Internet of Food and Farm 2020

Livrables

Hosting environment and IoF2020 Lab

Development and provision of an experimental infrastructure serving experi¬mentation and validation in the pilots. Full commercial type usage goes beyond this deliverable itself, but it prepares the baseline to even extend the required SLA and commercial procurement by individual use case related users. (Leader: FF, M30; O, PU)

Enhancement and Configurations of Open Platforms and Reusable Components

Enhancement and Configurations of Open Platforms and Reusable Components: Additions to existing components required by the IoF2020 use cases, while aiming at the realisation of modules that are also applicable for future usage. Usage is generally public, while source code availability depends on the underlying model of the existing module, preferably open source (Leader: FF, M30; O, PU)

Literature review
Progress Report on Synergy Analysis, Decisions and Coordination of Work

All use cases are analysed for synergetic developments and decisions by the PIB will be facilitated. Related synergies and decisions will be documented and communicated in the scope of this deliverable. (Leader: WR, M18 & 30, R, PU)

Guideline for value-sensitive design for smart farming

Guideline for value-sensitive design, with an instruction video, which explains in a step-by-step way what value-sensitive design is and how to do it. The guideline is meant allow future innovators to engage in value-sensitive design by themselves and learn from the values and ethical questions that use cases in IOF encountered as well as how they answered them based on values

(Revised) guideline and/or code of conduct

Based on the interviews and interactive sessions we will look at whether and how already existing guidelines and codes of conduct offer sufficient assistance to deal with the ethical questions that come up.

Guidelines for the use of IoT related Standards in Smart Farming and Food Security

D3.2.3 Guidelines for the use of IoT related Standards in Smart Farming and Food Security: Compilation of different IoT related standards to facilitate IoT system realisation, grouped according to stakeholder groups (Leader: ATB, M48; R, PU)

Scale-Up Demonstration Report (M51)

Final Scale-Up Demonstration Report (updated from M33)

Report on Validation of business models in IoF2020 use cases

D4.7 Report on Validation of business models in IoF2020 use cases. (Leader: DLO, M46, R, PU)

Opportunities and Barriers in the present regulatory situation for system development

The deliverable will compile all the use case related opportunities and barriers to facilitate and trigger collaboration and synergies between use cases and as input for collaboration with external stakeholders (Leader: FF, M14, R, PU)

Policy Recommendations

Policy Recommendations: At mid-term in the project, compilation of key policy requirements that are aiming at a regulatory influence towards the post project exploitation phase, for enabling different stakeholder groups to take full advantage of the IoF2020 validation and demonstration results. (Leader: GS1, M24, R, PU)

Data Management Plan

D1.4.1: Data Management Plan: Document describing how data will be managed in the pilot, including guidelines for data management in IoT. (Leader: DLO, M6, R, PU)

Overview of preconditions for data sharing

This is based on a comparison of ethical problems/issues encountered in the large scale European IoT pilots. It will be shared by means of presentations at workshops and conferences (amongst which; the HubIT project and the winner of RUR-02).

Data Management Plan and Support pack

D1.4.2: Data Management Plan and Support pack: Document describing how data will be managed in the pilot, including guidelines for data management in IoT. Updated version, including Support Pack. (Leader: DLO, M36, R, PU)

Methodology to assess market outlook and social impact for each use case (M6):

D4.2 Methodology to assess market outlook and social impact for each use case (M6): This deliverable identifies and characterises key market trends and social-economic development and develops a methodology for business impact assessment and social impact assessment. (Leader: DLO, M6, R, PU)

Consolidated Report on Synergies with other IoT LSPs

D1.6: Consolidated Report on Synergies with other IoT LSPs: Compilation of the synergies realised in close collaboration of the pilot projects and in coordination of the horizontal activity (CSA). The work results will be carefully planned and refined in close cooperation of the LSPs and CSA at kick-off and updated accordingly. (Leader: DLO, M51, R, PU)

Scale-Up Demonstration Report

D2.5.1: Scale-Up Demonstration Report: The Report will describe all implemented demonstration activities envisaged in T2.5, informational/promotional material used, tools used to collect feedback, and present the collected feedback and analysis thereof. The report will be published two times during the course of the project, to capture the distinct phases of the demonstration activities. (Leader: BIOS, M33, M48, R, PU)

Taxonomy of business models relevant to IoT applications

This deliverable characterises the key components of business models relevant to IoT applications and sets out principles for developing business models for specific use cases. (Leader: WR, M12, R, PU)

Analysis report of the interactive sessions

This deliverable will give insight into the questions raised in the use cases, as well as the ways in which participants answer them and the values and norms that play a role in their reflections.

Overall lessons learned regarding business model

This additional deliverable assess what business models work well. The lessons learned contribute to the large scale take-up with lessons available for initiatives beyond IoF2020. (Leader: WR, M51, R, PU)

Cards for the interactive session

his deliverable is based on the interviews planned in task 3.

