Periodic Reporting for period 1 - Smart Droplets (Accelerating the achievement of EU Green Deal Goals for pesticide and fertilizer reduction through AI, data and robotic technologies.)
Reporting period: 2022-09-01 to 2023-08-31
The "Smart Droplets" Horizon Europe project, stands at the forefront of pioneering agricultural advancements. This project merges the realms of technology and agriculture, aspiring to reshape conventional farming methodologies with state-of-the-art digital innovations. Distinguished beneficiaries, each contributing unique expertise, have collaborated intensively, ensuring that the project's aspirations translate into tangible results. This chapter provides an in-depth insight into the endeavors undertaken by these beneficiaries, highlighting both the milestones achieved and the challenges encountered.
The overall strategy of the project is based on the four interrelated objectives that were set out since the beginning of the project. For the execution of each of the objectives a plan of work was devised in such a way, as to ensure that each of the tasks and activities carried out will complement and pave the ground for the next one.
In the initial phase of the project, the Project Management Handbook and the Data Management Plan were developed. The Project Management Handbook serves as a comprehensive guide, outlining the management structures, methodologies, and procedures to ensure the project’s objectives are met efficiently. Accordingly, the initial Data Management Plan was developed to establish protocols for data handling, storage, and sharing while ensuring security and privacy.
Additionally, the project focused on analyzing industry needs and developing reference architectures by conducting a thorough Industry Needs & Requirements Analysis to initially understand the specific needs and challenges faced by the industry. These needs will be finalized during the forthcoming period. Also, the Smart Droplets Academy Program, Timeline & Activities was established to provide a comprehensive learning and development initiative for addressing these needs. Standardized architectures for industry applications were proposed and reported in Reference Architectures & Resources Mapping.
In WP3, a first functional prototype of the Smart Droplets’ Digital Platform and Digital Twin Intelligence is under development. The platform will be equipped with features (digital twin, AI for pesticide recommendation intelligence, and pest detection and canopy characterization) to simulate and analyze farm intelligence for optimized spraying application.
Accordingly, the components of the Autonomous Robotic Spraying System (WP4) are under development as well. Specifically, the consortium is designing a robust localization and 3D mapping process along with a multi- objective path planning in harsh environments. Additionally, Intelligent Spraying and Direct Injection Systems are developed to be used for optimized spraying applications through variable rate applications and robots among other settings.
Furthermore, during those first twelve months the Smart Droplets consortium also devised a plan on the dissemination and communication of the project results, defining the means and channels to be used, in order to showcase the commerciality of the Smart Droplets products and services right from the beginning. Communication tools such as the projects’ website, leaflets, brochures and fact sheets, were also produced. Additionally amongst the issues that were tackled during the first period was the strategy for the Intellectual Property Rights (IPR) that concerned the commercial exploitation of the project results and the Data Management Plan that dealt with issues of data collection, production and processing.
Smart Droplets project has been active since September 2022 and the overall progress is according to the planned tasks. The main goal of the project is to improve farming practices by integrating modern digital technologies. This effort is driven by the need to make farming more resource-efficient, environmentally friendly, and productive.
The primary goal of Smart Droplets will be accomplished by fulfilling the Key Objectives (KO) outlined below, which encompass the anticipated outcomes, facets of the work programme topic, and meeting designated Key Performance Indicators (KPIs). More detailed information of the specific objectives set from the beginning of the project is given in the section below.
Overall Objective: Advance both hardware and software capabilities during chemical applications for resource optimisation and minimisation of chemical waste. To accomplish this vision, this project will use already existing technologies (>TRL 7) developed within but not limited to the agricultural industry. Its ultimate aspiration is to deliver a complete system capable of translating large amounts of data from the field into meaningful information and impactful spraying commands to achieve the Green Deal goals.
Key Objectives:
KO#1: Innovate using intelligent (non-robotic) Data infrastructure and Digital Twins
KO#2: Integrate robotic (physical) solution for autonomous spraying
KO#3: Optimize technologies and demonstrate the Green Deal goals in real life environments
KO#4: Community building, synergies and results exploitation
The overall strategy of the project is based on the four interrelated objectives that were set out since the beginning of the project. For the execution of each of the objectives a plan of work was devised in such a way, as to ensure that each of the tasks and activities carried out will complement and pave the ground for the next one.
In the initial phase of the project, the Project Management Handbook and the Data Management Plan were developed. The Project Management Handbook serves as a comprehensive guide, outlining the management structures, methodologies, and procedures to ensure the project’s objectives are met efficiently. Accordingly, the initial Data Management Plan was developed to establish protocols for data handling, storage, and sharing while ensuring security and privacy.
Additionally, the project focused on analyzing industry needs and developing reference architectures by conducting a thorough Industry Needs & Requirements Analysis to initially understand the specific needs and challenges faced by the industry. These needs will be finalized during the forthcoming period. Also, the Smart Droplets Academy Program, Timeline & Activities was established to provide a comprehensive learning and development initiative for addressing these needs. Standardized architectures for industry applications were proposed and reported in Reference Architectures & Resources Mapping.
In WP3, a first functional prototype of the Smart Droplets’ Digital Platform and Digital Twin Intelligence is under development. The platform will be equipped with features (digital twin, AI for pesticide recommendation intelligence, and pest detection and canopy characterization) to simulate and analyze farm intelligence for optimized spraying application.
Accordingly, the components of the Autonomous Robotic Spraying System (WP4) are under development as well. Specifically, the consortium is designing a robust localization and 3D mapping process along with a multi- objective path planning in harsh environments. Additionally, Intelligent Spraying and Direct Injection Systems are developed to be used for optimized spraying applications through variable rate applications and robots among other settings.
Furthermore, during those first twelve months the Smart Droplets consortium also devised a plan on the dissemination and communication of the project results, defining the means and channels to be used, in order to showcase the commerciality of the Smart Droplets products and services right from the beginning. Communication tools such as the projects’ website, leaflets, brochures and fact sheets, were also produced. Additionally amongst the issues that were tackled during the first period was the strategy for the Intellectual Property Rights (IPR) that concerned the commercial exploitation of the project results and the Data Management Plan that dealt with issues of data collection, production and processing.
Smart Droplets project has been active since September 2022 and the overall progress is according to the planned tasks. The main goal of the project is to improve farming practices by integrating modern digital technologies. This effort is driven by the need to make farming more resource-efficient, environmentally friendly, and productive.
The primary goal of Smart Droplets will be accomplished by fulfilling the Key Objectives (KO) outlined below, which encompass the anticipated outcomes, facets of the work programme topic, and meeting designated Key Performance Indicators (KPIs). More detailed information of the specific objectives set from the beginning of the project is given in the section below.
Overall Objective: Advance both hardware and software capabilities during chemical applications for resource optimisation and minimisation of chemical waste. To accomplish this vision, this project will use already existing technologies (>TRL 7) developed within but not limited to the agricultural industry. Its ultimate aspiration is to deliver a complete system capable of translating large amounts of data from the field into meaningful information and impactful spraying commands to achieve the Green Deal goals.
Key Objectives:
KO#1: Innovate using intelligent (non-robotic) Data infrastructure and Digital Twins
KO#2: Integrate robotic (physical) solution for autonomous spraying
KO#3: Optimize technologies and demonstrate the Green Deal goals in real life environments
KO#4: Community building, synergies and results exploitation
Digital Platforms: Implemented algorithms for predictive maintenance and machine learning models for real-time equipment performance.
Digital Twins: Established a standardized model for asset management across all units.
Autonomous Machinery: Achieved integration of real-time data processing with autonomous vehicles.
Business Models: Developed and launched new business strategies for digital transformation initiatives.
Digital Twins: Established a standardized model for asset management across all units.
Autonomous Machinery: Achieved integration of real-time data processing with autonomous vehicles.
Business Models: Developed and launched new business strategies for digital transformation initiatives.