Due to a lack of a holistic approach combining physical and digital assets for optimal field performance and minimum environmental impact, AI models, data and autonomous robotic systems in crop care tasks have not reached a mature technological level. The conventional spraying methods result in excessive pesticide and fertilizer use, posing severe environmental impact - being responsible for soil, water and air pollution, and harming non-target plants, insects, animals and humans. Smart Droplets’ main objective is to advance both hardware and software capabilities to deliver a holistic system capable of translating large amounts of data into meaningful information and impactful spraying commands on the field. To demonstrate substantial impact on the Green Deal, Smart Droplets will implement Autonomous retrofit tractors with Direct Injection System (DIS) for intelligent spraying - avoiding exposure of farmers to hazardous chemicals. Through the combination of high-level technologies (>TRL 7), Smart Droplets adopts a hybrid approach for spraying operations, combining Data/AI/Digital Farm Twin technologies designed to translate data into actionable information, and real-time data collected from Field demonstrators evaluating and demonstrating optimised technologies in the real environments. Smart Droplets will exploit synergies with relevant stakeholders, and intensify Community & Capacity building through dedicated training programs designed for non-expert users of AI, data and robotics systems. The Smart Droplets Consortium consists of all agricultural AI, data and robotics value chain actors, and is well balanced in terms of expertise, entity type, and geographical distribution necessary to meet its objectives. Smart Droplets will demonstrate how autonomous robotic platforms, innovative spraying, digital twin and AI models, can deliver environmental, economic, regulatory, business, scientific, and societal benefits, assisting in the achievement of Green Deal goals.

The main objective of ARGONAUT is to develop an effective and easily accessible AI digital tool that accurately calculates the environmental and climate impact from bio-based products across the entire value chain (from cradle to grave) using language models from global literature based on LCA principles and allows for easy and secure tracking through a digital passport based on blockchain technology. This tool will also include a decision support tool that uses this data to map out different alternatives for the value chain and their environmental impact thereby facilitating better and more sustainable decision making. ARGONAUT will contribute to the integration of key emerging digital technologies (AI and blockchain) and an environmental assessment methodology (LCA) to create a reliable tool able to assist small and medium-sized producers to navigate the complex bio-product landscape with enough relevant information, security guarantees regarding the privacy of their data and in a user-friendly way capable of closing knowledge gaps and thereby of reaching to a wider range of producers. ARGONAUT will contribute to the implementation of the EU’s Ecodesign for Sustainable Products Regulation and allow for an accurate depiction of the environmental impact of such bio-based products thereby supporting the development of more sustainable value chains and the transition to a circular bioeconomy across the EU.

InterConnect envisages to contribute for the democratization of efficient energy management, through a flexible and interoperable ecosystem where demand side flexibility can be soundly integrated with effective benefits to end-users. In fact, over the last few years several projects and technology providers have come up with solutions that allow every energy user to have awareness and control over his appliances, but there has always been a major issue with interoperability. End-users should be able to choose and change their technology providers, without having to replace their installation, every time they feel this need and still be able to adopt sustainable behaviour and benefit from technological advances. In the energy sector, a steep move towards digital is occurring and becoming tremendously user-centric and market-driven. The system dimension is significant, as the number of energy service providers is increasing thanks to favourable regulatory environment and technology advancements for monitoring and control. This is the reason why this consortium integrates relevant partners from all the representative stakeholders in this new energy paradigm. Specific competences in ICT, IoT, energy, data science, software, were included and the full value chain, from R&D institutions, manufacturers, DSO, retailers, IT providers, and energy users is represented. To guarantee a higher Europe-wide impact, several relevant associations related with ICT and energy are also involved. To achieve a significant dimension, 7 large scale pilots, in different countries and with different end-users, are foreseen to guarantee representativeness and dimension in terms of number of appliances and services. The overarching objective of these pilots is to demonstrate a real digital market environment over electrical systems with significant amounts of DSF, reducing operational and investment costs that will benefit energy end-users and help EU achieve its energy efficiency objectives.

The main objective of the project is to design and implement a parameterized, knowledge-based, multi-target food sensitive mini-portable system, with heterogeneous micro-scale photonics for on-the-spot food quality sensing and shelf-life prediction. In particular, the miniaturized smart integrated system will be able to detect food hazards, spoilage (incl. early sign of spoilage) and food fraud through the combined bio-chemical data analysis and additionally will be able to perform food components/additives analysis, food identification and prediction of food shelf-life. The following use case will be addressed during the project: Use case 1: Detection of mycotoxins in various grains and nuts. Aflatoxins detection. A simple, convenient ultraviolet test makes it possible to detect the possible presence of aflatoxin. Use case 2: Detection of early sign of spoilage and spoilage in fruits, vegetables, meat, fish: combined with estimation on product expiration date. Use case 3: Detection of food fraud: Adulteration of alcoholic beverages, oil, milk and meat. 3 sensor devices will be integrated in the miniaturised smart sensor node: i) a MEMS-based near IR spectrometer (950-1900 nm), ii) a UV-VIS spectrometer (450-900 nm) and iii) a micro-camera. Moreover 3 light sources will also be integrated to support the sensing functionality: i) UV-LED, ii) white LED and iii) a miniaturised IR emitter. Smart signal processing of the spectrum images will be performed by an advanced microcontroller, integrated in the sensing device. The data will be communicated to a smartphone device, where the spectroscopy analysis will take place with the help of a cloud-base application connected to a reference database. Advanced detection algorithms will be deployed both in the level of cloud and the smartphone application. PhasmaFOOD system will enable common consumers for on the spot food quality sensing and shelf-life prediction.

Fruit cracking is a peel disorder, limiting fruit quality and yield. The phenomenon occurs mainly in the pre-harvest stage and affects many types of fruit. External conditions like climatic and environmental conditions, and orchard management play important roles in increasing the incidence of the phenomenon, this CrackSense will condict reasers in IL, FR, DE, LT, EL. CrackSense aims to address the problem of fruit cracking in citrus, pomegranate, table grapes and sweet cherries by developing and upscaling sensing technologies that will provide real-time sensor data through piloting activities. The sensor data collected will be upscaled into EU-wide data sets which will encompass Earth Observation Data (provided by Copernicus, e.g., Sentinel) and other data sets reflecting on environmental conditions. This data will be used to monitor agricultural production of the studied crops and enable farmers and growers’ efficient management of their resources and sustainability of their actions. By improving the agricultural production of these crops, CrackSense will as well help in creating a model for other agricultural crops. Furthermore, CrackSense will address the critical need for efficient and real-time monitoring of agri-environmental conditions because these conditions have a great influence on agricultural production. By deploying sensing technologies, CrackSense will enable high throughput assessment of cracking incidence risk at fruit, tree, field, and regional scale to mitigate the negative effects of the cracking phenomenon. By reducing 1/2 of the yield losses due to cracking, the use of the Integrated CrackSense Solution will result in 50% higher financial gain for farmers and growers. Integrated CrackSense Solution will enable farmers and growers to optimise their cost efficiency and generate pathways for more income. Fostering complementarities between partners will enable us to fulfil our goals to bring state-of-the-art CrackSense Solution to end users.