Short name: 4WINE DSS
Long name: Decision support system for sustainable viticulture
Company: Primo Principio S.c.a.r.l.
Call Stage 1: F4Fp-SME-COD210316 (see call details)
Proposal number: F4Fp-SME-COD210316-05
SUMMARY REMARKS & TESTBEDS
Characterized by a high-risk of fungine pathologies, viticulture largely uses pesticides and chemical treatments to defend cultivations. SmartAgriculture may offer a promising horizon in order to support a sustainable approach to manage pathologies. However, to achieve this result raw data from sensors are not enough: complex data analysis is needed. This is what a Decision-Support-System (DSS) for agriculture does where accuracy and timing are essential. For each specific crop and pathology the DSS algorithms are able to simulate in real-time the infection stage and the associated evolution mechanics. This is possible thanks to trainable forecast mathematical models which combine data from IoT sensors, weather forecast data and epidemiological data gathered from the fields with AI techniques in order to train the model on a specific “terroir”. The objective of the experiment in Stage1 is to assess the technical conditions, resources and costs ( computational, bandwidth, energy and internet access resources) needed for running (trained) DSS algorithms for a specific pathology on a single parcel. Stage2 wants to scale-up the setup involving farmers in the Prosecco area; the goal is to measure how much the needed resources (identified at Stage1) can be sustainable and profitable if scaled to an entire production area.