Aikaterini Kassimati presentation on the Table and Wine Grapes Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
The BigDataGrapes vision enabling global disruption of the grapevine-powered ...Big Data Grapes
Panagiotis Zervas presentation on the vision of the project at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Simone Parisi and Florian Schlenz presentation on the Farm Management Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Eleni Foufa presentation on the Natural Cosmetics Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Big Data Grapes, as part of the European Big Data Value community was on the 16th of May in Sofia, Bulgaria, in an event organised by the Big Data Value PPP, with the twofold objective of strengthening collaborations among community members and increasing the visibility and awareness about the PPP in East Europe in general and Bulgaria in particular. Ontotext, our Bulgarian project partner presented the potential of Big Data Streams in grape and wine production.
#bdvmeetupsofia18
Prediction algorithms for food data analytics and intelligence: towards a bi...Big Data Grapes
The document discusses the development of a big data platform and prediction experimentation panel for food data analytics. The big data platform collects and processes food data from various sources. The prediction experimentation panel allows data scientists to select datasets, customize data and algorithms, run prediction experiments, and evaluate results. It aims to facilitate testing of machine learning algorithms for food price prediction and other applications in an interactive and customizable manner without requiring code changes. Future work includes integrating the prediction panel into the big data platform to enable sharing and experimentation across a community of users.
NetBeat: The first irrigation system with a brainBig Data Grapes
Marco Panizza from Netafim presented the first irrigation system with a brain at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Coraline Damasio presentation on the Wine Making Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019).
Fostering Business and Software Ecosystems for large-scale Uptake of IoT in F...Sjaak Wolfert
The Internet of Things (IoT) is expected to be a real game changer that will drastically improve productivity and sustainability in food and farming. However, current IoT applications in this domain are still fragmentary and mainly used by a small group of early adopters. The Internet of Food and Farm 2020 Large-Scale Pilot (IoF2020) addresses the organizational and technological challenges to overcome this situation by fostering a large-scale uptake of IoT in the European food and farming domain. The heart of the project is formed by a balanced set of multi-actor trials that reflect the diversity of the food and farming domain. Each trial is composed of well-delineated use cases developing IoT solutions for the most relevant challenges of the concerned subsector. The project conducts 5 trials with a total of 19 use cases in arable, dairy, fruits, vegetables and meat production. IoF2020 embraces a lean multi-actor approach that combines the development of Minimal Viable Products (MVPs) in short iterations with the active involvement of various stakeholders. The architectural approach supports interoperability of multiple use case systems and reuse of IoT components across them. Use cases are also supported in developing business and solving governance issues. The IoF2020 ecosystem and collaboration space is established to boost the uptake of IoT in Food and Farming and pave the way for new innovations.
The BigDataGrapes vision enabling global disruption of the grapevine-powered ...Big Data Grapes
Panagiotis Zervas presentation on the vision of the project at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Simone Parisi and Florian Schlenz presentation on the Farm Management Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Eleni Foufa presentation on the Natural Cosmetics Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Big Data Grapes, as part of the European Big Data Value community was on the 16th of May in Sofia, Bulgaria, in an event organised by the Big Data Value PPP, with the twofold objective of strengthening collaborations among community members and increasing the visibility and awareness about the PPP in East Europe in general and Bulgaria in particular. Ontotext, our Bulgarian project partner presented the potential of Big Data Streams in grape and wine production.
#bdvmeetupsofia18
Prediction algorithms for food data analytics and intelligence: towards a bi...Big Data Grapes
The document discusses the development of a big data platform and prediction experimentation panel for food data analytics. The big data platform collects and processes food data from various sources. The prediction experimentation panel allows data scientists to select datasets, customize data and algorithms, run prediction experiments, and evaluate results. It aims to facilitate testing of machine learning algorithms for food price prediction and other applications in an interactive and customizable manner without requiring code changes. Future work includes integrating the prediction panel into the big data platform to enable sharing and experimentation across a community of users.
NetBeat: The first irrigation system with a brainBig Data Grapes
Marco Panizza from Netafim presented the first irrigation system with a brain at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019)
Coraline Damasio presentation on the Wine Making Pilot progress at the BigDataGrapes workshop "Big Data for the Grapevine Industries" in Pisa, Italy (8/3/2019).
Fostering Business and Software Ecosystems for large-scale Uptake of IoT in F...Sjaak Wolfert
The Internet of Things (IoT) is expected to be a real game changer that will drastically improve productivity and sustainability in food and farming. However, current IoT applications in this domain are still fragmentary and mainly used by a small group of early adopters. The Internet of Food and Farm 2020 Large-Scale Pilot (IoF2020) addresses the organizational and technological challenges to overcome this situation by fostering a large-scale uptake of IoT in the European food and farming domain. The heart of the project is formed by a balanced set of multi-actor trials that reflect the diversity of the food and farming domain. Each trial is composed of well-delineated use cases developing IoT solutions for the most relevant challenges of the concerned subsector. The project conducts 5 trials with a total of 19 use cases in arable, dairy, fruits, vegetables and meat production. IoF2020 embraces a lean multi-actor approach that combines the development of Minimal Viable Products (MVPs) in short iterations with the active involvement of various stakeholders. The architectural approach supports interoperability of multiple use case systems and reuse of IoT components across them. Use cases are also supported in developing business and solving governance issues. The IoF2020 ecosystem and collaboration space is established to boost the uptake of IoT in Food and Farming and pave the way for new innovations.
