Trends in Agricultural Robots. A Comparative Agronomic Grid Based on a French...Davide Rizzo
Equipment innovation is one of the crucial levers for the improvement of economic, societal and environmental performances of agriculture. In particular, precision farming is expected to be among the 10 technologies that could change our lives. Amid the different technologies enabling a greater precision of agriculture, robotics and sensors could radically change the way of farming. Automatic machines collecting and managing data, eventually feeding a bigdata approach, could provide new tools for fine-tuning farmers’ decision making and help them in mastering the environmental footprint of agriculture. Nevertheless, what is a robot from the agricultural point of view? What are the solutions under development or on the market? How to compare them? The disruptive transformation of the agricultural machinery market requires the definition of new landmarks, especially for agronomists who are facing new opportunities and technologies. We present here the early results of a comparative overview realized by a group of students in agronomy and specializing in agricultural equipment and new technologies at UniLaSalle. The five students were asked to provide figures and a summary of the agricultural robots available in France, either on the market or upcoming. Firstly, they defined what a “robot” is. They referred to Coiffet (2007) who considers “robot” a machine for the human assistance executing a work or a physical task, either as a tool handled during the execution of the task or capable to perform the work without human intervention. Accordingly, the database includes only agricultural machines fulfilling at least two out of the three following criteria: the capability to execute a task, the operational flexibility, the self-adaptability to the working environment. Three robot classes were identified (decision, assistance or substitution) further classified in two agricultural domains and related operational subdomains: crop production (including permanent crops, horticulture, field crop and other crops) and breeding (including cattle, poultry, and pig). Out of a 4 months work, the database finally contains 98 robots from 70 enterprises, with full specifications retrieved from more than 300 websites and 7 French agricultural journals, as well as through the participation to some specialized fora. For comparison, the “Agricultural Robots” report by Tractica highlighted 149 profiles over a comparable time period. Drawing upon a solid background in agronomy, the students analysed the farming operation performed by the listed robots, with a focus on the vehicle-soil interface. Altogether, the design and development of this database can provide agronomists with an up-to-date comparative grid of the existing and upcoming agricultural robots. Identifying clear landmarks in the high pace robot landscape will enhance the agronomic evaluation and enable a clearer understanding of robot relevance for farmers.
Keynote for the 9th International Scientific Conference
RURAL DEVELOPMENT 2019: Research and Innovation for Bioeconomy, 26-28th September 2019 Vytautas Magnus University | Akademija, Kaunas district, Lithuania http://www.ruraldevelopment.lt
This talk provides an overview of the multiple, sometimes contrasting perspectives on agtech players and their role for future agriculture and challenges for education and training (in France).
Strip-Till for Fine Seedbed Preparation in Silty Soil Davide Rizzo
The sustainable intensification process has though two main barriers: the learning curve to master new techniques and the cost of equipment suited for the new practices. This communication aims to discuss a project of strip-till design following an innovation system approach. First, we present the agronomic challenge and our approach for a custom supply development. Then, we discuss the relevance of our some early outcomes for the wider goal of sustainable intensification of crop production.
Farmer-oriented innovation: outcomes from a first bootcampDavide Rizzo
Suggested citation: Dantan J, Rizzo D, Fourati F, Dubois M, Jaber M (2018) Farmer-oriented innovation: outcomes from a first bootcamp. 3rd Abbé Grégoire Innovation Days, April 3rd Paris.
+ + + + + + + We have explored the construction of solutions around farmers' questions about the culture of knowledge sharing (Open Source & Open Hardware Initiatives). To tackle such challenges, UniLaSalle has almost finished building the AgriLab® platform. AgriLab® is a “new generation” laboratory which is, among others, a rapid prototyping platform in digital technologies (robotics, collaboration platforms, big data processing and decision support tools) and in agro-equipment. Dedicated to open innovation, this platform promotes the culture of knowledge sharing. It is part of the worldwide movement of free knowledge exchange for a more sustainable agriculture.
Following, we will present and discuss the major outcomes from a first Bootcamp, as an example of a farmer-oriented event designed upon the open-source IoT in smart farming.
