Information and Communication Technologies and Robotics for Sustainable Agriculture

Project No: 16178

Project dates:
1 Mar 2015 - 31 Aug 2016

Veselin Pizurica, waylay (Belgium)

Collaborating Institutions:

Claus Sørensen, Aarhus University (Denmark)

Project website
Full report


Proposal Summary

The purpose of FERIA is to develop, test and exploit a probabilistic mobile app assessing trafficability/workability estimates and predictions for agricultural field operations. This system will have great influence in organic farming due to many field operations especially for mechanical weeding, as chemical herbicides are forbidden.

Main Results

This project has provided a prototype consisting of an android application that can connect to the waylay platform. The device can send any sensor information, including GPS coordinates, allowing use of a geoFancing sensor. For this pilot, two templates have been designed: one where we fetch the data directly from the cloud API of the sensors SynField and one where waylay first sends the data to the orion broker (implemented as the actuator) and later fetch the same data using the orion as a sensor. Functionality of two templates is the same – provide advice about workability and trafficability of the field.
Also, the project has produced results of collected data showing a significant system performance in terms tillage/seeding trafficability/workability, based on soil moisture prediction and weather forcasting. For example, the systems seems able to predict suitable seeding times outperforming manual predictions. Additional, given that farmer’s decision on scheduling seeding operations is affected by stochastic factors such as soil-water content and weather information related to air temperature and precipitation, a scheduling model for seeding/tillage operations under stochastic conditions with on-line information of soil-water content, temperature,
and precipitation was developed and tested. The results show that the optimal policy adopts well to different conditions in the field (the optimal policy was used in three scenarios with different weather information) and finds optimal tillage decisions maximizing satisfaction level for workability, trafficability, and completion criteria..Moreover, a sensitivity analysis revealed that the risk attitude of the farmer for workability, trafficability, and completion criteria can affect the optimal scheduling of tillage operations in the field.


The developed models for the field readiness scheduling of field operations like seeding can be further implemented and integrated into a suitabke user-interface. This further development and implementation can be carried out by software developers like waylay. Additional, based on the current stage of the field readiness indicator system further adaptions and testing will be pursued by AU in concurrent project activities.