Announcing Winners & Cool Projects of Seeed Studio Vision Challenge!
Discover the winners of the Seeed Studio Vision Challenge! After three thrilling months, we reveal the top projects using Grove Vision AI V2 Modules and XIAO ESP32C3 units. Explore innovative AI Computer Vision solutions in automation, conversation, home security, smart assistants, music composition, smart agriculture, and more.
Hello, community!
After three exciting months, the Seeed Studio Vision Challenge has come to a close. We are thrilled to announce the winners and share the outstanding projects that have emerged from this inspiring competition.
For those unfamiliar with the Vision Challenge, we distributed 100 Grove Vision AI V2 Modules + XIAO ESP32C3 units and received over 60 innovative project submissions. You can learn more about the Vision Challenge here.
3 Winners & Their Projects
It’s the most difficult decision of the year for us to select only 3 winners (that’s why it took way longer than we expected at the first place). But we’re super happy to share our top 3 picks! Without further ado, big congrats to the following 3 winners and their awesome tinyML projects based on Grove Vision AI Module V2:
🎵 Skulls: Composing Music with Computer Vision and a Custom YOLO5 AI Model
- Creator: Joshua Curry at Lucid Beaming
- Project Link
An innovative project that uses computer vision and a custom YOLO5 AI model to compose music. By analyzing visual inputs, this project generates unique musical compositions, merging the worlds of AI and art in a fascinating way.
🤖️ Assistant Based on Grove Vision AI Module V2
- Creator: Jaime Andres Rincon Arango
- Project Link
This project integrates the Grove Vision AI Module V2 to create a smart assistant that can recognize and respond to various visual cues. It’s an impressive demonstration of how AI can enhance everyday tasks and improve efficiency.
🔔 PIR Doorbell with XIAO ESP32C3 and Grove Vision AI Module V2
- Creator: Team Professional
- Project Link
This project showcases a low-power doorbell camera that utilizes a PIR sensor to detect human presence. The XIAO ESP32C3 activates the Grove Vision AI Module V2 for person classification, sending a WhatsApp message to the tenant if a stranger is detected. A brilliant solution for home security!
Honorable Mentions
In addition to our winners, we received many exceptional entries. Here are some of the standout projects that deserve special recognition:
🏋️ Pose Training by TAKESHI IKEUCHI: An AI-based tool to assist with pose training, perfect for fitness and rehabilitation.
🐦Dual AI Camera for Monitoring Hummingbirds by Ralph Yamamoto: Dual AI Camera using Grove Vision AI V2 and Xiao ESP32S3 Sense to detect and capture images of hummingbirds.
🐶 Pet Detector with Grove Vision AI V2 by Bruno Santos: A smart system to detect and monitor pets using the Grove Vision AI V2.
🤖️ Face Controlled Robot by Timothy Lovett (Cosmic Bee): A robot that utilizes facial recognition for control, showcasing the potential of AI in robotics.
🐦 The Internet of Birds: Using IoT to Determine Bird Types by Saudin Dizdarevic: A fascinating project that uses IoT and AI to identify bird species, contributing to ecological research.
🔥 Fire Extinguishing Robot – Grove Vision AI Module V2 by SekolahRobot: An autonomous robot designed to detect and extinguish fires, enhancing safety in various environments.
🏊 Solar Powered Pool Alert System by Timothy Lovett (Cosmic Bee): A solar-powered system to monitor pool safety, utilizing AI to detect potential hazards.
👔 Watching Washers w/ Grove Vision AI Module V2 by Matevž Zorec and fb03: A project focused on monitoring washing machines, ensuring efficient operation and maintenance.
🐑 Flame-Free Farm by Rifqi Abdillah: An innovative farming solution to prevent fires, and count goats using computer vision, enhancing agricultural safety.
📸️ Step Guard 3.0 by Roni Bandini: This project incorporates the Grove Vision AI Module V2 for AI-based detection, reporting activities with BLE, and triggering deterrent actions such as dog barks and loud sounds. The system uses an outdoor ESP32S3 sensor connected to an indoor Linux/Python Unihiker, sending notifications and escalating sounds when loitering is detected.
⚡️ Eletect by Abhinav Krishna, and Amritha M: An intelligent system for detecting electrical faults, improving safety and maintenance.
🖨️ $16 AI 3D Print Spaghetti Detection (feat. Home Assistant) by Spence Stoltzfus: A practical tool to detect 3D printing errors, integrating with Home Assistant for smart home setups.
Claim Your Prizes
We will be contacting the 3 winners via the email addresses provided during project submission. Each winner will receive a $300 coupon for Seeed products and the opportunity to participate in the SenseCAP Watcher Alpha Test. Additionally, we will select a few exceptional projects for the SenseCAP Watcher Alpha Test and contact the creators via email too.
Keep an eye on your inbox and promptly respond to claim your prizes. Thank you all for your enthusiastic participation in the Vision Challenge!
Stay tuned for more exciting opportunities and keep innovating!
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