This document discusses a "smart farm" project that uses sensors, internet connectivity, and semantic technologies to monitor and manage a farm. The project collects data from 100 soil sensors and 2 weather stations on the farm. It uses an ontology and linked open data to semantically integrate and provide open access to the sensor data. Machine learning algorithms could potentially generate predictive models from the sensor data to estimate values without physical sensors. The system detects events on the farm like cattle leaving and alerts farmers. It aims to help farmers make informed decisions and remotely monitor their farm operations.
Entrepreneurs active in the agricultural sector spend more and more of their time registering and publishing all kinds of data, as the government, certification bodies, banks, clients, the retail sector and consumers all want to have more insight into how safe and sustainable their food is.
The majority of this agriculture-related data is still paper-based, spread over different systems and difficult to exchange between the people who want to access it. This is why digitising agricultural business data is an important item on the agenda. With FarmDigital, we can respond to these developments.
FarmDigital is an action research programme which is currently working towards a situation in which data only needs to be entered once and can be shared easily. It aims to achieve this goal by standardising data and developing and implementing an independent, digital platform for people to use.
IoF2020 project overview for BDE/eRosa/GODANSjaak Wolfert
Presentation of the IoF2020 project at the 2nd Joint workshop of Big Data Europe, eRosa & GODAN on European Policy Perspectives on Data-intensive Agriculture & Food.
- Qoudra is a technology company that has developed IoT solutions for farming and renewable energy since 2009.
- Recently, they developed an Internet of Farming solution called Mirsaad for Agriculture that collects big data from plants in real-time using sensors to measure parameters like temperature, humidity, and soil moisture.
- This solution consists of BLE beacons to identify each tree, sensors, a control unit, data gateway, and local data center to buffer data when internet is unavailable.
Bridging the skills gap IoT Tech Expo Berlin 1 Jun 2017Sjaak Wolfert
Bridging the skills gap: How industrial/academic partnerships can benefit your IoT business.
Several of the large IoT players have recently partnered with universities and colleges worldwide to ensure that the next generation of recruits have the high level technical skills and understanding of the IoT ecosystem need to add value to their businesses. How should you take advantage of such collaboration opportunities, and how can they translate into increasing innovation and getting that competitive edge within your organisation? The EU-funded IoT Large Scale Pilot 'The Internet of Food and Farm 2020 (IoF2020)' will be used as a showcase. New opportunities for collaboration will be mentioned.
The SmartAgriHubs project enables a broad digital transformation of the European farming and food sector. With a €20 million budget co-funded by the European Union, the project aims to build an extensive pan-European network of Digital Innovation Hubs (DIHs). The project starts today on November 1st, 2018. This presentation describes the project's objective and method that is used to reach these objectives.
The document discusses the increasing role of information and communication technologies (ICT) in agriculture and food systems. It describes how technologies like mobile/cloud computing, location-based monitoring, the Internet of Things, and big data can help address challenges in transportation, input supply, farming, food processing, retail, and consumer demands. Examples are provided of ICT solutions that offer benefits like early detection of animal health issues, optimized crop spraying advice, and food traceability. Concerns are raised about issues like data ownership and the potential for industry consolidation or lock-in under different business models enabled by big data in agriculture.
This document discusses how IoT can enable smart farming and food systems. It describes an ecosystem of apps that can push data between farmers, equipment, weather services, and government agencies to optimize activities like pesticide spraying. The IoF2020 project aims to demonstrate IoT business cases across the food sector through large-scale trials. It will integrate available technologies, address user needs, and establish an IoT ecosystem to facilitate large-scale adoption of IoT in European agriculture and food.
Large ICT-projects in Agri-Food in EuropeSjaak Wolfert
This is a presentation about the background, development and state-of-the-art of large ICT-projects in Agri-Food that are going on in Europe: Internet of Food and Farm 2020 (IoF2020) and SmartAgriHubs.
Precision Agriculture and ICT in The NetherlandsSjaak Wolfert
This document summarizes developments in information and communication technology (ICT) and precision agriculture in the Netherlands. It discusses several Dutch and EU projects funding these areas, with budgets ranging from 1.3 to 20 million Euros. ICT is becoming a key driver of innovation through tools like GPS, sensors, cloud services, and social media. The document outlines a roadmap for technical and organizational solutions and describes use cases around controlled traffic farming, variable rate application, and smart agriculture food pilots involving greenhouse management, crop spraying, and supply chain monitoring.
