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Coordination of ICT and Robotics in Agriculture and Related Environmental Issues
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ICT-AGRI FUNDED PROJECTS

First call 2010
Seven projects are funded by the first ICT-AGRI Call for research projects in the field of ICT and robotics in agriculture. All projects are running over two years from spring 2011 to spring 2013.
Second call 2012
Eight projects are funded by the second ICT-AGRI Call for research projects in the field of ICT and robotics in agriculture. All projects are running over three years from 2013 to 2016.

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Advanced Monitoring of Tree Crops for Optimized Management (3D- Mosaic)
3D-Mosaic is targeting the automation of irrigation in orchards. Input requirements in an orchard show spatial and temporal pattern due to the variability of climate, soil and plant growth. On a tree-scale, irrigation needs will be evaluated considering the spatial distribution of the soil properties and of the apparent phenotypes using automated sensors and GIS.
Category: Research, Ongoing, Product, Robot, Software, Machine Learning.
Contact: Manuela Zude
Organisation profile: Leibniz Institute for Agricultural Engineering Potsdam-Bornim
Funded by ICT-AGRI

On the tree-scale, leaf area index, fruit load, fruit water content, and maturity-related pigmentation represent information vital for orchard management/irrigation decision making. Until now, these parameters have been underutilized due to lack of automation of their monitoring as well as evaluation of their feasibility. The target of 3D-Mosaic is to provide a reasonable automation concept for precision management of orchards. 3D-Mosaic Objectives are: o Data acquisition in orchards by autonomous platform o Monitoring of plant and fruit growth by means of automated sensors using geo-information system o Derivation of tree adapted management maps based on pre-knowledge of soil maps and actual plant data to improve the irrigation in model orchards o Verification of concept by field tests Partner from Denmark and Germany will supply the certified field robot platform that is ready for implementation into practice, partners from Switzerland and Germany contribute the newly developed 3D vision system, and partners from Italy and Germany share calibration knowledge and spectroscopy field experiences. Partners from southern and northern regions of EU collaborate within 3D-Mosaic and imply relevance of the tackled issue. The topic of the joint research is highly relevant throughout Europe due to its wide applicability in tree crop production systems with water management requirements (crops of the temperate and subtropical such as citrus, stone fruit, pip fruit, and viticulture).

Acknowledgement: Manuela Zude, ATB; Hans Werner Griepentrog, University Hohenheim; Stavros G. Vougioukas, Aristotle University of Thessaloniki; Riza Kanber, University of Cukurova; Alon Bengal, ARO; Dejan Šeatoviæ, ZHAW; Paolo Rozzi, Sintéleia; Thomas Anken, ART; Oliver Hensel, University Kassel; José Espinosa, Versas Consultores; Alessandro Torricelli, Politecnico di Milano
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Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV)
Autonomous vehicles are being increasingly adopted in agriculture to improve productivity and efficiency. For a vehicle to operate safely, environment perception and interpretation capabilities are fundamental requirements. The project focuses on the development of sensors and sensor processing methods to provide an vehicle with such ambient awareness.
Category: Research, Ongoing, Product, Robot.
Contact: Anders Petersen
Organisation profile: Danish Technological Institute, Centre for Robot Technology
Funded by ICT-AGRI

The obstacles that might be encountered in the field can be eparated into four overall categories that should be detected and handled in different ways: positive obstacles, negative obstacles, moving people/animals/obstacles, and difficult terrain. Further, obstacles may vary greatly from situation to situation, depending on type of crop, fruit, vegetable or plant grown, curvature of landscape as well as other factors. Owing to the variety of situations and problems that may be encountered, no sensor exists that can guarantee reliable results in every case. Any candidate sensor has its strengths and drawbacks. Therefore, a complementary sensor suite should be used to gain the best performance. The idea of this project is that of using different sensor modalities and multi-algorithm approaches to detect the various kinds of obstacles and to build an obstacle database that can be used for vehicle control. The project investigates the potential of four sensor technologies: (stereo) vision, radar, ladar and thermography. Existing state-of-the-art sensors, some previously developed by the partners themselves, will be modified and interfaced in such a way that they can be demonstrated in an agricultural context. The sensors will be mounted on an autonomous tractor and a data acquisition campaign will collect sensor data from a previously selected set of agriculturally relevant test scenarios. These data will provide the basic dataset for the development of novel sensor processing and sensor fusion techniques aiming to detect and classify obstacles in an agricultural environment.

