Development achievements in AR, VR, xR, and MR for manufacturing, construction, and healthcare.

basic information

【Supported Environments】Unity, iOS, Android, Meta Quest 3, various AR/MR glasses 【Supported Technologies】AR, VR, xR, MR, 3D model display, point cloud processing, photogrammetry, image recognition, machine learning, OpenCV, ArUco markers, QR code recognition, voice recognition 【Supported Data Formats】STL, PLY, FBX, OBJ, etc. 【Supported Features】Hands-free work support, recognition of parts and three-dimensional objects, VR tours of buildings and AR verification, plant growth assessment, display systems for medical and research purposes, development of alternative methods when existing SDKs are not supported 【Provision Formats】Contract development, PoC, research and development support, improvement of existing systems. Designed and developed according to the device, accuracy, and usage environment for each project.

Price information

The price for custom development varies depending on the requirements for each project, the devices involved, the scope of development, recognition accuracy, and verification content. First, we will confirm your requests and provide individual estimates based on the stages such as PoC, prototype, and full development.

Delivery Time

Applications/Examples of results

【Applications】Support for hands-free work in manufacturing, parts recognition and assembly training, VR tours of buildings and AR exterior inspections, plant growth assessment, MR displays in medical and research fields, and demonstrations for exhibitions and training, among others. 【Examples of Achievements】Plant growth assessment using iPhone and point cloud analysis, parts model number verification using AR glasses, VR tours of pre-construction homes and AR exterior views, MR displays for assisting artificial joint surgeries, assembly support using unique 3D markers, and xR system development using Meta Quest 3 and OpenCV.

Detailed information

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  This is a case where images and depth information captured with an iPhone are converted into point clouds, and a machine learning model is used to assess the growth condition of plants. The size of tomato seedlings and the condition of their branches and leaves were visualized and used for determining and recording which plants to thin. By combining photogrammetry, point cloud processing, and image analysis, this can be applied to tasks that continuously monitor the shape and changes of objects in agriculture, forestry, equipment inspection, and more.

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  This is an example of an AR support system that allows workers on the manufacturing floor to check part information and work procedures without using their hands. Voice commands are used on smart glasses to scan QR codes of parts and retrieve information from the server. By combining modifications to the Android OS, voice recognition, camera control, and QR recognition, it supports the efficiency of verification tasks and reduces errors in the assembly process.

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  This is an example of building an xR system using ArUco markers and OpenCV in an environment where Meta Quest 3 does not support Vuforia. By combining Unity, Meta SDK, and OpenCV, we were able to accommodate ultra-small marker recognition and accuracy verification against obstacles. Even when existing SDKs are not available, the recognition method can be redesigned to suit the intended use and device characteristics, allowing for applications such as assembly support and exhibition demos.