Nquiringminds are developing a suite of agritech sensors that are capable of gathering key harvest data metrics. And deploying state of the art machine learning to drive efficiency, energy and environmental gains. Covering all the aspects of a crop life cycle: sowing, growing, harvesting, drying, storage and delivery.

Sensor Requirements:

• Harsh environment – outside in the field, wind and rains resistant as well as in an industrial drier at temperatures up to 100oC
• Robust transmission – both long range, weak field-to-farm and short noisy industrial deployments.
• Seasonal deployments – with sensors required to operate for up to one year without battery change.

Interactive cloud based visualizations, analytics and control systems, will drive efficiency, reduce energy consumption and decrease the environmental impact of the harvest.

The AgriSense project will automate the data collection through sensors and provide the tools to allow scarce expert knowledge to be shared across multiple simultaneous harvests through a mixture or efficient remote expert intervention, and transfer of “expert knowledge” into honed machine learning systems.

The solution’s sensor hubs are be based on the ST 32 EuroCPS platform. Which possesses the right combination of low power, robust environmental performance and flexible integration options.