IoF2020 project overview for S3 platform Big Data and TraceabilitySjaak Wolfert
Presentation at a technical meeting of the S3 AgriFood platform on Big Data and Traceability hosted by the regional government of Andalusia. Special attention was paid to those use cases that are dealing with this theme.
This document provides an overview of the IoF2020 project, which aims to foster large-scale adoption of IoT technologies in European farming and food production. The project objectives are to (1) demonstrate IoT's business value across various farming and food applications, (2) integrate and reuse available IoT technologies through open standards, and (3) ensure user acceptability by addressing needs like security, privacy and trust. A lean multi-actor approach will be used to conduct trials of IoT use cases in areas like arable, vegetables and dairy farming. The project aims to establish an IoT ecosystem to support large-scale adoption beyond the lifetime of the project.
This is a keynote presentation presented at a conference on INNOVATIVE TECHNOLOGIES AND DATA APPLICATIONS IN THE AGRIFOOD SECTOR, 26 February 2019 at Boğaziçi Üniversitesi South Campus, Rectorate Conference Hall, Turkey. It describes multi-disciplinary, collaborative, agile approach for digital transformation of the agri-food sector based on the IoF2020 and SmartAgriHubs project. It describes several examples of IoT and Big Data applications from those projects,
The video and voice-over of this presentation can be found at https://youtu.be/wYJVqh6jvSE
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...Andreas Kamilaris
With the recent advancement of the Internet of Things (IoT), it is now possible to process a large number of sensor data streams using different large-scale IoT platforms. These IoT frameworks are used to collect, process and analyse data streams in real-time and facilitate provision of smart solutions
designed to provide decision support. Existing IoT-based solutions are mainly domain-dependent, providing stream processing and analytics focusing on specific areas (smart cities, healthcare etc.). In the context of agri-food industry, a variety of external parameters belonging to different domains (e.g. weather conditions, regulations etc.) have a major influence over the food supply chain, while flexible and adaptive IoT frameworks, essential to truly realize the concept of smart farming, are currently inexistent. In this presentation, we propose Agri-IoT, a semantic framework for IoT-based smart farming applications, which supports reasoning over
various heterogeneous sensor data streams in real-time. Agri-
IoT can integrate multiple cross-domain data streams, providing
a complete semantic processing pipeline, offering a common
framework for smart farming applications. Agri-IoT supports
large-scale data analytics and event detection, ensuring seamless interoperability among sensors, services, processes, operations, farmers and other relevant actors, including online information sources and linked open datasets and streams available on the Web.
KG2 has been collecting, compiling and managing data for agricultural marketing professionals for over 20
years.It serves the markets and works with the leading organisations involved in crop production in Australia.
Smart Farming is a development that emphasizes the use of information and communication technology in the
cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing
are expected to leverage this development and introduce more robots and artificial intelligence in farming.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be
captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of
Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following
a structured approach, a conceptual framework for analysiswas developed that can also be used for future
studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond
primary production; 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. Several authors therefore suggest that Big Data will cause major shifts in
roles and power relationsamong different players in current food supply chain networks. The landscape of stakeholders
exhibits an interesting gamebetween 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 in which the farmer is part of a highly integrated
food supply chain or 2) open, collaborative systems inwhich the farmer and every other stakeholder in the chain
network is flexible in choosing business partners as well for the technology as for the food production side. The
further development of data and application infrastructures (platforms and standards) and their institutional
embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective,
the authors propose to give research priority to organizational issues concerning governance issues and suitable
business models for data sharing in different supply chain scenarios.
DATA-FAIR - value creation by data sharing in agri-food businessSjaak Wolfert
The digitization of society makes data more important. This is enhanced by the Internet of Things (IoT) in which a variety of devices, sensors and the like are connected via the Internet together and deliver real-time data.
Many companies see data as the way to generate new business, also in the agri-food sector. However, the added value is only created when multiple data sources are combined, aggregated and analyzed. The sharing of data between companies in the chain is therefore a critical success factor.
Although several initiatives to share data have been initiated, this development seems to be stagnating. Now the agribusinesses are mainly developing their own proprietary platforms, resulting in a maze of platforms which makes it technically difficult to exchange data between different systems and devices. This causes rather more administrative burdens than they reduce.
Exchange of data between platforms and applications is currently inhibited because of discussions about ownership of data, privacy, fear of concentration of power in the chain and the lack of clear business models where added value of data sharing is distributed among the various stakeholders. Now it seems that the benefit to the primary producers - the farmers - is minimal and the agri-business seems to benefit most. This creates resistance to sharing data that inhibits innovations that ultimately serve the interests of the farmer and the competitiveness of the whole agri-food sector.
DATA-FAIR breaks this deadlock and will accelerate innovation by hosting several large-scale trials with companies and Wageningen Research in which applications are developed where data between various platforms is shared and value is created.
In these trials, the farmer plays a central role as a main supplier and manager of data. He or she determines who may use which data and under what conditions. Digital permissions will play an important role enabled by a central register (e.g. AgriTrust). Also, special attention is paid to the development of attractive and transparent business models and good organizational embedding (governance) so that the results will continue to exist after the project.
