SentiV

With SentiV, keep an eye on your crops

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SentiV is a scouting robot that highlights the variability within field crops plots and detects potential threats to crops. Being in contact with the ground, we are talking about near sensing.

SentiV is dedicated to agricultural professionals: it is a tool to improve practices for farmers, a farm advisory solution for coops, and an indispensable element to optimize phenotyping on experimental plots.

The information gathered is highlighted within variability maps, allowing farmers to pilot daily, with precision, their exploitations by modulating inputs on the plots.

We develop SentiV for the people of the agricultural sector. Our goals are for a better farming profitability (input savings, improved yields and crop quality), a good quality of life for farmers (time saving and better working comfort), and environmental preservation (input reduction and less soil compaction).

Autonomous navigation
Once in place, SentiV detects where it has been setup and moves without an operator nearby. The plot is surveyed and analyzed in its entirety, covering up to 20 hectares per day.
Scouting - Harvesting data
The robot has two cameras that scan over and under the foliage. With time we plan to add other sensors according to the types of data to be detected.
Modularity
In order to adapt to the type of plants studied and to follow the growth of crops, we have made SentiV a modular robot: width, height, mode of motion are adjustable.
Accuracy of readings
Unlike existing remote sensing solutions, images captured by the SentiV sensor provide more details than can be seen by a human eye on the plot.
Besides, the robot also scans under the crop canopy (soil and under leaves).
Preservation of crops
A robot that does not damage crops was the leitmotif that guided the development of SentiV. In addition to its lightness (15kg), SentiV moves thanks to a unique and innovative wheel system to step over vegetation.
Obtaining qualified information
Collected data are analyzed by artificial intelligence algorithms allowing to identify the presence of biological threats: weeds, diseases, and pests (invertebrates, birds, mammals).