We believe that the growth of IoT sensors and data in Agriculture is an opportunity for AI enabled precision farming, to optimize farm operations and increase yields.
- Trevor Bloch, VROC CEO
It has been estimated, by McKinsey, that farmers may be able to improve yield between 15 and 20 percent using IoT technologies. As the volume of data being produced by farms continues to increase, this data can be used to help farmers make critical decisions, confirm assumptions, and predict future conditions for more accurate planning, such as planting dates, crop selection, accurate distribution of fertilizers and treatments for disease and pests.Book a demo
Produce AI models in minutes without coding or programmingRead More
With model confidence and accuracy averaging 99%, users have confidence to make decisionsRead more
Built to integrated with legacy systems and equipment agnostic so you can obtain insights from your dataRead more
Optimize your team with anywhere, anytime access to real time monitoring and predictionsRead more
Optimize farming practices and operations using IoT data. Benefit from real time monitoring across the whole network, along with advanced analytics predictions for improved decision making.
A changing climate and global food security concerns make the long-term sustainability of the agricultural industry a high priority. Using data to monitor real-time conditions and predict future conditions and their impact, such as the weather, and being agile to adapt operating practices to ensure optimal harvests, is critical to building a resilient and sustainable industry.
Use real time and historic farm and industry data to assist with compensation modelling and forecasting to help provide a decision support tool for farm operators
Collect real time and historic data from critical machinery and predict future equipment conditions for predictive maintenance. These essential insights can help farm operators order spares to remote locations, so they arrive in-time, reducing downtime and high freight costs. Ai predictions can also determine accurate root causes of failure so that maintenance is carried out correctly first time.
Client supply of historical data and set-up of real-time streaming
VROC Data ingestion and real-time data streaming connection
Client training and model generation
Models in Production. Client starts delivering business value
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Ready to embark on a pilot project or roll-out the innovation enterprise wide? Perhaps you need assistance integrating your systems or accessing your data? We have a solution to help you as you progress through your digital transformation.
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DataHUB4.0 is our enterprise data historian solution, OPUS is our Auto AI platform and OASIS is our remote control solution for Smart Cities and Facilities.
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Ready to embark on a pilot project or roll-out AI innovation enterprise wide? Perhaps you need assistance integrating your systems or storing your big data? Whatever the situation, we are ready to help you on your digital transformation.
The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
Learn more about DataHUB4.0, VROC's distributed enterprise data historian. Complete the form form to download the product sheet.
Discover how you can connect disparate systems and smart innovations in one platform, and remotely control your smart facility. Complete the form to download the product sheet.
'OPUS, an artistic work, especially on a large scale'
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