DATA-FAIR doesn’t create a new platform itself, but uses existing building blocks and will help improving these if necessary. Here one can think of open application interfaces (APIs) and standards to link platforms and databases. DATA-FAIR builds on experiences with existing data hubs such as EDI-Circle and AgriPlace.
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.
FI-PPP SmartAgriFood and FIspace at IoT China 2013Sjaak Wolfert
This document summarizes a presentation about future internet business collaboration networks in agri-food, transport, and logistics. It discusses how information and communication technologies (ICT) are crucial drivers of innovation in multi-dimensional agri-food supply chain networks. It then describes the EU Future Internet Public-Private Partnership program and two projects it has funded - SmartAgriFood and FIspace. SmartAgriFood aims to boost the use of future internet technologies in agri-food through various pilots. FIspace aims to facilitate seamless cross-organizational collaboration and transparency through a platform integrating different technologies.
The SMART GROUND project aims to enhance availability and accessibility of data on secondary raw materials from landfill mining in the EU. Funded by the European Commission's Horizon 2020 program, the 30-month project involves 14 partners from 5 EU countries. The objectives are to collect and integrate quantitative and structural data on secondary raw materials, identify promising markets, evaluate environmental and socioeconomic impacts, analyze legislation, and build an inventory through a database platform. The project focuses on construction and demolition waste, municipal waste, and mining waste from landfills.
This document describes several IoT tools being developed for sustainable wine production, quality management, and shipping monitoring. The tools include sensors and software to monitor vineyards, wineries, and shipments. Sensors collect data on production factors like water and pesticide use in vineyards. Spectrometers and software analyze wine composition. Data loggers track temperature during shipping to identify quality issues. The tools aim to reduce costs, improve sustainability, and help resolve disputes through remote monitoring and data analysis.
This document discusses a "smart farm" project that uses sensors, internet connectivity, and semantic technologies to monitor and manage a farm. The project collects data from 100 soil sensors and 2 weather stations on the farm. It uses an ontology and linked open data to semantically integrate and provide open access to the sensor data. Machine learning algorithms could potentially generate predictive models from the sensor data to estimate values without physical sensors. The system detects events on the farm like cattle leaving and alerts farmers. It aims to help farmers make informed decisions and remotely monitor their farm operations.
Entrepreneurs active in the agricultural sector spend more and more of their time registering and publishing all kinds of data, as the government, certification bodies, banks, clients, the retail sector and consumers all want to have more insight into how safe and sustainable their food is.
The majority of this agriculture-related data is still paper-based, spread over different systems and difficult to exchange between the people who want to access it. This is why digitising agricultural business data is an important item on the agenda. With FarmDigital, we can respond to these developments.
FarmDigital is an action research programme which is currently working towards a situation in which data only needs to be entered once and can be shared easily. It aims to achieve this goal by standardising data and developing and implementing an independent, digital platform for people to use.
IoF2020 project overview for BDE/eRosa/GODANSjaak Wolfert
Presentation of the IoF2020 project at the 2nd Joint workshop of Big Data Europe, eRosa & GODAN on European Policy Perspectives on Data-intensive Agriculture & Food.
- Qoudra is a technology company that has developed IoT solutions for farming and renewable energy since 2009.
- Recently, they developed an Internet of Farming solution called Mirsaad for Agriculture that collects big data from plants in real-time using sensors to measure parameters like temperature, humidity, and soil moisture.
- This solution consists of BLE beacons to identify each tree, sensors, a control unit, data gateway, and local data center to buffer data when internet is unavailable.
Bridging the skills gap IoT Tech Expo Berlin 1 Jun 2017Sjaak Wolfert
Bridging the skills gap: How industrial/academic partnerships can benefit your IoT business.
Several of the large IoT players have recently partnered with universities and colleges worldwide to ensure that the next generation of recruits have the high level technical skills and understanding of the IoT ecosystem need to add value to their businesses. How should you take advantage of such collaboration opportunities, and how can they translate into increasing innovation and getting that competitive edge within your organisation? The EU-funded IoT Large Scale Pilot 'The Internet of Food and Farm 2020 (IoF2020)' will be used as a showcase. New opportunities for collaboration will be mentioned.
The SmartAgriHubs project enables a broad digital transformation of the European farming and food sector. With a €20 million budget co-funded by the European Union, the project aims to build an extensive pan-European network of Digital Innovation Hubs (DIHs). The project starts today on November 1st, 2018. This presentation describes the project's objective and method that is used to reach these objectives.
The document discusses the increasing role of information and communication technologies (ICT) in agriculture and food systems. It describes how technologies like mobile/cloud computing, location-based monitoring, the Internet of Things, and big data can help address challenges in transportation, input supply, farming, food processing, retail, and consumer demands. Examples are provided of ICT solutions that offer benefits like early detection of animal health issues, optimized crop spraying advice, and food traceability. Concerns are raised about issues like data ownership and the potential for industry consolidation or lock-in under different business models enabled by big data in agriculture.