Acknowledgement: DTI, Centre for Robot Technology (DEN), Cemagref, TSCF (FR), Fraunhofer, IAIS (GER), CLAAS Agrocom (GER), University of Salento (I)
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Geospatial ICT infrastructure for agricultural machines and FMIS in planning and operation of precision farming (GeoWebAgri)
The overall aim of the GeoWebAgri-project is to analyze and develop an ICT infrastructure for handling geospatial data and knowledge both in agricultural machines and farm management information systems (FMIS) and promote the introduction of this technology in European software and automation products for agriculture.
Category: Research, Ongoing, Product, Software, Online service.
Contact: Ilkka Seilonen
Organisation profile: Aalto University, School of Science and Technology, Faculty of Electronics, Communication and Automation
Funded by ICT-AGRI

The overall aim of the GeoWebAgri-project is to analyze and develop an ICT infrastructure for handling geospatial data and knowledge both in agricultural machines and farm management information systems (FMIS) and promote the introduction of this technology in European software and automation products for agriculture. The technology is studied particularly in the context of spatial data infrastructures (SDI) for the planning and operation of precision agriculture in arable farming. This overall objective can be divided into four specific objectives. The first objective is to specify an ICT infrastructure for handling geospatial data both in agricultural machines and FMIS as a continued development of current systems. This specification will be the baseline for subsequent work. The second objective is to confirm the viability of the challenging parts of the specified ICT infrastructure with proof of concept implementations. The third objective is to evaluate the impact of the possible application of the specified ICT infrastructure on farming objectives. A special focus in the evaluation is on reduced environmental effects through the use of precision agriculture in arable farming. The fourth objective is, based on the results of the project, to enhance the knowledge of European software vendors about the applicability and possible benefits of ICT for geospatial applications in agriculture.

Acknowledgement: Project partners: Aalto University (FI), MTT Agrifood Research Finland (FI), Rostock University (DE), University of Hohenheim (DE), Aarhus University (DK), Knowledge Centre for Agriculture (DK)
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Integrated robotic and software platform as a support system for farm level business decisions (ROBOFARM)
ROBOFARM aims to create a technology platform that integrates and harmonizes existing software and hardware technologies into a single system and makes use of robots equipped with sensors and active vision systems to automatically collect data from the field, feeding a farm management DSS and considering the agronomical, environmental and food safety aspects
Category: Research, Ongoing, Product, Software.
Contact: Maurizio Canavari
Organisation profile: Alma Mater Studiorum - University of Bologna, Dept. of Agricultural Economics and Engineering
Funded by ICT-AGRI

The research will integrate a hardware and software platform in a single system and in an innovative approach that makes use of robotic systems. The use of robots to detect and collect data is novel in terms of methodology and application. On the method side, differently from other approaches, the system will be able to infer complex situations and behavioral patterns by merging the contribution of several “simple sensors” distributed in the environment and carried around by the robot. On the application perspective, context awareness through distributed sensors will allow to recall information about data collected by way of middleware distributed control system. ROBOFARM activities build on previous research. The FutureFarm project (FP7, Meeting the challenges of the farm of tomorrow by integrating Farm Management Information Systems to support real-time management decisions and compliance to standards) provided a comprehensive guideline for the design of any information and management system. The OMNIAFARM software platform provide a sound basis to create the Farm Management Information Systems integrating a DSS in irrigation, fertilization, treatments and in the correct use of regulations, and adhering to the FutureFarm guidelines. The Hortibot project (Danish Ministry of Food, Agriculture and Fisheries, 2005-2008, j. no. 3412-05-01241) and the API project (Danish Ministry of Food, Agriculture and Fisheries, 2001-2003, j. no. 93S-2466-Å00-01367) developed data collection methods allowing monitoring of crop growth status and mapping of weed species populations.