Modern Energy Services for Modern Agriculture Potentials and challenges of smallholder agriculture
Dorothea Otremba
Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH
Programme Poverty-oriented Basic Energy Services (HERA)
Presentation at the International Conference on Re & Agri
Tunis, Tunisia, 2-4th December 2014
Trends in Agricultural Robots. A Comparative Agronomic Grid Based on a French...Davide Rizzo
Equipment innovation is one of the crucial levers for the improvement of economic, societal and environmental performances of agriculture. In particular, precision farming is expected to be among the 10 technologies that could change our lives. Amid the different technologies enabling a greater precision of agriculture, robotics and sensors could radically change the way of farming. Automatic machines collecting and managing data, eventually feeding a bigdata approach, could provide new tools for fine-tuning farmers’ decision making and help them in mastering the environmental footprint of agriculture. Nevertheless, what is a robot from the agricultural point of view? What are the solutions under development or on the market? How to compare them? The disruptive transformation of the agricultural machinery market requires the definition of new landmarks, especially for agronomists who are facing new opportunities and technologies. We present here the early results of a comparative overview realized by a group of students in agronomy and specializing in agricultural equipment and new technologies at UniLaSalle. The five students were asked to provide figures and a summary of the agricultural robots available in France, either on the market or upcoming. Firstly, they defined what a “robot” is. They referred to Coiffet (2007) who considers “robot” a machine for the human assistance executing a work or a physical task, either as a tool handled during the execution of the task or capable to perform the work without human intervention. Accordingly, the database includes only agricultural machines fulfilling at least two out of the three following criteria: the capability to execute a task, the operational flexibility, the self-adaptability to the working environment. Three robot classes were identified (decision, assistance or substitution) further classified in two agricultural domains and related operational subdomains: crop production (including permanent crops, horticulture, field crop and other crops) and breeding (including cattle, poultry, and pig). Out of a 4 months work, the database finally contains 98 robots from 70 enterprises, with full specifications retrieved from more than 300 websites and 7 French agricultural journals, as well as through the participation to some specialized fora. For comparison, the “Agricultural Robots” report by Tractica highlighted 149 profiles over a comparable time period. Drawing upon a solid background in agronomy, the students analysed the farming operation performed by the listed robots, with a focus on the vehicle-soil interface. Altogether, the design and development of this database can provide agronomists with an up-to-date comparative grid of the existing and upcoming agricultural robots. Identifying clear landmarks in the high pace robot landscape will enhance the agronomic evaluation and enable a clearer understanding of robot relevance for farmers.
Keynote for the 9th International Scientific Conference
RURAL DEVELOPMENT 2019: Research and Innovation for Bioeconomy, 26-28th September 2019 Vytautas Magnus University | Akademija, Kaunas district, Lithuania http://www.ruraldevelopment.lt
This talk provides an overview of the multiple, sometimes contrasting perspectives on agtech players and their role for future agriculture and challenges for education and training (in France).
Strip-Till for Fine Seedbed Preparation in Silty Soil Davide Rizzo
The sustainable intensification process has though two main barriers: the learning curve to master new techniques and the cost of equipment suited for the new practices. This communication aims to discuss a project of strip-till design following an innovation system approach. First, we present the agronomic challenge and our approach for a custom supply development. Then, we discuss the relevance of our some early outcomes for the wider goal of sustainable intensification of crop production.
Farmer-oriented innovation: outcomes from a first bootcampDavide Rizzo
Suggested citation: Dantan J, Rizzo D, Fourati F, Dubois M, Jaber M (2018) Farmer-oriented innovation: outcomes from a first bootcamp. 3rd Abbé Grégoire Innovation Days, April 3rd Paris.
+ + + + + + + We have explored the construction of solutions around farmers' questions about the culture of knowledge sharing (Open Source & Open Hardware Initiatives). To tackle such challenges, UniLaSalle has almost finished building the AgriLab® platform. AgriLab® is a “new generation” laboratory which is, among others, a rapid prototyping platform in digital technologies (robotics, collaboration platforms, big data processing and decision support tools) and in agro-equipment. Dedicated to open innovation, this platform promotes the culture of knowledge sharing. It is part of the worldwide movement of free knowledge exchange for a more sustainable agriculture.