This document discusses how IoT can enable smart farming and food systems. It describes an ecosystem of apps that can push data between farmers, equipment, weather services, and government agencies to optimize activities like pesticide spraying. The IoF2020 project aims to demonstrate IoT business cases across the food sector through large-scale trials. It will integrate available technologies, address user needs, and establish an IoT ecosystem to facilitate large-scale adoption of IoT in European agriculture and food.
Large ICT-projects in Agri-Food in EuropeSjaak Wolfert
This is a presentation about the background, development and state-of-the-art of large ICT-projects in Agri-Food that are going on in Europe: Internet of Food and Farm 2020 (IoF2020) and SmartAgriHubs.
Precision Agriculture and ICT in The NetherlandsSjaak Wolfert
This document summarizes developments in information and communication technology (ICT) and precision agriculture in the Netherlands. It discusses several Dutch and EU projects funding these areas, with budgets ranging from 1.3 to 20 million Euros. ICT is becoming a key driver of innovation through tools like GPS, sensors, cloud services, and social media. The document outlines a roadmap for technical and organizational solutions and describes use cases around controlled traffic farming, variable rate application, and smart agriculture food pilots involving greenhouse management, crop spraying, and supply chain monitoring.
IoF2020 project overview for S3 platform Big Data and TraceabilitySjaak Wolfert
Presentation at a technical meeting of the S3 AgriFood platform on Big Data and Traceability hosted by the regional government of Andalusia. Special attention was paid to those use cases that are dealing with this theme.
This document provides an overview of the IoF2020 project, which aims to foster large-scale adoption of IoT technologies in European farming and food production. The project objectives are to (1) demonstrate IoT's business value across various farming and food applications, (2) integrate and reuse available IoT technologies through open standards, and (3) ensure user acceptability by addressing needs like security, privacy and trust. A lean multi-actor approach will be used to conduct trials of IoT use cases in areas like arable, vegetables and dairy farming. The project aims to establish an IoT ecosystem to support large-scale adoption beyond the lifetime of the project.
This is a keynote presentation presented at a conference on INNOVATIVE TECHNOLOGIES AND DATA APPLICATIONS IN THE AGRIFOOD SECTOR, 26 February 2019 at Boğaziçi Üniversitesi South Campus, Rectorate Conference Hall, Turkey. It describes multi-disciplinary, collaborative, agile approach for digital transformation of the agri-food sector based on the IoF2020 and SmartAgriHubs project. It describes several examples of IoT and Big Data applications from those projects,
The video and voice-over of this presentation can be found at https://youtu.be/wYJVqh6jvSE
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...Andreas Kamilaris
With the recent advancement of the Internet of Things (IoT), it is now possible to process a large number of sensor data streams using different large-scale IoT platforms. These IoT frameworks are used to collect, process and analyse data streams in real-time and facilitate provision of smart solutions
designed to provide decision support. Existing IoT-based solutions are mainly domain-dependent, providing stream processing and analytics focusing on specific areas (smart cities, healthcare etc.). In the context of agri-food industry, a variety of external parameters belonging to different domains (e.g. weather conditions, regulations etc.) have a major influence over the food supply chain, while flexible and adaptive IoT frameworks, essential to truly realize the concept of smart farming, are currently inexistent. In this presentation, we propose Agri-IoT, a semantic framework for IoT-based smart farming applications, which supports reasoning over
various heterogeneous sensor data streams in real-time. Agri-
IoT can integrate multiple cross-domain data streams, providing
a complete semantic processing pipeline, offering a common
framework for smart farming applications. Agri-IoT supports
large-scale data analytics and event detection, ensuring seamless interoperability among sensors, services, processes, operations, farmers and other relevant actors, including online information sources and linked open datasets and streams available on the Web.
KG2 has been collecting, compiling and managing data for agricultural marketing professionals for over 20
years.It serves the markets and works with the leading organisations involved in crop production in Australia.
Smart Farming is a development that emphasizes the use of information and communication technology in the
cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing
are expected to leverage this development and introduce more robots and artificial intelligence in farming.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be
captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of
Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following
a structured approach, a conceptual framework for analysiswas developed that can also be used for future
studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond
primary production; 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. Several authors therefore suggest that Big Data will cause major shifts in
roles and power relationsamong different players in current food supply chain networks. The landscape of stakeholders
exhibits an interesting gamebetween 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 in which the farmer is part of a highly integrated
food supply chain or 2) open, collaborative systems inwhich the farmer and every other stakeholder in the chain
network is flexible in choosing business partners as well for the technology as for the food production side. The
further development of data and application infrastructures (platforms and standards) and their institutional
embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective,
the authors propose to give research priority to organizational issues concerning governance issues and suitable
business models for data sharing in different supply chain scenarios.
DATA-FAIR - value creation by data sharing in agri-food businessSjaak Wolfert
The digitization of society makes data more important. This is enhanced by the Internet of Things (IoT) in which a variety of devices, sensors and the like are connected via the Internet together and deliver real-time data.
