Periodic Reporting for period 1 - AgriBIT (Artificial intelliGence applied to pRecision farmIng By the use of GNSS and Integrated Technologies)
Período documentado: 2021-07-01 hasta 2022-12-31
AgriBIT will improve agriculture chain by delivering higher precision, more accurate and continuously available Precision Agriculture services, combining GNSS, and more specifically new high precision Galileo positioning and augmentation services like EGNOS, Earth Observation (EO) information with on-field and on-machine sensors and actuators, Artificial Intelligence (AI) technologies and expert agricultural knowledge. IIt will deliver a range of customisable and modular solutions suitable for various types of agricultural uses and brands of crops through six defined objectives:
• Market and needs analysis
• Higher precision location services
• Affordable, European source, high precision Galileo and EGNOSS GNSS receiver
• Bundle of PA services for farmers and farm advisors
• Strategy for services uptake
• Open service-oriented platform
Project objectives are:
• To understand the business needs and translate them to project technical requirements & exploitation strategies
• To develop and provide a bundle of improved precision agriculture services for farmers and farm advisors
• To develop intelligent high precision location farm information management services for efficient precision agriculture applications
• To support the integration of intelligent agricultural analytics and services provided by third parties through an open service-oriented platform architecture
• To deliver an integrated and intelligent approach for services uptake by service advisors and farmers
• To use and improve a high precision GNSS receiver compliant with Galileo and EGNOS in a very diverse set of products and services to deliver affordable solutions
• Market and needs analysis
• Higher precision location services
• Affordable, European source, high precision Galileo and EGNOSS GNSS receiver
• Bundle of PA services for farmers and farm advisors
• Strategy for services uptake
• Open service-oriented platform
Project objectives are:
• To understand the business needs and translate them to project technical requirements & exploitation strategies
• To develop and provide a bundle of improved precision agriculture services for farmers and farm advisors
• To develop intelligent high precision location farm information management services for efficient precision agriculture applications
• To support the integration of intelligent agricultural analytics and services provided by third parties through an open service-oriented platform architecture
• To deliver an integrated and intelligent approach for services uptake by service advisors and farmers
• To use and improve a high precision GNSS receiver compliant with Galileo and EGNOS in a very diverse set of products and services to deliver affordable solutions
PROJECT, INNOVATION AND DATA MANAGEMENT
It started with the organization of the quality management creation of mailing lists for the whole consortium, and the creation of the committees. A Project Management Handbook has been delivered: it provides the AgriBIT partners with the explanation of rules and guidelines to be adopted in AgriBIT for the complete management of processes. The coordination actions continued with the monitoring of the whole project tasks. A second plenary meeting took place on November 2021, remotely.
AgriBIT REQUIREMENTS AND DESIGN:
AGENSO conducted surveys targeting the end-users of pilot sites. Questionnaires about their perceptions and requirements with respect to the distinct use cases of the AgriBIT system, as well as technical aspects. Coupled with the Consortium’s expertise on a broad spectrum of domains tangent to agri-tech and ICT, the findings shape AgriBIT’s architecture and will guides system development. At a later stage, partners will seek to validate the efficacy of our solution and the satisfaction of the farmer on-site, making adjustments accordingly.
AGRICULTURE VALUE-ADDED SERVICES
Specifications of services were collected to define the input required from the end-users and describe outputs that each service will serve. Based on collected information, a conceptual architecture described system interconnections and dependencies among various parts of the system, services and external systems.
SERVICES INTEGRATION AND DEPLOYMENT
The first version of the community platform has been completed, containing a presentation of AgriBIT services to end users along with the first version of the APIs interface for third parties! Activities continued with the update of the community platform design and with the first model of the mockup for the cross-visualization platform that will expose the GUI for precision agriculture services to end-users. Analysis and design were also conducted on the integration platform of the various subsystems that make up AgriBIT.
It started with the organization of the quality management creation of mailing lists for the whole consortium, and the creation of the committees. A Project Management Handbook has been delivered: it provides the AgriBIT partners with the explanation of rules and guidelines to be adopted in AgriBIT for the complete management of processes. The coordination actions continued with the monitoring of the whole project tasks. A second plenary meeting took place on November 2021, remotely.
AgriBIT REQUIREMENTS AND DESIGN:
AGENSO conducted surveys targeting the end-users of pilot sites. Questionnaires about their perceptions and requirements with respect to the distinct use cases of the AgriBIT system, as well as technical aspects. Coupled with the Consortium’s expertise on a broad spectrum of domains tangent to agri-tech and ICT, the findings shape AgriBIT’s architecture and will guides system development. At a later stage, partners will seek to validate the efficacy of our solution and the satisfaction of the farmer on-site, making adjustments accordingly.
AGRICULTURE VALUE-ADDED SERVICES
Specifications of services were collected to define the input required from the end-users and describe outputs that each service will serve. Based on collected information, a conceptual architecture described system interconnections and dependencies among various parts of the system, services and external systems.
SERVICES INTEGRATION AND DEPLOYMENT
The first version of the community platform has been completed, containing a presentation of AgriBIT services to end users along with the first version of the APIs interface for third parties! Activities continued with the update of the community platform design and with the first model of the mockup for the cross-visualization platform that will expose the GUI for precision agriculture services to end-users. Analysis and design were also conducted on the integration platform of the various subsystems that make up AgriBIT.