Following, we will present and discuss the major outcomes from a first Bootcamp, as an example of a farmer-oriented event designed upon the open-source IoT in smart farming.
Modern Energy Services for Modern Agriculture Potentials and challenges of smallholder agriculture
Dorothea Otremba
Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH
Programme Poverty-oriented Basic Energy Services (HERA)
Presentation at the International Conference on Re & Agri
Tunis, Tunisia, 2-4th December 2014
Powerpoint designed for children ages 8-10. This is just a basic overview of the rainforest layers and some of the animals that live in the rainforest.
This project was carried as a semester project requirement for CSC 522 Automated Learning & Data Mining.
The project focuses on predicting forest cover type in the 4 Wilderness Areas of Roosevelt National Park located at Colorado.
The data for the project was obtained from Kaggle (it is also hosted on UCI repository under the name "forest cover type").
We obtained incremental improvement with every new classification technique we tried and simultaneously our Kaggle ranking also went up.
In this persentation I give a short description about ecology and the history of it. I also show the ecological crisis as well as environmental situation for ethical and social awareness.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
CoO + GI2015 ppt_mayer ict for a sustainable agriculture - status and missingIGN Vorstand
15. Sächsisches GI/GIS/GDI Forum und Club of Ossiach Workshops,
Dresden: 15. September 2015
ICT FOR A SUSTAINABLE AGRICULTURE AND FORESTRY STATUS AND MISSING
Walter H. MAYER, CEO PROGIS / Treasurer of CoO
APPLICATION OF BIG DATA IN ENHANCING EFFECTIVE DECISION MAKING IN AGRICULTURA...Sjaak Wolfert
The agriculture production system increasingly becomes data-driven and data-enabled based on the cyber-physical management cycle. This paper describes several IoT-applications of the EU-funded IoF2020 project in which data and data-sharing plays a crucial role. It provides an integrative framework aiming at cross-fertilisation, co-creation and co-ownership of results. Technical integration, business support and ecosystem development are key mechanisms to realize this.
Powerpoint designed for children ages 8-10. This is just a basic overview of the rainforest layers and some of the animals that live in the rainforest.
This project was carried as a semester project requirement for CSC 522 Automated Learning & Data Mining.
The project focuses on predicting forest cover type in the 4 Wilderness Areas of Roosevelt National Park located at Colorado.
The data for the project was obtained from Kaggle (it is also hosted on UCI repository under the name "forest cover type").
We obtained incremental improvement with every new classification technique we tried and simultaneously our Kaggle ranking also went up.
In this persentation I give a short description about ecology and the history of it. I also show the ecological crisis as well as environmental situation for ethical and social awareness.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
CoO + GI2015 ppt_mayer ict for a sustainable agriculture - status and missingIGN Vorstand
15. Sächsisches GI/GIS/GDI Forum und Club of Ossiach Workshops,
Dresden: 15. September 2015
ICT FOR A SUSTAINABLE AGRICULTURE AND FORESTRY STATUS AND MISSING
Walter H. MAYER, CEO PROGIS / Treasurer of CoO
APPLICATION OF BIG DATA IN ENHANCING EFFECTIVE DECISION MAKING IN AGRICULTURA...Sjaak Wolfert
The agriculture production system increasingly becomes data-driven and data-enabled based on the cyber-physical management cycle. This paper describes several IoT-applications of the EU-funded IoF2020 project in which data and data-sharing plays a crucial role. It provides an integrative framework aiming at cross-fertilisation, co-creation and co-ownership of results. Technical integration, business support and ecosystem development are key mechanisms to realize this.
Beyond Seminars - Deep Learning for fusion of Sentinel-1 and Sentinel-2 data ...ENVISION H2020
Iason Tsardanidis presents in the BEYOND Centre his work on ENVISION H2020 project regarding Deep Learning for fusion of Sentinel-1 and Sentinel-2 data and grassland mowing detection to promote peer-to-peer learning between the various teams of BEYOND!
Think Piece presented at the “ICTs transforming agricultural science, research and technology generation” Workshop - Science Forum 2009, 16–17 June, Wageningen, The Netherlands
The presentation makes the case for "tree-rich" agriculture and pastoralist systems in Niger - and the Sahel. It explores carbon financing for development of governance arrangements.