Many companies see data as the way to generate new business, also in the agri-food sector. However, the added value is only created when multiple data sources are combined, aggregated and analyzed. The sharing of data between companies in the chain is therefore a critical success factor.
Although several initiatives to share data have been initiated, this development seems to be stagnating. Now the agribusinesses are mainly developing their own proprietary platforms, resulting in a maze of platforms which makes it technically difficult to exchange data between different systems and devices. This causes rather more administrative burdens than they reduce.
Exchange of data between platforms and applications is currently inhibited because of discussions about ownership of data, privacy, fear of concentration of power in the chain and the lack of clear business models where added value of data sharing is distributed among the various stakeholders. Now it seems that the benefit to the primary producers - the farmers - is minimal and the agri-business seems to benefit most. This creates resistance to sharing data that inhibits innovations that ultimately serve the interests of the farmer and the competitiveness of the whole agri-food sector.
DATA-FAIR breaks this deadlock and will accelerate innovation by hosting several large-scale trials with companies and Wageningen Research in which applications are developed where data between various platforms is shared and value is created.
In these trials, the farmer plays a central role as a main supplier and manager of data. He or she determines who may use which data and under what conditions. Digital permissions will play an important role enabled by a central register (e.g. AgriTrust). Also, special attention is paid to the development of attractive and transparent business models and good organizational embedding (governance) so that the results will continue to exist after the project.
DATA-FAIR doesn’t create a new platform itself, but uses existing building blocks and will help improving these if necessary. Here one can think of open application interfaces (APIs) and standards to link platforms and databases. DATA-FAIR builds on experiences with existing data hubs such as EDI-Circle and AgriPlace.
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.
FI-PPP SmartAgriFood and FIspace at IoT China 2013Sjaak Wolfert
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The SMART GROUND project aims to enhance availability and accessibility of data on secondary raw materials from landfill mining in the EU. Funded by the European Commission's Horizon 2020 program, the 30-month project involves 14 partners from 5 EU countries. The objectives are to collect and integrate quantitative and structural data on secondary raw materials, identify promising markets, evaluate environmental and socioeconomic impacts, analyze legislation, and build an inventory through a database platform. The project focuses on construction and demolition waste, municipal waste, and mining waste from landfills.
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This document summarizes several projects that received funding from the European Union to develop and demonstrate technologies for improving water and nutrient use efficiency in soil-grown crops. It describes 9 showcase projects from different partners across Europe that tested sensors, decision support tools, and other technologies for more precise irrigation management and reduction of overfertilization. The projects monitored soil moisture, nutrients, and plant parameters in various crops like tomatoes, peppers, olives and more to optimize fertigation according to real-time crop needs.
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...Andreas Kamilaris
Intensive farming has been linked to excessive accumulation of heavy metals and other contaminants on soil, and to significant groundwater pollution with nitrates. Hence, it is necessary to develop a common body of knowledge, so as to allow an effective monitoring of cropping systems, fertilization and water demands, and impacts of climate change, with a focus on the sustainability and the protection of the physical environment. In this presentation, we describe AgriBigCAT, an online software platform that uses geophysical information from various diverse sources, employing geospatial and big data analysis, together with web technologies, in order to estimate the impact of the agricultural sector on the environment. It considers land, water, biodiversity and natural areas requiring protection, such as forests and wetlands. This platform can assist both the farmers' decision-taking processes and the administration planning and policy-making, with the ultimate objective of meeting the challenge of increasing food production at a lower environmental impact. An online application of AgriBigCAT, focusing on the local environmental issues of the agricultural sector of Catalonia, is presented and described, together with some preliminary analysis findings. This presentation has been prepared for the EFITA 2017 Congress in Montpellier.
This project summary outlines the objectives and activities of the SMART GROUND project, which aims to enhance availability and accessibility of data on secondary raw materials in the EU. The project has 14 partners from 5 EU countries and received full funding from the Horizon 2020 program. Key objectives include collecting and integrating quantitative and structural knowledge on secondary raw materials from existing landfills, identifying promising markets, and building an inventory database. To achieve these objectives, the project will characterize pilot sites, estimate materials potential, and create an open user-friendly online platform to facilitate sharing of reports, statistics, and advanced search/retrieval of data.
Parrot pro agro - Agro Innovations Forum 2018 by DroneUADroneUA Iakovenko
8 июня в рамках выставки Агро-2018 прошел Международный форум аграрных инноваций «Agro Innovations Forum 2018».Это первое мероприятие такого формата организованное DroneUA.Форум состоялся при поддержке Министерства аграрной политики и продовольствия Украины и Агентства «Бизнес Франс» при Посольстве Франции в Украине.
The SWAMP project develops IoT-based methods for smart water management in precision irrigation. It aims to develop these methods, address climate change challenges by using water and energy efficiently, and maximize crop yields. The project will pilot the approaches in Europe and Brazil, with objectives of automating platforms, integrating sensors, and validating new business models for smart water management.
