Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.

This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices.

Korean Cattle 3D Reconstruction from Multi-View 3D-Camera System in Real Environment.

The rapid evolution of 3D technology in recent years has brought about significant change in the field of agriculture, including precision livestock management. From 3D geometry information, the weight and characteristics of body parts of Korean cattle can be analyzed to improve cow growth. In this paper, a system of cameras is built to synchronously capture 3D data and then reconstruct a 3D mesh representation. In general, to reconstruct non-rigid objects, a system of cameras is synchronized and calibrated, and then the data of each camera are transformed to global coordinates. However, when reconstructing cattle in a real environment, difficulties including fences and the vibration of cameras can lead to the failure of the process of reconstruction. A new scheme is proposed that automatically removes environmental fences and noise. An optimization method is proposed that interweaves camera pose updates, and the distances between the camera pose and the initial camera position are added as part of the objective function. The difference between the camera's point clouds to the mesh output is reduced from 7.5 mm to 5.5 mm. The experimental results showed that our scheme can automatically generate a high-quality mesh in a real environment. This scheme provides data that can be used for other research on Korean cattle.

Laparoendoscopic Single-Site Pyeloplasty Using Additional 2 mm Instruments: A Comparison with Conventional Laparoscopic Pyeloplasty.

PURPOSE: Despite a recent surge in the performance of laparoendoscopic single-site surgery (LESS), concerns remain about performing LESS pyeloplasty (LESS-P) because of the technical difficulty in suturing. We report our techniques and initial experiences with LESS-P using additional needlescopic instruments and compare the results with conventional laparoscopic pyeloplasty (CL-P). MATERIALS AND METHODS: Nine patients undergoing LESS-P were matched 2:1 with regard to age and side of surgery to a previous cohort of 18 patients who underwent CL-P. In both groups, the operating procedures were performed equally except for the number of access points. In the LESS-P group, we made a single 2 cm incision at the umbilicus and used a homemade port. We also used additional 2 mm needlescopic instruments at the subcostal area to facilitate suturing and the ureteral stenting. RESULTS: The preoperative characteristics were comparable in both groups. Postoperatively, no significant differences were noted between the LESS-P and CL-P cases in regard to length of stay, estimated blood loss, analgesics required, and complications. But, LESS-P was associated with a shorter operative time (252.2 vs. 309.7 minutes, p=0.044) and less pain on postoperative day one (numeric rating scale 3.7 vs. 5.6, p=0.024). The success rate was 94% with CL-P (median, 23 months) and 100% with LESS-P (median, 14 months). CONCLUSIONS: Our initial experiences suggest that LESS-P is a feasible and safe procedure. The use of additional 2 mm instruments can help to overcome the difficulties associated with LESS surgery.