Entries open for TII OrbitSight Challenge

The Technology Innovation Institute (TII) has launched a global innovation challenge seeking AI-powered solutions that can process neuromorphic vision sensor (NVS) data for resident space object (RSO) detection, tracking, and visualization. The winning proposal will receive up to US$50,000, with the challenge open to startups, researchers, students, and enterprises developing real-time AI/ML solutions for Space Situational Awareness.

Technology Innovation Institute Neuromorphic Vision Sensor AI Challenge

The Technology Innovation Institute (TII) is inviting proposals for innovative artificial intelligence and machine learning solutions that can process raw Neuromorphic Vision Sensor (NVS) data to detect, track, and visualize Resident Space Objects (RSOs) in real time.

The challenge aims to advance Space Situational Awareness (SSA) by encouraging participants to build intelligent systems capable of accurately identifying and tracking objects in space, even under noisy and low-light conditions.

Program Overview

The competition seeks advanced AI/ML models and processing pipelines capable of transforming raw neuromorphic sensor data into actionable space object detection and tracking results.

Key challenge highlights include:

• Prize of up to US$50,000 for the winning solution.
• Open to participants worldwide.
• Focus on AI, machine learning, and computer vision.
• Real-time processing of neuromorphic vision sensor data.
• Opportunity to collaborate with the Technology Innovation Institute after the competition.

Challenge Objectives

The challenge aims to develop innovative solutions that can:

• Process raw Neuromorphic Vision Sensor (NVS) data.
• Detect Resident Space Objects (RSOs) in real time.
• Track moving objects accurately.
• Visualize detection and tracking results.
• Improve autonomous Space Situational Awareness.
• Increase satellite resilience.
• Support future national and commercial space security applications.

Focus Areas

Participants should develop solutions that address the following technical areas:

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Neuromorphic Vision Sensors (NVS)
• Computer Vision
• Real-time object detection
• Real-time object tracking
• Space Situational Awareness (SSA)
• Resident Space Object (RSO) detection
• Data visualization
• Autonomous space monitoring

Technical Requirements

Proposed solutions should be capable of:

• Processing raw neuromorphic vision sensor data.
• Detecting resident space objects in noisy environments.
• Tracking space objects in real time.
• Classifying objects while filtering background noise and artifacts.
• Detecting both dim and bright space objects across varying magnitude levels.
• Delivering low-latency AI inference.
• Supporting multiple neuromorphic sensor resolutions.
• Working with datasets provided by TII.
• Producing visualization outputs that clearly display detection and tracking results.

The complete pipeline should operate from raw NVS data input through object detection, tracking, and visualization.

Expected Solution Features

Strong submissions should demonstrate:

• High detection accuracy.
• Fast real-time processing.
• Robust performance in low-light conditions.
• Reliable tracking of multiple space objects.
• Efficient AI/ML algorithms.
• Scalable processing pipelines.
• Compatibility with different camera resolutions.
• Clear visualization and reporting capabilities.

Funding and Awards

The challenge offers:

• Winning Prize: Up to US$50,000
• Number of Winners: One

In addition to the monetary award, the winning team may have the opportunity to collaborate with the Technology Innovation Institute (TII) on future research or development projects, subject to mutual agreement.

Who Can Apply?

The challenge is open to a wide range of innovators, including:

• Startups
• Researchers
• University students
• Academic teams
• Enterprises
• AI and machine learning developers
• Computer vision specialists
• Space technology innovators

Individuals and multidisciplinary teams with expertise in AI, computer vision, and space technologies are encouraged to participate.

Submission Requirements

Participants must submit:

• A written proposal of up to five pages.
• A technical package delivered as a Docker image.

The proposal should clearly explain:

• Technical approach.
• AI or ML methodology.
• System architecture.
• Expected performance.
• Innovation.
• Visualization approach.
• Implementation plan.

The Docker package should demonstrate the proposed solution’s functionality.

Evaluation Criteria

Submissions will be evaluated based on:

• Technical innovation.
• Detection accuracy using test datasets.
• Real-time processing performance.
• Quality of documentation.
• Visualization and reporting capabilities.
• Team expertise and technical competency.
• Clarity of the proposed solution.

Solutions that balance innovation with practical implementation and high performance are expected to be the most competitive.

Why This Challenge Matters

As the number of satellites and space objects continues to increase, accurate monitoring of orbital activity has become increasingly important.

Traditional imaging systems can struggle under challenging conditions such as:

• Low-light environments.
• High background noise.
• Rapid object movement.
• Large volumes of sensor data.

Neuromorphic vision sensors combined with AI offer new possibilities for:

• Faster object detection.
• Reduced processing latency.
• Improved autonomous decision-making.
• Better satellite protection.
• Enhanced national space security.
• More reliable Space Situational Awareness systems.

The challenge encourages the development of technologies that can transform how space is monitored in the future.

How to Apply

Interested participants should follow these general steps:

1. Review the challenge requirements and technical specifications.
2. Design an AI/ML solution capable of processing raw NVS data.
3. Prepare a written proposal (maximum five pages).
4. Develop and package the solution as a Docker image.
5. Ensure the solution meets the required technical objectives.
6. Submit all required materials before the application deadline.

Applicants should carefully review the submission guidelines to ensure all technical requirements are met.

Tips for a Strong Submission

To improve your chances of success:

• Design a complete end-to-end processing pipeline.
• Prioritize real-time inference performance.
• Demonstrate high detection accuracy.
• Optimize performance for noisy and low-light conditions.
• Ensure compatibility with multiple sensor resolutions.
• Include clear documentation and architecture diagrams.
• Develop intuitive visualization tools.
• Thoroughly test the Docker package before submission.

Common Mistakes to Avoid

Avoid these common submission errors:

• Submitting incomplete documentation.
• Exceeding the five-page proposal limit.
• Providing poorly documented Docker images.
• Ignoring real-time performance requirements.
• Failing to demonstrate compatibility with multiple NVS datasets.
• Overlooking visualization features.
• Not validating the solution using representative test data.

Frequently Asked Questions (FAQs)

What is the Technology Innovation Institute Neuromorphic Vision Sensor AI Challenge?

It is a global innovation competition seeking AI-powered solutions that process neuromorphic vision sensor data to detect, track, and visualize resident space objects in real time.

Who can participate?

The challenge is open to startups, researchers, students, enterprises, AI developers, and other innovators with expertise in relevant technical fields.

What is the prize?

The winning solution will receive up to US$50,000.

What technologies should participants use?

Participants are expected to develop AI and machine learning solutions capable of processing raw Neuromorphic Vision Sensor (NVS) data for real-time Resident Space Object (RSO) detection and tracking.

What must participants submit?

Applicants must submit:

• A written proposal of up to five pages.
• A technical package in the form of a Docker image.

How will submissions be evaluated?

Entries will be assessed based on technical innovation, detection accuracy, real-time performance, documentation quality, visualization capabilities, and overall team competency.

Will there be opportunities beyond the competition?

Yes. The winning participant or team may have the opportunity to collaborate with the Technology Innovation Institute (TII) on future projects if both parties agree.

Conclusion

The Technology Innovation Institute Neuromorphic Vision Sensor AI Challenge offers innovators an exciting opportunity to develop next-generation AI solutions for space surveillance and autonomous object tracking. With up to US$50,000 in funding and the potential for future collaboration with TII, the challenge encourages researchers, startups, students, and enterprises to advance real-time Space Situational Awareness through cutting-edge neuromorphic vision, artificial intelligence, and machine learning technologies.