The networking session provided an overview of the SMART GROUND project, which aims to (1) collect and integrate quantitative and structural data on secondary raw materials (SRMs) from landfill sites across the EU, (2) identify the most promising markets for SRMs, and (3) evaluate the environmental, economic, and social impacts of extracting SRMs from landfills. The project involves characterizing pilot landfill sites, estimating their potential SRMs, building an online database, and creating a marketplace to connect SRM suppliers with potential customers like construction companies. The overall goal is to help advance the circular economy and EU waste management targets by exploiting landfills as a source of new resources.
SaltGae Project: results achieved and demo sites.SALTGAEProject
This document summarizes a stakeholder event for the Saltgae Project, which received funding from the European Union's Horizon 2020 Innovation Action programme. The project aims to develop a modular technology platform for efficiently treating saline wastewater with organic loads. The event provided an overview of the project objectives, structure, scientific approach and challenges. It also described the project's pilot sites in Ljubljana and Israel and discussed preliminary tests on sludge valorization, biomass valorization, and effluent valorization.
Estimating the Environmental Impact of Agriculture by means of Geospatial and...Andreas Kamilaris
This document discusses using geospatial and big data analysis to estimate the environmental impact of agriculture in Catalonia. The methodology involves collecting datasets from agricultural sensors and weather monitoring, developing a database to store the data, using the datasets as layers in a geospatial analysis tool, and applying big data analysis to estimate impacts and find solutions. The results are presented through an online policy tool that allows visualizing data on farms, emissions calculations, and GIS maps showing analysis of areas like animal concentration and methane emissions. The tool aims to help policymakers make decisions on issues like manure management. Future work will focus on nitrate management and siting manure plants.
This document describes the design of a remotely monitored agricultural vehicle. The vehicle is equipped with sensors to measure temperature, moisture, humidity, and nitrogen, phosphorus, and potassium (NPK) levels in soil. It transmits sensor data via Wi-Fi to be viewed on a mobile app. A camera provides live video streaming and a GPS tracker monitors the vehicle's location. The system aims to help farmers remotely monitor field conditions to optimize water and nutrient management. It was tested in soil and successfully measured various parameters and transmitted data via Wi-Fi. The project allows individual plant monitoring over an entire field to improve crop yields.
The Development of the Scheduled Planting (SP) and High Starch Content (HS) Decision Support
Tool – Current progress, including how WS1-3 activities feed into the Decision Support Tool
This project received funding from the European Union to develop a soil map-based variable rate application and machine automation system for potato production. The system includes:
1) A Soil Map Service that creates high-resolution soil maps using sensor data and soil analyses.
2) A Variable Rate Application Map Service that generates precision crop management task maps based on soil variability maps.
3) An Automation & Machine Communication system that automatically translates task maps into machine instructions and logs application data.
The goal is to improve potato yields, quality, and farming efficiency through precision agriculture techniques informed by detailed soil data analysis and variable rate applications. Field trials were conducted in 2016-2018 to validate and refine the system.
Commercial & research landscape for smart irrigation systems. A survey of commercial product offerings, research prototypes and approaches to smart irrigation. I also cover the why there is such a dire need to conserve water and increase yield.
This document summarizes a workshop on the Saltgae project, which received funding from the European Union to develop a pilot site in Camporosso, Italy for treating dairy wastewater using algae. The 0.5 hectare pilot site uses a multi-stage process including pretreatment, algae growth in photobioreactors, harvesting, and drying to remove nutrients from the wastewater and produce algae biomass. The workshop aimed to explain how the system was designed and currently operates to convert wastewater from a liability to a useful resource.
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BigDataGrapes_Table and Wine Grapes Pilot
1. WWW.BIGDATAGRAPES.EU
BigDataGrapes - Big Data to Enable Global Disruption of the
Grapevine-powered Industries has received funding from the
European Union’s Horizon 2020 research and innovation programme
under grant agreement No 780751.
Table and Wine Grapes
Pilot
“Big Data for the Grapevine Industries” Workshop |
Pisa , Italy, 08/03/2019
Aikaterini Kasimati | Laboratory of Precision Agriculture
Maritina Stavrakaki | Laboratory of
Viticulture
Agricultural University of Athens
“Big Data for the Grapevine Industries”
Workshop
2. WWW.BIGDATAGRAPES.EU
Tables and Wine Grapes Pilot
Introduction & Specific Goals
Technical Guidelines and Methodology
• Site Description
• Equipment Used and Measurements
Data Collected
Expected Timeline
Envisaged Outcomes
“Big Data for the Grapevine Industries” Workshop 2
Presentation Outline
5. WWW.BIGDATAGRAPES.EU
This pilot will continuously collect and monitor sensor, farming and
phenological data derived from all test sites located in Greece.
Pilot’s goal
Denote associations and correlations between precision agriculture
information and phenological data and grape chemical analysis
Ultimate goal
Correlate the aforementioned data with earth observation data to
examine the effectiveness of applying machine learning techniques and
eventually train the relevant machine learning components
5
Table and Wine Grapes Pilot
Specific Goals
“Big Data for the Grapevine Industries” Workshop
7. WWW.BIGDATAGRAPES.EU 7
Three test sites in the
north-eastern part of
Peloponnese, Greece:
• Palivou Estate
• Kontogiannis
Estate
• Fasoulis Estate
Site Description
“Big Data for the Grapevine Industries” Workshop
8. WWW.BIGDATAGRAPES.EU 8
• Nemea
• Vitis vinifera L. cv.
‘Agiorgitiko’ and ‘Merlot’
for winemaking
• northeast-southwest
row orientation
• VSP - cane
pruning, double Guyot
training/trellis system
Site Description
Palivou Estate
“Big Data for the Grapevine Industries” Workshop
9. WWW.BIGDATAGRAPES.EU 9
• Ancient Corinth
• ‘Roditis’, ‘Savatiano’,
‘Mavroudi’ and
‘Soultanina’ for
winemaking north-south
row orientation
• VSP - cane
pruning, double Guyot
or double Royat
training/trellis system
Site Description
Kontogiannis Estate
“Big Data for the Grapevine Industries” Workshop
11. WWW.BIGDATAGRAPES.EU 11
HiPer V RTK GPS
Topographical data: field boundary points and elevation data
Equipment Used and Measurements
Topographical and Elevation Mapping
“Big Data for the Grapevine Industries” Workshop
12. WWW.BIGDATAGRAPES.EU 12
EM38-MK2 probe
Soil electrical conductivity (ECa) at 0.5 and 1.0 m depth (mS/m)
https://photos.app.goo.gl/5LzP3WpcbsRvJEAe9
Equipment Used and Measurements
Geo-referenced Apparent Soil Electrical Conductivity
“Big Data for the Grapevine Industries” Workshop
13. WWW.BIGDATAGRAPES.EU 13
Crop Circle ACS-470
Basic reflectance information from plant canopies and classic spectral
vegetative index data (NDVI, NDRE etc.)
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
14. WWW.BIGDATAGRAPES.EU 14
Crop Circle RapidSCAN CS-45
Basic reflectance information from plant canopies and classic spectral
vegetative index data (NDVI, NDRE etc.)
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
15. WWW.BIGDATAGRAPES.EU 15
SpectroSense2+ GPS
Leaf Area Index (LAI) and NDVI vegetation indices
Equipment Used and Measurements
Canopy Characteristics and Vegetation Indices
“Big Data for the Grapevine Industries” Workshop
16. WWW.BIGDATAGRAPES.EU 16
Two Phantom 4 Pro drones Parrot Sequoia+ Multispectral sensor and
FLIR Vue Pro thermal infrared sensor
Aerial imagery data, vegetation indices, water activity maps
Equipment Used and Measurements
Drones with Multispectral and Thermal Sensors
“Big Data for the Grapevine Industries” Workshop
17. WWW.BIGDATAGRAPES.EU 17
Two Vantage Pro 2 weather stations
Rain sensor, anemometer to measure wind speed and direction, air
temperature sensor, air and soil humidity sensor
Equipment Used and Measurements
Weather and Soil Data
“Big Data for the Grapevine Industries” Workshop
18. WWW.BIGDATAGRAPES.EUWP8 - Grapevine-powered Industry Application Pilots 18
ATAGO N1-a refractometer w/ 0-32 Brix measurement range
Soluble solids
Titration with a 0.1 N NaOH solution
Total titratable acidity -expressed as tartaric acid-
HPLC Shimadzu Nexera (gradient pump Shimadzu Nexera X2, ProStar
model 410 AutoSampler, and ProStar model 330 Photodiode Array Detector)
Quantitative and qualitative analysis of the substances
Modified colorimetric method
Antioxidant activity (2,2-diphenyl-1-picrylhydrazyl, DPPH)
UV/Vis spectrophotometer
Reduction of the DPPH radical @ 517 nm and the absorption of the
antioxidant activity @ 593 nm
Equipment Used and Measurements
Qualitative and Quantitative Data
20. WWW.BIGDATAGRAPES.EU 20
• Identification of grapevine varieties
• Remote sensing for spatial data, topographical and elevation
mapping
• Geo-referenced apparent soil electrical conductivity (ECa)
• Canopy characteristics and vegetation indices
• Water activity and photosynthesis and chlorophyll data
• Qualitative and quantitative characters for wine and table
grapes
• Full phenolic profile of grapevine varieties
• Yield mapping
• Soil, weather and farming data
Data Collected
22. WWW.BIGDATAGRAPES.EU 22
The collection of datasets for BigDataGrapes will serve
as the basis for carrying out research and technical
work
These data will contribute to a data marketplace
demonstrator that will serve as the project’s
experimentation environment
The data pool will be continuously enriched in volume
and range, in accordance with the needs and
requirements of the project
Envisaged Outcomes
“Big Data for the Grapevine Industries” Workshop