Successful Applicants of 1st PUSH Open Call for Innovation Development

1st PUSH Open Call for Innovation Development 

The 1st ICAERUS PUSH Open Call for Innovation Development is underway. The following five awarded sub-projects will work towards developing drone-based ideas, concepts, and prototypes that can be introduced to the market and contribute to drone innovation in agriculture and rural areas.

AGRICLOUD- School of Sky Farmers (SKYFAR)
Organisation: AGRICLOUD

SKYFAR- School of Sky Farmers  addresses the design, development, and marketing of a cross-training program on drone piloting and managing data developed by drones, needed to valorize better the information that IoT is offering to the farmers (drone piloting, new technologies (Ground Penetrating Radar – GPR and Light Detection and Ranging LiDar) and GIS usage in agriculture). SKYFAR will allow farmers and agri-entrepreneurs to integrate drone technology in their daily work. Moreover, an interdisciplinary approach needs to be employed in order to bring to fruition the entire cycle and encourage a different approach in terms of educational tools and framework based on the professional profile of the end-users (farmers and service providers for farmers). 

The educational program (curriculum and educational logistics) aims to boost the quality of services and thus the trust in drone-based agri services. More than that, this service will contribute to the green transition of Romanian agriculture in a time where decrease in subsidies is beginning to emerge as an issue. AgriCloud is already present in Romanian agriculture, bringing IoT and IAS (Input as a service) to farms, thus increasing sectoral competitiveness as well.  By implementing the educational program, i.e., by developing the curriculum and by delivering the training, AgriCloud aspires to become a leader in the field.

Additionally, the timing of SKYFAR is of particular importance as the National Strategic Regional Framework and the implementation of AKIS in Romania are both at an early stage, considering the point in time of the current Programming Period, as this means that a substantial number of future professionals that can offer integrated services – from piloting to decision-making will benefit from the implementation effort

Agrobit s.r.l

The AGROTWIN project aims to exploit 3D point clouds (big data) generated by consumer-grade RGB drones in order to develop a Decision Support System (DSS) based on innovative AI computer vision algorithms, that automatically analyse vineyards digital twin and assess for canopy biometrics and field parameters, to create and prescription maps for optimized variable rate pesticide treatments. The proposed DSS will help farmers to reach the EU Green Deal targets, which aim to reduce the use of pesticides by 50% by 2030, decreasing economic, social, and environmental impacts in agriculture.

Secure and High Integrity EGNSS enable drone system (SHIELD)
Organisation: Obsidian Innovation Institute

SHIELD focuses on developing an advanced drone system component, SHIELD, powered by the European Global Navigation Satellite System (EGNSS) to enhance security, reliability, and precision. By utilizing the superior attributes of the Galileo and European Geostationary Navigation Overlay Service (EGNOS) systems, SHIELD intends to tackle key security challenges in drone operations, providing encrypted, high-integrity services for various sectors like remote sensing, agriculture, emergency response, defense, and logistics. Its integration with EGNSS promises navigation of higher accuracy and reliability by reducing errors due to atmospheric disturbances.

The project is in line with the EU’s objectives of promoting EGNSS usage and anticipates compliance with future regulations, thereby contributing to the standardisation of EGNSS-enabled drone technology. Research and development activities encompass software/hardware enhancements, testing, EGNSS integration, and cybersecurity improvements.

The Obisidian Innovation Institute (OBDSIDIAN)’s team is committed to transforming drone applications within the sectors like Agriculture, Security, Surveillance and Surveying by resolving crucial security and integrity problems, advancing European drone technology, and promoting safer and more efficient drone operations. The SHIELD project holds transformative potential for the drone industry, addressing significant security and integrity concerns while enhancing European drone technology for safer and more efficient operations.


The Universal UAV Civil Drone for AI-boosted Methane Gas Inspections
Organisation:Schweitzer Ingenieurgesellschaft mbH

Schweitzer Ingenieur (SI) GmbH’s Civil Drone Project Universal UAV, combines high-speed logging and high payload capacity. These drones are built applying aviation-grade composite materials and use sophisticated systems such as professional autopilots, mission software, including, drone system data terminal, radio and satellite data links, and mobile ground stations with professional control stick for Fly-by-Wire steering the drone. 

SI’s Canadian partner, Perspectum Drone Inspection Inc., is a drone flight service provider and developer of an innovative AI-boosted gas camera focused on detecting Methane gas. Having its own test range, including oil and gas facilities PDI can optimize this gas camera so that it receives an AI-boosted Gas Camera operated under an AMEP contact with PDI’s copter drones to perform Methane gas leakage inspection of oil and gas facilities in Alberta/Canada. 

The gas camera system is presently used for stationary inspection tasks above gas facilities, showing its superior performance in terms of accuracy. SI and PDI aim to extend the application of this innovative gas camera system to long-range leakage inspection missions in Europe and Canada. This requires the use of fixed-wing drones such as SI’s Universal compared to Copler drones, the gas camera Universal UAV has to be optimized to enable the detection of small gas leakages. Both features will be demonstrated within the ICAERUS project using a scaled Universal AV demonstrator along with Perspectum’s AI-boosted Cas Camera. 

Organisation: TAAL s.r.l

Sensor 2.0 aims to combine Computer Vision (CV) technology and drones to develop a plant recognition system capable of identifying plant types, assessing their current state, and detecting any potential diseases. The project will utilise the drone, CV libraries, artificial intelligence algorithms, and relevant plant identification datasets to achieve these objectives, developing a system wherein sensors (cameras) placed on the drone capture images (data) and transmit them to a cloud infrastructure housing an AI system. This AI system performs the necessary computations and returns the processed results. 

The first objective of this proposal is to realize a solid and accurate plant recognition system that may analyse images of plants, determine their species and assess their health status. Firstly, by employing advanced CV techniques and combining them with plant species databases, the system will be able to identify various plant types with a high degree of precision and efficiency. After the plant identification, the system will also evaluate the health status of plants. By leveraging AI algorithms and integrating with plant disease databases, the drones-based system will be capable of detecting and diagnosing any potential diseases in the plants. This functionality will enable early detection and intervention, leading to improved plant health management and crop yield optimization. The expected outcomes of this project include:

  1. Efficient and accurate plant recognition.
  2. Real-time plant health monitoring and assessment.
  3. Enhanced agricultural productivity.

This project aims to leverage cutting-edge technologies and knowledge to develop a powerful tool that positively impacts various sectors, especially in rural areas, relying on plant health assessment.

700 400 ICAERUS

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