Develop algorithms and services for location-based data analysis in turf management using high-precision GNSS.
Utilize AI-driven vision to analyze turf damage in real-time and provide predictive management solutions.
Automate complex and hazardous field tasks to enhance operational efficiency and reduce labor demands.
Optimize golf course maintenance by predicting turf fatigue and recovery times, distributing stress effectively, with AI-driven hole cup relocation recommendations, and real-time heatmap analysis of concentrated green damage.
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Measure and assess pitch mark damage, collect comprehensive deep learning datasets including size, depth, occurrence time, and distribution, and optimize repair paths with advanced robotic task scheduling for efficient maintenance.
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Maintaining a beautiful golf course involves overseeing a vast area,
requiring deep expertise and considerable human effort to keep it in pristine condition.
Due to the difficulty in managing the root causes of turf damage, maintenance becomes increasingly challenging,
and significant resources are required for repairs.
The labor-intensive course management market is directly linked to issues such as
rising labor costs, workforce shortages, aging populations, and an increase in safety incidents.
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