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Included File Formats
This model is provided in 14 widely supported formats, ensuring maximum compatibility:
• - FBX (.fbx) – Standard format for most 3D software and pipelines
• - OBJ + MTL (.obj, .mtl) – Wavefront format, widely used and compatible
• - STL (.stl) – Exported mesh geometry; may be suitable for 3D printing with adjustments
• - STEP (.step, .stp) – CAD format using NURBS surfaces
• - IGES (.iges, .igs) – Common format for CAD/CAM and engineering workflows (NURBS)
• - SAT (.sat) – ACIS solid model format (NURBS)
• - DAE (.dae) – Collada format for 3D applications and animations
• - glTF (.glb) – Modern, lightweight format for web, AR, and real-time engines
• - 3DS (.3ds) – Legacy format with broad software support
• - 3ds Max (.max) – Provided for 3ds Max users
• - Blender (.blend) – Provided for Blender users
• - SketchUp (.skp) – Compatible with all SketchUp versions
• - AutoCAD (.dwg) – Suitable for technical and architectural workflows
• - Rhino (.3dm) – Provided for Rhino users
Model Info
• - All files are checked and tested for integrity and correct content
• - Geometry uses real-world scale; model resolution varies depending on the product (high or low poly)
• • - Scene setup and mesh structure may vary depending on model complexity
• - Rendered using Luxion KeyShot
• - Affordable price with professional detailing
Buy with confidence. Quality and compatibility guaranteed.
If you have any questions about the file formats, feel free to send us a message — we're happy to assist you!
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SURF3D
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More Information About 3D Model :
An IoT Hydroponic Plant Auto Control Water Drip Irrigation System represents a sophisticated technological integration designed for the autonomous management of nutrient and water delivery in soil-less cultivation environments. This system leverages the principles of the Internet of Things (IoT) to monitor, control, and optimize the crucial parameters of hydroponic plant growth, specifically focusing on precise water and nutrient drip irrigation. Its primary objective is to enhance resource efficiency, improve plant health, and maximize yields through data-driven automation, minimizing manual intervention.
Core Components and Architecture:
The system is fundamentally composed of several interconnected elements that facilitate its automated operation: