automation's technology have beyond drones?
An investor of Iris Automation believes that their technology could extend beyond drones to enhance situational awareness systems in other vehicles, such as cars and ships, indicating a broader applicability of their AI technology.
Key Statistics & Figures
Detection range of Iris Automation's system
over 500 meters
This range is significantly farther than current capabilities of other systems.
Funding raised by Iris Automation
$1.5M
This funding is aimed at advancing their technology for industrial drones.
Technologies & Tools
Hardware
Nvidia Gpus
Used for training deep learning models on the Amazon cloud.
Hardware
Jetson Tx1
Onboard module for real-time video analysis in drones.
Key Actionable Insights
1Consider integrating AI-based obstacle detection systems in your drone operations to enhance safety and efficiency.As industrial drones operate in complex environments, leveraging AI can significantly improve their ability to navigate and avoid collisions, which is crucial for operational success.
2Evaluate the use of NVIDIA GPUs for training deep learning models in your projects.NVIDIA's powerful GPUs are well-suited for processing large datasets and training AI models, making them a valuable asset for any AI-driven application.
3Stay informed about advancements in drone technology and AI applications.The rapid evolution of AI and drone technology can provide new opportunities for innovation and efficiency in various industries.