An overview of weeding by robots – focus on European solutionsDavide Rizzo
This presentation addressed an overview of the European context, mowing towards data-intensive farming, driven by the agfood sector. It is an invited presentation in the framework of a meeting coordinated by Matthew Cutulle (Clemson University) for a Specialty Crop Research Initiative (SCRI) planning grant about Robotic Weed Control in Specialty Crops. The meeting was organized as a side event during the Southeast Regional Fruit and Vegetable Conference. The presentation provides an overview of European trends on the topic, with a focus on the French institutional perspective aiming at the support and development of agricultural robotics to face the lack of labour and the willingness to phase out glyphosate. In this context, the RobAgri association was presented. The last part lists some sources of information about agricultural robotics, with a list of European sources of information on agricultural robotics and automation. The presentation ends with a list of robot examples that were compared from the agronomic point of view.
Agro IR 4.0-smart and next generation agro-farming-Fab labs to make anythingAbulHasnatSolaiman
Agriculture 4.0 is a term for the next big trends facing the industry, including a greater focus on precision agriculture, the internet of things (IoT) and the use of big data to drive greater business efficiencies in the face of rising populations and climate change. Makerspaces or Fab labs around the world can contribute in big margin to make prototypes reducing cost and makerspaces will be actions towards IR 4.0 in Bangladesh
Similar to Integrated information systems for farmers and advisors as well as vertical and horizontal chain partners and its benefits (20)
IAALD 2010 Closing Session Report: Innovations in Biodiversity Information W...IAALD Community
Report to the Closing session from the 'Innovations in BiodiversityInformation Workshop' at the 2010 IAALD World Congress - 26-29 April 2010, Montpellier, France
IAALD 2010 Closing Session Report: Targeted Information Products and ServicesIAALD Community
Report to the Closing Session from discussions on ’Targeted information products and services’ at the 2010 IAALD World Congress - 26-29 April 2010, Montpellier, France
The state and exchange of agricultural scientific and technical information i...
Integrated information systems for farmers and advisors as well as vertical and horizontal chain partners and its benefits
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5. USER-INTERFACE AND EXPERT-INFO WHERE WHEN WHAT patents pend. EXPERT-INFO : machines,crops, fertilizer, herbicide, methods, …. AGRICULTURE FORESTRY EXPERT-INFO : machines, trees, growth-tables,methods, …. patents pend. EXPERT-INFO : torrent, mudflow, drought, flood, avalanche, rockfall, … ENVIRONMENT patents pend. patents pend. location time information
6. Forest inventory (2 models) Forestry management/logisic Utility management (water, .…) Sensor integration (meteorology, Sensors for irrigation, machines Logistics and order processing Precision & Virtual Farm/Forest Land consolidation, Carbon calc. Environment- & risk management GIS & thematic mapping – region Documentation & Traceability Nutrient -(energy-, CO2- )balance Field profit margin calculation GIS & thematic mapping–farm (EU) subsidy claim (IACS/LPIS) AGRICULTURE REGIONAL APPLICATION FORESTRY Bottom up Top down REGIONAL SERVER Forestry- management village management river SERVER utility management river basin management farm management for farmers / advisors RURAL AREA MANAGEMENT MOA GlobalGAP FSC, PEFC Food & wood chain Sawmill Environment System Logistics PF System Trust Centre countrywide Horizontal Applications Vertical Applications HORIZONTAL & VERTICAL APPLICATIONS state summary country summary district summary regional summary Farmers and advisors level BMR BMR
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10. Transfer data: from office to harvester to loader or forwarder to truck, factory Office - Dispatcher Harvester GPRS/UMTS GPS Truck INTEGRATE AGRO-FOREST LOGISTIC Mobile Office Largest EC project: 45 cooperatives, using 100+ harvesters with mobGIS handling 100K+ datasets for 40.000 farmers on 40.000km² – all online with update all 30 seconds! Consumers, industry and trade are the driving forces, but agro-forest complex has to accept these challenges Loader/Forwarder
