Best New Product 2024: SKIM Turf Management at the PGA Show in Orlando

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Participation in the prestigious PGA Show in Orlando brought OPTIDATA a fantastic achievement: the Best New Product 2024 Award! The event took place at the Orange County Convention Center in Orlando between the 24th-26th January, 2024.

This distinction was awarded by the PGA SHOW professionals and golf product buyers, recognizing the exceptional quality and innovation offered in the award-winning product, SKIM Turf Management. Receiving this esteemed award further motivates Optidata to continue providing top-notch turf management solutions to the golf industry, as well as expand the service to other industries and sports fields.

The Evolution of SKIM Turf Management: Achievements and Research

Since 2002, OPTIDATA has specialized in software production. Three years ago, it began innovative research to create the SKIM Turf Management platform using AI, responding to the needs of the golf industry. SKIM Turf Management harnesses the power of artificial intelligence and image analysis from multispectral cameras, enabling golf course management to optimize decision-making both in precision and speed.

Working with turf scientists, OPTIDATA conducted extensive research, collecting data over three growth seasons across experimental turf fields and active golf courses. Over 33,000 satellite photos, 7,000 drone photos, 5,000 visual assessments, 4,500 in-situ tests and 24,000laboratory results enabled the construction of an advanced Artificial Intelligence System.

Breakthrough solutions in SKIM Turf Management

SKIM Turf Management allows you to positively impact the environment through precise management of turf areas while taking into consideration innovative technologies and data from present environmental factors.

- Multispectral satellite images access for the selected golf course(s) at any time;

- Multispectral image analysis, using waves invisible to the human eye, enables early recognition of the condition of turf areas throughout the entire course, especially allowing for the detection of anomalies.

- Artificial intelligence algorithms enable precise measurements and analyzes based on models developed by the R&D OPTIDATA department, which have a significant impact on the optimization of human and technical resources;

- Generative AI, through the Ask SKIM portal, is a source of extended knowledge for the user, which, for example, can advise on selecting treatment for specific turf species;

- The mobile application enables effective work and collaboration from anywhere, providing easy access to reports, tasks and visualisations of the golf course.

- The scalability of SKIM Turf Management in the Cloud allows the golf course to safely and effectively process large amounts of data.

Benefits of SKIM Turf Management: Precision, Savings and Automatic Measurements

SKIM Turf Management takes into account environmental factors such as the grass type, climate, weather and plant conditions in its calculations. These elements are crucial for effective and accurate management of turf areas.

With SKIM Turf Management, a golf course can implement best practices in the efficient use of fertilizers, water and pesticides as well as communication and HR management.  As a result, it leads up to 24% of the annual maintenance budget, according to USGA research.

By using data generated in SKIM Turf Management, the golf course Manager will obtain an automatic and intuitive interpretation of the results. These will be presented in the form of visual reports such as maps, charts, diagrams, graphics and lists, particularly helpful when making advantageous decisions.

Artificial intelligence models that process multispectral images enable the golf course Managers to create automatic monitoring and measurement of indicators while receiving results in close to real-time. By viewing them online the golf course manager can choose from a wide range of monitored indicators, such as vegetation indices (NDVI, PVR, NDRE), nutrients (N, P, K, Ca, Mg, Na), micronutrients (Zn, Cu, Mn).