Innovative Positioning Performance improvements for modern Precision Agriculture
AgriBIT aims to improve the agriculture chain by exploiting the added value of combining GNSS, in particular new high precision Galileo positioning and augmentation services like EGNOS and alike, Earth Observation (EO) information with on-field and on-machine sensors and actuators, innovative use of Artificial Intelligence technologies to aid in managing crops through AI-driven Decision Support System, and expert agricultural knowledge to deliver high precision and continuously available services.
Novel solutions for Modern Agriculture taking advantage of Earth Observations (EO)
AgriBIT puts emphasis on sustained provision and access of most relevant Earth Observation data, developing enhancements (data products and predictive models) targeting various types of crops out of EO observations to improve agricultural monitoring, development of the capacity and infrastructure necessary to make available and utilize earth observation information. It will develop and improve analytical tools and methods for agricultural risk assessment, particularly for crop failure, supporting operational agricultural monitoring systems, enhancing current capabilities in the areas of agricultural monitoring, early warning and food security.
Novel applications of Artificial Intelligence (AI) in modern Precision Agriculture
AgriBIT aims at targeting primarily technological AI challenges in PA, to demonstrate unique benefits behind combining precise positioning offered by modern and future GNSS with advances in Machine Learning/Vision and Artificial Intelligence systems performing cognitive analysis of large amounts of data (Big Data problem) made available from vast variety of sources, from large scale EO images to very localised aerial and ground based surveillance and monitoring systems.
Autonomous Systems in service of modern Precision Agriculture applications
AgriBIT targets development of robust and self-learning (AI-based) means of controlling heterogeneous vehicle systems with focus on Agricultural applications. Starting with nonlinear observer theory to build new efficient algorithms for sensor fusion of inertial, magnetic, range/position, velocity, and imaging sensors, through novel Machine Learning methods to understand the surrounding environments to autonomous selfmanagement of a mission. Target detection, tracking and understanding based on AI-vision with be key research subjects.
New services for agriculture
Many agricultural services on the market are not “smart”, assuming that users are “aware” of all opportunities and what implications certain measurements could have. It is common among farmers to consider technology as a powerful tool. They often do not have the training nor time to invest in understanding benefits of ‘optimal use of data’. AI will aim to overcome this barrier. It will simplify instruction to farmers based on data, measurements, etc. The target is to deliver additional “intelligence” to help farmers interpret data and increase their interest in monitoring and evaluating improvements over time.
Bringing Precision Agriculture services to farmers
Whilst PA is a key to sustainable use of resources and decrease the spreading of diseases to crops, current solutions have brought more precise management capabilities to larger farm holdings. This in practice overlooks 70% of farm holdings in Europe whose size is below 15 hectares. AgriBIT provides innovative and advanced farm management services building on the increased accuracy and availability of GNSS enabled services, and its open architecture and approach supports the connection of the services across a wide range of sensors and actuators.
AgriBIT aims to improve the agriculture chain by exploiting the added value of combining GNSS, in particular new high precision Galileo positioning and augmentation services like EGNOS and alike, Earth Observation (EO) information with on-field and on-machine sensors and actuators, innovative use of Artificial Intelligence technologies to aid in managing crops through AI-driven Decision Support System, and expert agricultural knowledge to deliver high precision and continuously available services.
Novel solutions for Modern Agriculture taking advantage of Earth Observations (EO)
AgriBIT puts emphasis on sustained provision and access of most relevant Earth Observation data, developing enhancements (data products and predictive models) targeting various types of crops out of EO observations to improve agricultural monitoring, development of the capacity and infrastructure necessary to make available and utilize earth observation information. It will develop and improve analytical tools and methods for agricultural risk assessment, particularly for crop failure, supporting operational agricultural monitoring systems, enhancing current capabilities in the areas of agricultural monitoring, early warning and food security.
Novel applications of Artificial Intelligence (AI) in modern Precision Agriculture
AgriBIT aims at targeting primarily technological AI challenges in PA, to demonstrate unique benefits behind combining precise positioning offered by modern and future GNSS with advances in Machine Learning/Vision and Artificial Intelligence systems performing cognitive analysis of large amounts of data (Big Data problem) made available from vast variety of sources, from large scale EO images to very localised aerial and ground based surveillance and monitoring systems.
Autonomous Systems in service of modern Precision Agriculture applications
AgriBIT targets development of robust and self-learning (AI-based) means of controlling heterogeneous vehicle systems with focus on Agricultural applications. Starting with nonlinear observer theory to build new efficient algorithms for sensor fusion of inertial, magnetic, range/position, velocity, and imaging sensors, through novel Machine Learning methods to understand the surrounding environments to autonomous selfmanagement of a mission. Target detection, tracking and understanding based on AI-vision with be key research subjects.
New services for agriculture
Many agricultural services on the market are not “smart”, assuming that users are “aware” of all opportunities and what implications certain measurements could have. It is common among farmers to consider technology as a powerful tool. They often do not have the training nor time to invest in understanding benefits of ‘optimal use of data’. AI will aim to overcome this barrier. It will simplify instruction to farmers based on data, measurements, etc. The target is to deliver additional “intelligence” to help farmers interpret data and increase their interest in monitoring and evaluating improvements over time.
Bringing Precision Agriculture services to farmers
Whilst PA is a key to sustainable use of resources and decrease the spreading of diseases to crops, current solutions have brought more precise management capabilities to larger farm holdings. This in practice overlooks 70% of farm holdings in Europe whose size is below 15 hectares. AgriBIT provides innovative and advanced farm management services building on the increased accuracy and availability of GNSS enabled services, and its open architecture and approach supports the connection of the services across a wide range of sensors and actuators.