Go offline with the Player FM app!
Counting What Counts: How Edge AI is Saving Japan's Seafood Industry
Manage episode 473821856 series 3574631
When SoftBank's team was approached by Japanese fishermen struggling with declining catches and inefficient practices, they knew technology could offer a solution. Their response: an innovative Edge AI system that transforms traditional aquaculture through sophisticated computer vision running directly on smartphones.
Japan's fishing challenges are emblematic of global food security concerns. With the country's self-sufficiency rate at just 38% and fish catches halved from peak levels, the stakes couldn't be higher. Traditional aquaculture has relied heavily on intuition rather than data, making it nearly impossible to optimize feeding (which represents 60-70% of operational costs) or accurately monitor fish populations.
The SoftBank and AIZip collaboration tackles these challenges through a remarkable edge computing approach. What makes their solution particularly groundbreaking is how it functions in environments with zero infrastructure—no power supply, no connectivity, and corrosive saltwater everywhere. By developing density-based crowd counting AI models that run efficiently on edge devices, they've created a system that can count hundreds of fish with 96% accuracy in clear water and 86% accuracy in muddy conditions.
Perhaps most fascinating is their development process. Unable to collect sufficient real-world training data underwater, the team developed a sophisticated Unity-based simulation that generates realistic fish behavior under various conditions. This simulator provided 65% of their training data, complemented by manual observation from divers who documented actual fish behavior at different depths and feeding stages. The result is an AI system that not only counts fish but can potentially detect hunger levels, health issues, and optimize feeding schedules.
This CES 2024 Innovation Award-winning technology demonstrates how Edge AI can transform traditional industries without requiring massive infrastructure investments. By bringing intelligence directly to the point of data collection, even in the most challenging environments, we're witnessing the beginning of a new era in sustainable food production. Whether you're involved in agriculture, environmental monitoring, or any field requiring intelligent sensing in harsh conditions, the lessons from this underwater AI revolution could transform how you approach your next challenge.
Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org
Chapters
1. Counting What Counts: How Edge AI is Saving Japan's Seafood Industry (00:00:00)
2. Introduction and Austin Conference Recap (00:00:58)
3. Introducing Aquaculture Challenge with SoftBank (00:03:32)
4. Japan's Fishing Industry Problems (00:11:13)
5. SoftBank's Fish Cage Research Approach (00:18:59)
6. Computer Graphics Simulation for Fish Tracking (00:27:38)
7. AI Model Development and Implementation (00:36:05)
8. Hardware Challenges in Marine Environments (00:42:14)
9. Future Applications and Q&A Discussion (00:48:37)
37 episodes
Manage episode 473821856 series 3574631
When SoftBank's team was approached by Japanese fishermen struggling with declining catches and inefficient practices, they knew technology could offer a solution. Their response: an innovative Edge AI system that transforms traditional aquaculture through sophisticated computer vision running directly on smartphones.
Japan's fishing challenges are emblematic of global food security concerns. With the country's self-sufficiency rate at just 38% and fish catches halved from peak levels, the stakes couldn't be higher. Traditional aquaculture has relied heavily on intuition rather than data, making it nearly impossible to optimize feeding (which represents 60-70% of operational costs) or accurately monitor fish populations.
The SoftBank and AIZip collaboration tackles these challenges through a remarkable edge computing approach. What makes their solution particularly groundbreaking is how it functions in environments with zero infrastructure—no power supply, no connectivity, and corrosive saltwater everywhere. By developing density-based crowd counting AI models that run efficiently on edge devices, they've created a system that can count hundreds of fish with 96% accuracy in clear water and 86% accuracy in muddy conditions.
Perhaps most fascinating is their development process. Unable to collect sufficient real-world training data underwater, the team developed a sophisticated Unity-based simulation that generates realistic fish behavior under various conditions. This simulator provided 65% of their training data, complemented by manual observation from divers who documented actual fish behavior at different depths and feeding stages. The result is an AI system that not only counts fish but can potentially detect hunger levels, health issues, and optimize feeding schedules.
This CES 2024 Innovation Award-winning technology demonstrates how Edge AI can transform traditional industries without requiring massive infrastructure investments. By bringing intelligence directly to the point of data collection, even in the most challenging environments, we're witnessing the beginning of a new era in sustainable food production. Whether you're involved in agriculture, environmental monitoring, or any field requiring intelligent sensing in harsh conditions, the lessons from this underwater AI revolution could transform how you approach your next challenge.
Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org
Chapters
1. Counting What Counts: How Edge AI is Saving Japan's Seafood Industry (00:00:00)
2. Introduction and Austin Conference Recap (00:00:58)
3. Introducing Aquaculture Challenge with SoftBank (00:03:32)
4. Japan's Fishing Industry Problems (00:11:13)
5. SoftBank's Fish Cage Research Approach (00:18:59)
6. Computer Graphics Simulation for Fish Tracking (00:27:38)
7. AI Model Development and Implementation (00:36:05)
8. Hardware Challenges in Marine Environments (00:42:14)
9. Future Applications and Q&A Discussion (00:48:37)
37 episodes
All episodes
×Welcome to Player FM!
Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.