For an industry that started 12,000 years ago, there is a lot of unpredictability and imprecision in agriculture. To be predictable and precise, we need to align our actions with insights gathered from data. Last week at Microsoft Ignite, we launched the preview of Azure FarmBeats, a purpose-built, industry-specific solution accelerator built on top of Azure to enable actionable insights from data.
With AgriTechnica 2019 starting today, more than 450,000 attendees from 130 countries are gathering to experience innovations in the global agriculture industry. We wanted to take this opportunity to share more details about Azure FarmBeats.
Azure FarmBeats is a business-to-business offering available in Azure Marketplace. It enables aggregation of agriculture datasets across providers and generation of actionable insights by building artificial intelligence (AI) or machine learning (ML) models based on fused datasets. So, agribusinesses can focus on their core value-add rather than the undifferentiated heavy lifting of data engineering.
With the preview of Azure FarmBeats you can:
- Assess farm health using vegetation index and water index based on satellite imagery.
- Get recommendations on how many sensors to use and where to place them.
- Track farm conditions by visualizing ground data collected by sensors from various vendors.
- Scout farms using drone imagery from various vendors.
- Get soil moisture maps based on the fusion of satellite and sensor data.
- Gain actionable insights by building AI or ML models on top of fused datasets.
- Build or augment your digital agriculture solution by providing farm health advisories.
As an example, here is how a farm populated with data appears in Azure FarmBeats:
For a real-world example of how it works, take a look at our partnership with the United States Department of Agriculture (USDA). In a pilot, USDA is using Azure FarmBeats to collect data from multiple sources, such as sensors, drones, and satellites, and feeding it into cloud-based AI models to get a detailed picture of conditions on the farm.
Azure FarmBeats includes the following components:
- Datahub: An API layer that enables aggregation, normalization, and contextualization of various agriculture datasets across providers. You can leverage the following data providers:
o Sensor: Davis Instruments, Teralytic
o Drone imagery: DJI, EarthSense, senseFly, SlantRange
Coming soon: DTN, Pessl
Datahub is designed as an API platform and we are working with many more providers – sensor, satellite, drone, weather, farm equipment – to integrate with FarmBeats, so you have more choice while building your solution.
- Accelerator: A sample solution, built on top of Datahub, that jumpstarts your user interface (UI) and model development. This web application leverages APIs to demonstrate visualization of ingested sensor data as charts and visualization of model output as maps. For example, you can use this to quickly create a farm and easily get a vegetation index map or a sensor placement map for that farm.
While this preview is the culmination of years of research work and working closely with more than a dozen agriculture majors, it is just the beginning. It would not have been possible without the early feedback and validation from these organizations, and we take this opportunity to extend our sincere gratitude.
Azure FarmBeats is offered at no additional charge and you pay only for the Azure resources you use. You can get started by installing it from Azure Marketplace in Azure Portal. In addition, you can:
- Get and stay informed with our documentation.
- Seek help by posting a question on our support forum.
- Provide feedback by posting or voting for an idea on our feedback forum.
With Azure FarmBeats preview, we are pioneering a cloud platform to empower every person and every organization in agriculture to achieve more, by harnessing the power of IoT, cloud, and AI. We are delighted to have you with us on this global transformational journey and look forward to your feedback on the preview.
This article was written by Shon Shah and originally appeared in Microsoft Azure Announcement Blog
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