NURIA DE LAMA (ATOS)
SJAAK WOLFERT (WAGENINGEN UNIVERSITY)
As smart machines and sensors crop up on farms and farm data grow in quantity and scope, farming processes will become increasingly data-driven and data-enabled. Rapid developments in the Internet of Things and Cloud Computing are propelling the phenomenon of what is called Smart Farming. Data produced at the farm also becomes increasingly valuable in the rest of the value chain leading to new business models and consumer markets.
This session will explore the developments of data-driven food production, address and discuss technical and organizational issues that arise from these developments.
Part I. Global developments of Big Data in Agri-Food production
New technologies such as the Internet of Things and Cloud Computing are expected to leverage the current trend of Smart Farming, introducing more sensors, robots and artificial intelligence, encompassed by the phenomenon of Big Data.
This presentation will give a quick insight into the state-of-the-art of Big Data applications in Smart Farming and identify the related challenges that have to be addressed. It shows that the scope of Big Data applications in Smart Farming goes beyond the farm; it is influencing the entire food supply chain. Big data are being used to provide predictive insights in farming operations, drive real-time operational decisions, and redesign business processes for game-changing business models.
It is expected that Big Data will cause major shifts in roles and power relations among different players in current food supply chain networks. The landscape of stakeholders exhibits an interesting game between powerful tech companies, venture capitalists and often small startups and new entrants. At the same time there are several public institutions that publish open data, under the condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a continuum of two extreme scenarios: 1) closed, proprietary systems or 2) open, collaborative systems.
The development of data and application infrastructures (platforms and standards) and their institutional embedment will play a crucial role in the battle between these scenarios. A major challenge is therefore to cope with governance issues and define suitable business models for data sharing in different supply chain scenarios. (presentation)
Part II. DataBio: New Methods of Advanced Visualisation of Big Data for Agriculture
DataBio is a H2020 lighthouse project focusing on utilizing Big Data components and datasets to improve bioeconomy. It deploys state-of-the-art Big Data, Earth Observation, ICT technologies and existing partners’ infrastructure and solutions, linked together through the DataBio Platform. It is driven by the development, use and evaluation of 26 pilots covering agriculture (13), forestry (7) and fishery (6). By matching over 90 existing big data components to these pilots and integrating them in a systematic approach, the most common and high-impact pipelines of datasets and components emerge, to drive the DataBio platform development.
The demo will focus on: (a) 3D visualisation and analysis of agriculture and rural development data, and (b) new methods of analysis and geographical visualisation of Agriculture Linked Open Data (RDF). (presentation)
Part II. The Internet of Food and Farm 2020 – the case of Big Wine Optimization
Big Wine Optimization has deployed an IoT system based on 150 actuator/sensor nodes to monitor data from 5 vineyards and cellars concerning accurate weather conditions in real time, wine conditions (such as grape detection, phenological stages determination, and disease status characterization) and key cellar conditions, thereby demonstrating the potential benefits of these new cultivation methods. Big Wine Optimization:
- Optimizes wine production from the vineyard to the consumer.
- Reduces the use of chemicals for plant protection through a precise use of treatments in order to reduce resources, environmental impact, and efficiently protect grape
- Performs selective harvesting automatically and quickly in order to reduce the inspection time and achieve accurate results
- Monitors accurate weather conditions in real time, vine conditions (grape detection, phenological stages determination, and disease status characterization).
- Monitors the wine cellar to avoid temperature and humidity issues causing the wine evaporation during summer time.
- Performs remote frequent characterization of wine composition in order to preserve maximum expression of grape quality potential throughout winemaking phases.
- Allow remote monitoring of storage and transportation conditions of wine from cellar gate to final shelf.
Mr. Dubourdieu will present this case highlighting challenges and opportunities, helping the audience to ‘touch’ the benefits of data in a concrete production environment. (presentation)
Part III. Panel Discussion
The digital revolution is now upon us. A number of digital technologies and trends have the potential of entirely transforming the way the agriculture sector works. These include big data, internet of things, robotics, etc. Applying these technologies to agriculture could provide solutions for many of the challenges the sector is facing. However, in one way or another, these technologies all rely on data sharing among different actors. To generate value out of data, it often has to be aggregated, and data from different sources has to be combined. Data sharing is difficult to achieve and it needs to happen in an environment of trust.
That is the context that Ms. Cuadrado will address presenting the strategy and actions under development at the European Commission.