Hey community, you might have noticed that we have been upgrading our monthly campaign Seeed Project of the Month as a thematic event this year if you’re following us on LinkedIn. At the end of each month, we will select our 4 favorite projects from the community such as Hackster, Hackaday, Instructables, etc. The candidate projects will be showcased at the campaign and invite community members to vote out a winning project, which will be awarded as the Project of the Month.
Excited already? No! We also prepare prizes and benefits for community members who make their projects into the campaign! The winner can get a $200 or more coupon for the next project promotion, and we will select two lucky voters to get a $30 coupon for exploration.
To encourage you to share your innovative projects, we are always calling for candidate projects to run the thematic Project of the Month campaign! All you need to do is publish your Seeed-powered projects and let us know. It can be an already-built project that you shared on other platforms (Hackaday, your websites, Instructables, and more). It can also be a new project that you are working on. Be creative and please include at least one Seeed product. (Spoiler. We like projects powered by reTerminal, reComputer, and SenseCAP series products. 😊)
Seeed Project of the Month – Home Assistant (February)
Home Assistant empowers makers to consolidate control over a diverse array of smart devices and systems within their homes. Its robust feature set facilitates seamless integration, automation, and customization across various tasks such as smart home control, energy monitoring, security management, and entertainment control.
For the Seeed thematic project of the month campaign in February, themed “Home Assistant,” we’ve observed several members crafting their personalized automation routines, leveraging voice commands for device control, monitoring energy usage, enhancing security with alerts and notifications, and even tracking environmental conditions. Now, let’s delve into these standout projects:
Hello February! Seeed’s Thematic Project of the Month for February is now open for submissions! Whether you’re just starting to prepare for your smart home project or looking to upgrade your automation system, we are calling for your Home Assistant projects.
- DIY 8 Channel Home Automation using Home Assistant by techiesms
- Integrating Sensecap S2103 and displaying data on reTerminal by Saudin Dizdarevic
- Comovis by Nayel Khouatra
- 4 Node Home-Automation System Using Smallest ESP32 by Technolab creation
As usual, we will select two lucky voters to win a Seeed $30 coupon. Moreover, each candidate will receive a $50 coupon, and the winner will receive an additional $100. The winner announced on February 5th.
Seeed Project of the Month – Machine Learning (January)
Machine learning lets computers learn from data and make decisions or predictions without being explicitly programmed. It’s applicable in various industries, from improving healthcare with predictive diagnostics to detecting pollution to protect the environment, optimizing retail supply chains, and advancing autonomous vehicle technology. Machine learning helps to enhance our lives, and with compact machine learning modules, it’s become accessible for everyone to explore and innovate in our daily routines.
🔥 Riding this wave, we are excited to share the January—Thematic Project of Month Campaign. We’ve spotlighted four captivating ML projects from our community. Thanks to everyone for making this community a more splendid one. So now, we’d love to celebrate it!
Now, time to meet the 4 amazing projects that we featured as Project of Month – Machine Learning:
Winner: Garbage Detection using Drone and Computer Vision by Timothy Malche
This project introduces a pioneering solution utilizing drone technology for garbage monitoring. This system allows for comprehensive inspection of a smart city remotely, ensuring the timely and effective management of garbage. The integration of this project into existing smart city waste management systems is seamless, highlighting the adaptability.
Candidate Project: Superman Detection and Visualization by David Tischler, uses the Seeed Grove Vision AI Module to build a computer vision model and perform inferencing, with the results captured and sent to a cloud dashboard.
Candidate Project: NMCS: No More Coffee Spills by Sashrika Das, which is a device that uses its hearing and seeing skills to make sure that your coffee doesn’t spill when making your energy booster.
That’s it for this entry. As always, we can’t wait to see what you make. Shoot us a tweet @seeedstudio, or let us know on LinkedIn, Discord, or publish your project on our Project Hub on Hackster. Please be safe out there, be kind to one another, and we’ll see you soon with even more exciting news!