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12. PRECISION FARMING DETAILS I Vectormap: track Track and MS-BingMap Soil analysis - (or RapidEye-) -map Fertilisation contract
13. PRECISION FARMING DETAILS II Fertiliserer map with kg Tools for modification Harvest map Harvest + track map Profit contribution HUBER MOSER MAIER VIRTUAL FARMING Return minus costs = marginal income / m² or farmer = detailed result map and calculation per farmer KARL FRITZ
26. Wood & Timber CO2 - Sequestration Water quality, -storage, -supply Source of Bio-Energy Recreation Protection against Natural Hazard Local Climate Air qualiy Multiple Forest (agriculture) Functions
38. Intersection Parcels - Evaluation Digitizing of the evaluation Topology of value classes Intersection with the parcels Total value of each land owner
41. Waarnemen Global Applications of SEBAL O 2 , CO 2 ,H 2 O: three info-layers RapidEye: Chlorophyl map Organic matter map TECHNOLOGY BEHIND – PARTNERS I: Chlorophyll [%]
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44. Farmer DokuPlant Advisor Forester ForestOffice COM-SERVER Logistics & Precision FF 196.000 Farmers 260 Offices TC TRUSTCENTER § § Retailer Public mobGIS Certification GlobalGAP FSC, PEFC Wholesales Farm/Forest data Farmer/Forest data Expert DB – Agro/Forest Farmer/Forester Marketing Portal Documentation Nutrient balance CO 2 balance Profit margin Subsidies mapping Farmer DokuPlant Advisor Forester ForestOffice 196.000 Farmers Documentation Nutrient balancing CO 2 balance Profit margin Subsidies mapping COM-SERVER Logistics & Precision FF Environment- & Riskmanagement Agro/Forest Wiki 260 Offices mobGIS iso-BUS iso-BUS Standard Interface ICT INFORMATION CENTER - TRUST CENTER
45. 7 steps for a countrywide solution (4 ): Put pilot project/workplan into life: 24(12-36)) months and control (1 ): Define consortium: MoAF, NADS, Science/University, Bank/Insur.,Coops (1) setup base maps and field mapping (2) setup expert-information + localize all tools, (3) start farm-forest-advise and farm-forest-mgmt. with IT-tools (4) setup logistics incl. servers & communication (5) setup precision farming/forestry (meteorology-, soil-, pest- management , (6) setup risk- and environment management (7) verify and optimize (3): Define detailed workplan: + education + training + know-how transfer (2): Define pilot region: with farmers, foresters, coops, industry, advisors, based on following steps: (6 ): Rollout stepwise (1-3) the workplan : throughout regions or the whole country, setup a trustcentre including marketing tools for farmers, invite producers implementing precision farming, link insurance and financing, …… (5 ): Evaluate pilot projects results (farmer, advisor, …) (7 ): Implement further (or parallel ): forestry, environmental caretaking, risk-management, community and utility mgmt., index insurance, microcredits, ….
46. EU co-funded Projects 2009 and 2010: The Future Farm Project: FutureFarm is a 3 Mio € European project, funded by the EU as part of the Seventh Research Framework Programme . The official project start date was 1 st January 2008, and the project duration is 3 years. The full project title is "Meeting the challenges of the farm of tomorrow by integrating Farm Management Information Systems to support real-time management decisions and compliance to standards“. Project Partners 15 partners, mainly science and research and PROGIS as single IT company are working within the FutureFarm project, spread across 10 European countries, including universities, research institutes and private companies. Pilot Farms There are four "pilot farms" from four different countries, working within the FutureFarm project. Details you read on the homepage http://www.futurefarm.eu/ JRC/European Union contract: „Whole Farm management and information needs at sustainable biomass production “ 2009: PROGIS Conference together with EC INSPIRE and EC EUROGI 2009: DG Development Development Days in Stockholm 2010: Invitation to several EC FP7 projects as well as presentation of our technology at the EC parliament „Deforestation“ meeting
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48. VALUATION OF BENEFITS Value (€ + enviro + risk) increase
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51. ADVISE NEW AND ITS POLITICAL IMPACT ADVISE NEW AND ITS POLITICAL IMPACT