Objectives of the Product

AgriTrack Full DSS Stack is an innovative product on the frontier of Farm Management Systems. It is an advanced Full Decision Support System able to combine modeling and remote sensing historical information to diagnose the hot spots of vegetative stress highlighted by remote sensing.  The ambition is to overcome the two main problems of agricultural DSS:

• information overload;
• lack of spatial information and practical prescription.

The core concept of this product is the capacity to integrate traditional DSS with spatialization. In fact, Satellite data collected and elaborated by AgriTech platforms are usually able to identify general issues (such as areas with reduced vigor within each field) but cannot provide precise diagnosis of the seriousness of the vegetation vigour issues and information on its possible causes. On the other hand, traditional DSS can provide specific information on single issues, such as field water or nutrients needs, pest risks etc., which usually refers to the whole field, without differentiating between different areas of the field. With the Full DSS, all the information can be integrated, providing tempestive feedback on what is happening in the field and where it is happening and why, giving some agronomic advice.

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Customers and their Needs

AgriTrack Full DSS Stack can directly support a wide range of stakeholders with direct and indirect benefits. The targeted customers are:

• Farmers, which could improve farm profitability through optimized use of inputs and reduce environmental impact.
• Farmers’ association, which could collect useful data and information;
• Cooperatives, which could monitor multiple fields and timely identify hot spots. Consortia, which could obtain an easy-to-use tool for providing agronomic support to numerous farms.

Faced with an ever-changing environmental and economic scenario, farmers, consultants, and other actor of the agronomic sector find themselves increasingly in need to identify critical areas within the field and plan new and immediate intervention action remotely and timely. On this regard, AgriTrack Full DSS stack can respond to their need to take agronomic decision making based on reliable and spatialised information, improve the monitoring and data collection from several fields and farms, be able to obtain tangible and reported results on farm’s agronomical performance. This is completed by the possibility provided to users to have spatial and detailed alert information and its causes. Lastly, from the interviews carried on with target users, the urgence to be trained and supported in the use of innovative and technological tools strongly emerged.

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Target customers/users countries

• Italy
• Spain

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Product description

AgriTrack Full DSS Stack is a functionality to be added to an existing cloud based FMIS. It will use all existing and new model outputs and sensed data (e.g., satellite, in-situ sensors) to obtain a probabilistic diagnosis of the agronomic issues affecting specific areas within the identified critical field.

This will be achieved testing different Machine Learning and data-fusion approaches adopted as predictive tools within the large dataset that has been created by Agricolus in several years of smart farming experience.  AgriTrack Full DSS Stack consists of two modules. The first is a web application called Visualization Module, that displays sets of geospatial information and alerts, being the main interface and interaction point with the user. The second is the Computational Module, which produces such information and alerts combining different data sources into specific algorithms.

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Added value

AgriTrack Full DSS is a new solution which brings four core innovations:

1. Critical area diagnosis from interpretation of satellite images:
   The Full DSS is the only solution able to automatically detect real vigour issues within the field, inform the users and provide information about its causes.
2. Spatial model outputs on specific issues at sub-field level:
   The Full DSS is able to provide information about field’s criticalities such as nutrient and water needs, pest risks, thermal stress, waterlogging and heat waves. Moreover, information is elaborated differentiating between field specific areas, allowing a precise management of the issues.
3. Integration of several data sources into a single information:
    The Full DSS models will integrate information from a range of different sources (satellite, sensors, user data etc.) to provide the simplest and most useful information to the user, which will no longer have to retrieve data from different sources.
4. Sharing and aggregation of information at different levels:
   The Full DSS allows data exchange between hundreds of farms fostering insights and communication at a large scale; Full DSS makes possible real-time and forecast data based reporting among connected farms and other stakeholders, and agronomic management of the entire ecosystem with activity and support in optimizing agronomic practices.

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Current Status

The project activities are proceeding well. The team successfully conducted the user engagement activities foreseen, through a survey and a set of interviews with targeted users. The feedbacks collected have been used to derive the user needs, the user requirements and the system requirements which will be used for the design and development of the service in the next months. Moreover, the adoption of a first version of the mockup during the interviews allowed designers to gather useful insight on the usability side, which will be used to further improve the design of the solution. Moreover, data collection activities have also started, with the installation of the sensors in the fields and regular crop scouting activities on winter cereals.