Acknowledgement: Project partners: Alma Mater Studiorum University of Bologna (IT), Harper Adams University College (UK), Centre for Research and Technology – Thessaly (GR), Ege University (TR)
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open System for TRAcTOrs’ autonomouS Operations (STRATOS)
The main objective of the STRATOS project is to develop an open ICT hardware-software infrastructure enabling the partial automation of tractors and at the same time enhancing their operational safety and production efficiency, with the positive effects of reduced accident risk and environmental impact.
Category: Product, Machine, Software.
Contact: Cesare Fantuzzi
Organisation profile: University of Modena and Reggio Emilia, Department of Science and Method of Engineering (DISMI), Automation, Robotics and System Control Lab (ARSControl)
Funded by ICT-AGRI

STRATOS project target is to develop and demonstrate new functions enabled by ISOBUS technology (ISO 11783) that support a substantial improvement of the quality of the farming jobs. In particular the idea is to develop a technology based on ISOBUS compliant, wireless self-powered sensor network for the real time measurement of soil and harvester conditions. In this way, Task Controller (an ICT component defined by ISOBUS specification which supervises actively the farming job performed by the tractor) can optimize the whole tractor and implement operational modes to improve the farming job quality and safety of the overall systems. The project is structured in 5 Work Packages (WP). In WP1 the system specifications are defined, including system requirement analysis and system use case definition, WP2 is devoted to system development and deployment, while WP3 is aimed at system validation and test. The WP4 will take care of the dissemination and exploitation plan, while the last WP is for management. The consortium is composed by (1) University of Modena and Reggio Emilia (UNIMORE, Coordinator), (2) Riga Technical University, Faculty of computer science and information Technology, Division of computer networks and systems technology (UNIRIGA), (3) University of Lugano, Advanced Learning and Research Institute (ALARI), (4) Institute for Agricultural and Earthmoving Machines-National Research Council (IMAMOTER), (5) Technion-– Israel Institute of Technology Control Systems in Environmental Water and Agriculture Laboratory (TECHNION) and (6) EIA Electronics a Belgian company.

Acknowledgement: (1) University of Modena and Reggio Emilia (2) Riga Technical University, Faculty of computer science and information Technology, (3) University of Lugano, (4) Institute for Agricultural and Earthmoving Machines-National Research Council (5) Israel Institute of Technology Control Systems in Environmental Water and Agriculture Laboratory (6) EIA Electronics.
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Optimizing performance and welfare of pigs using High Frequent RFID and synergistic control on individual level (PIGWISE
An ICT based tool will be developed that can be used to monitor performance and welfare of pigs at the individual level in order to detect problems at an early stage and hence preventing economical losses. Computer-aided analysis of individual animals’ data enables to develop an Early Warning System for potential drops in performance or potential health.
Category: Research, Ongoing, Product, Machine, Robot, Software, Software.
Contact: Engel Hessel
Organisation profile: University of Göttingen, Faculty of Agriculture Sciences, Department of Animal Sciences, Division: Process Engineering
Funded by ICT-AGRI

This will be done by combining an innovative individual online-monitoring system based on HF RFID, camera vision technology and software. Computer-aided analysis of individual animals’ data enables to treat each animal as a production unit, define animal based threshold values and hence develop an Early Warning System (EWS) for potential drops in performance or potential health. Individual feeding behaviour of group-housed pigs will be monitored by means of HF RFID. A camera vision based identification system will be used for validation of the HF RFID technology. First the hardware and software components of the RFID and sensor system will be integrated through a unique infrastructure. Thereafter feeding behaviour data of individual pigs will be recorded online. Normal variation within pigs and between pigs in RFID-parameters will be defined depending on the pigs’ age and the environmental factors and transformed into performance and welfare related parameters. Using the RFID parameters algorithms will be developed to detect deviations in the RFID data. Based on these algorithms, an EWS can be developed. The EWS gives an alarm if the displaced feeding behaviour of an individual pig or of a group of pigs differs from the expected feeding behaviour. Finally the EWS will be validated concerning its Sensitivity and Specificity under practical conditions.

