Since Elon Musk bought and changed Twitter to X, we feel that the title of X Turtle doesn’t have the same connotation as the original title. As such, we choose to keep the Twitter name. This project takes inspiration from the Tweeting Tree. We are working closely with Arribada.org to deploy their cost-effective Horizon Artic GPS tags to be applied. Details of this project can be seen on the main webpage.
The ESP32Cam module presents a cost-effective solution for creating wildlife cameras and smart AI cameras. At its core, the module combines a powerful ESP32 chip with an integrated OV2640 camera module and an SD card slot, allowing for the capture and storage of high-quality images and videos in various environments. This compact and affordable device, priced at under 20 USD (and even cheaper when bought in bulk), opens up numerous possibilities for both researchers and hobbyists.
One of the standout features of the ESP32Cam is its ability to run lightweight AI algorithms, such as MobileNet, which enables real-time object detection and classification. This capability transforms the module into a versatile tool for a wide range of applications, from monitoring wildlife in their natural habitats to creating smart AI-driven security systems. The module's small size and low power consumption make it an ideal choice for deployment in remote or challenging environments where traditional camera systems might be impractical.
For wildlife observation, the ESP32Cam can be used to set up automated monitoring stations that capture images and videos of animals without human intervention. These stations can be programmed to detect specific species or behaviors, providing valuable data for ecological studies and conservation efforts. The ability to process data on-board means that only relevant images are stored, reducing the need for extensive post-processing and analysis.
Moreover, the ESP32Cam's affordability and ease of use make it accessible to a broader audience. Hobbyists can experiment with AI and computer vision technologies, creating innovative projects and gaining hands-on experience with cutting-edge tools. The extensive community support and wealth of online resources further enhance the learning experience, making it easier for users to get started and troubleshoot any issues that arise.
In summary, the ESP32Cam module is a powerful and versatile solution for creating wildlife cameras and smart AI cameras. Its combination of high-quality imaging, real-time object detection, and affordability makes it an excellent choice for anyone looking to explore the potential of AI and computer vision in their projects.
Seeedstudio Grove Vision AI Module V2
This is an offshoot project from the main SmartCam project. Instead of using ESP32Cam, we used the AI camera module from Seeedstudio. The Seeedstudio Grove Vision AI Module V2 is an advanced AI and computer vision module designed for seamless integration into a wide array of projects. Equipped with a powerful AI chip and a high-resolution camera, this module excels in real-time object detection, image classification, and an assortment of other AI functionalities. Its capabilities allow for the development of sophisticated applications in various domains.
One of the standout features of the Seeedstudio Grove Vision AI Module V2 is its versatility. Whether you're building smart home devices, enhancing security systems, or engaging in environmental monitoring, this module serves as a robust foundation. The ease of integration and compact size make it an excellent choice for both hobbyists and professionals looking to implement AI-driven solutions without the need for extensive technical expertise.
Moreover, the module is designed with cost-effectiveness in mind. For a relatively low investment, users can leverage advanced AI and computer vision technologies that were once accessible only to large organizations with significant resources. This democratization of technology enables more individuals and smaller teams to innovate and create impactful projects.
In addition to its practical applications, the Seeedstudio Grove Vision AI Module V2 boasts a user-friendly interface and comprehensive documentation. This ensures that users can quickly get up to speed and start developing their projects without unnecessary delays. The support from the Seeedstudio community further enhances the experience, providing a valuable resource for troubleshooting and inspiration.
Overall, the Seeedstudio Grove Vision AI Module V2 represents a significant advancement in the field of AI and computer vision. Its combination of power, versatility, and affordability makes it a compelling choice for anyone looking to explore the potential of AI in their projects.
This is also an AI-assisted project. We will track the hatchlings' movement patterns using a night vision camera, artificial lights, and several AI tools. Currently, we are using DeepLabCut from the Matthis group and IDTrackerai.
Monitoring turtle movement is crucial for understanding their behavior, migration patterns, and habitat use. By tracking their movements, researchers can gain valuable insights into the turtles' life cycles, feeding habits, and interactions with their environment. This information is essential for developing effective conservation strategies and ensuring the long-term survival of these species. The use of advanced technologies such as GPS tracking and AI-assisted analysis allows for more precise and detailed monitoring, enhancing our ability to protect and preserve turtle populations.