Acknowledgement: Project partners: University of Goettingen, Division: Process Engineering, Germany Katholieke Universiteit Leuven, Division: Mechatronics, Biostatistics and Sensors, Beligum Institute for Agricultural and Fisheries Research (ILVO) – Agricultural Engineering, Belgium Engineering College of Aarhus, Denmark Istituto Superiore Mario Boella (ISMB) , Italy
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Preparing for the EU Soil Framework Directive by optimal use of Information and Communication Technology across Europe (Predictor)
Soil quality is threathened due to traffic with modern agricultural machinery. The PredICTor project has two main deliverables, i) an online decision support tool for evaluating an intended field traffic situation, and ii) an online tool for creating European-wide maps of the wheel load carrying capacity for combinations of tyres, soils and water contents.
Category: Research, Ongoing, Product, Software, Online service.
Contact: Per Schjønning
Organisation profile: Aarhus University, Faculty of Agricultural Sciences
Funded by ICT-AGRI

Soil has a mechanical strength that is dependent on soil type and soil water content. Soil compaction occurs if soil stress imposed by machinery exceeds soil strength. Soil compaction creates persistent effects on several soil functions in subsoil layers, including environmental footprints and crop production. Soil machinery producers are showing increased interest in ICT solutions allowing for optimization of field operations like soil tillage and traffic. The EU has launched a proposal for a Soil Framework Directive for soil protection, including soil compaction as a major threat to a sustained soil quality. The project includes four workpackages addressing i) improvement and combination of state-of-the-art models for the soil compaction process with pedotransfer functions for estimating soil strength and stress propagation patterns in the soil, ii) preparation of data on soil properties and meteorogical observations for direct access by the models, iii) programming of the support tool in an internet environment, emphasizing end-user needs (e.g. icon-based selection of machinery and with ‘go’/’stop’ advice for a planned traffic situation), and iv) online display of European-wide maps of the wheel load carrying capacity for user-selected combinations of soil water regime, tyre type and tyre inflation pressure.

Acknowledgement: PredICTor project partners: Aarhus University, DK Copenhagen University, DK Institute for Agri Technology and Food Innovation, DK Agroscope Reckenholz-Tänikon Research Station ART, CH Swiss College of Agriculture, CH Helsinki University, SF MTT Agrifood Research Finland, SF

References
Risk assessment and effects of soil compaction: Research chains at work, Schjønning et al, 2012, Page 13-16 of: Alakukku, L., Kymäläinen, H-R. and Pienmunne, E. (Eds.) Soil compaction – Effects on soil functions and strategies for prevention. Proceedings, NJF-seminar 448, Helsinki, Finland, 6-8 M
Terranimo® - a web based tool for evaluating soil compaction: Model design and user interface, Lassen, P. et al., 2012, Page 83-86 of: Alakukku, L., Kymäläinen, H-R. and Pienmunne, E. (Eds.) Soil compaction – Effects on soil functions and strategies for prevention. Proceedings, NJF-seminar 448, Helsinki, Finland, 6-8 M
Terranimo® - a web-based tool for evaluating soil compaction: Machinery-included stresses versus soil strength, Stettler, M. et al., 2012, Page 87-90: Alakukku, L., Kymäläinen, H-R. and Pienmunne, E. (Eds.) Soil compaction – Effects on soil functions and strategies for prevention. Proceedings, NJF-seminar 448, Helsinki, Finland, 6-8 Marc
Rules of thumb for minimizing subsoil compaction, Schjønning, P., Lamandé, M., Keller, T., Pedersen, J. & Stettler, M., 2012, Soil Use and Management
Terranimo TEST version, PredICTor Project Consortium, 2012, Select 'Terranimo', 'Model interface', 'Standard scenario'


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