Report Validation of user acceptability in IoF2020 use cases

Assesses the user acceptability for IoF2020 use cases. (Leader: WR, M42, R, PU)

Open Call Realisation

D3.6.1 : The technology related realisation of the open call will be supported in T3.6 and related announcement prepared that are based on the technological requirements of the use cases. (Leader: ATB, M24, R, PU)

KPI Catalogue for each use case (M6):

This deliverable lists all KPIs and variables measured regarding its business impact and shows the value network characteristics of each use case. This might be a valuable source for other companies in this field to assess their performance and enhance the understanding of market potentials. (Leader: WR, M6, R, PU)

Progress Report on Development, Integration and Deployment of Reusable Components for WP2

D3.6.2 Progress Report on Development, Integration and Deployment of Reusable Components for WP2: The content, status and progress of the joint developments managed in T3.6 will be documented and communicated with this deliverable. (Leader: ATB, M51, R, PU)

Guidelines for Use Case Analysis & Design

D3.1.1 Guidelines for Use Case Analysis & Design: Approach and reference architecture to be applied for the analysis, design and conception of IoT based solutions in WP2. It is based on past partners’ activities in IoT initiatives and specifically w.r.t. FIWARE and Open IoT platforms. (Leader: ISMB, M9, R, PU)

IoF2020 Reference Catalogue for the reuse of Open Platforms

Type of catalogue or an extension to existing resources like the FIWARE catalogue or the IoT open platforms initiative. (Leader: UNPARRALLEL, M24, DEC, PU)

Catalogue of Use Cases, Project Management and Quality Assurance Guidelines

An attractive presentation of the use cases, clear presentation of the IoT technology applied and demonstrating the benefits for the user organizations involved. On top of that, providing guidelines required for a harmonised project management and QA on different project levels. (Leader : S&P, M51, DEC, PU)

Project website

D5.2 Project website (S&P, M6, DEC, PU)

Project Identity

D5.1 : logo, style book, communication formats (S&P, M4, DEC, PU)

Publications

Combining the Internet of Things with Simulation-Based Optimization to Enhance Logistics in an Agri-Food Supply Chain

Auteurs: David Raba, Angel A. Juan, Javier Panadero, Alejandro Estrada-Moreno, Christopher Bayliss
Publié dans: 2019 Winter Simulation Conference (WSC), 2019, Page(s) 1894-1905, ISBN 978-1-7281-3283-9
Éditeur: IEEE
DOI: 10.1109/wsc40007.2019.9004952

GreenBook: App híbrida para el seguimiento y control de explotaciones agrarias intensivas

Auteurs: Victor Maldonado, Joaquín Cañadas, Jorge A. Sánchez-Molina, Manuel Muñoz, Manuel Berenguel
Publié dans: Congreso Ibérico de Agroingeniería, 2019, Page(s) 998-1003
Éditeur: Servicio de Publicaciones Universidad
DOI: 10.26754/c_agroing.2019.com.3490

Edge Computing for Offload-Aware Energy Conservation Using M2M Recommendation Mechanisms

Auteurs: Constandinos X. Mavromoustakis, George Mastorakis, Jordi Mongay Batalla, Joel J. P. C. Rodrigues, John N. Sahalos
Publié dans: 2019 IEEE Global Communications Conference (GLOBECOM), 2019, Page(s) 1-6, ISBN 978-1-7281-0962-6
Éditeur: IEEE
DOI: 10.1109/globecom38437.2019.9013438

VANET Clustering Based on Weighted Trusted Cluster Head Selection

Auteurs: Grace Khayat, Constandinos X Mavromoustakis, George Mastorakis, Jordi Mongay Batalla, Hoda Maalouf, Evangelos Pallis
Publié dans: 2020 International Wireless Communications and Mobile Computing (IWCMC), 2020, Page(s) 623-628, ISBN 978-1-7281-3129-0
Éditeur: IEEE
DOI: 10.1109/iwcmc48107.2020.9148339

On the Social Network Centrality Principle for Human Centric Efficiency

Auteurs: Katerina Papanikolaou, Constandinos X Mavromoustakis, George Mastorakis, Jordi Mongay Batalla, Ciprian Dobre, Konstantinos Katzis
Publié dans: 2020 International Wireless Communications and Mobile Computing (IWCMC), 2020, Page(s) 1685-1688, ISBN 978-1-7281-3129-0
Éditeur: IEEE
DOI: 10.1109/iwcmc48107.2020.9148079

A Secure, Energy-Efficient and Distributed manageable model for a Smart Home

Auteurs: Ioannis Kounatidis, Constantinos X. Mavromoustakis, Periklis Chatzimisios, George Mastorakis, Jordi Mongay Batalla
Publié dans: 2020 International Wireless Communications and Mobile Computing (IWCMC), 2020, Page(s) 457-462, ISBN 978-1-7281-3129-0
Éditeur: IEEE
DOI: 10.1109/iwcmc48107.2020.9148504

An Internet of Things (IoT) Solution to Optimise the Livestock Feed Supply Chain

Auteurs: David Raba, Salvador Gurt, Oriol Vila, Esteve Farres
Publié dans: 6th International Conference on Natural Language Processing (NATP 2020), Numéro Copenhagen, 2020, Page(s) 103-118, ISBN 9781925953183
Éditeur: Aircc Publishing Corporation
DOI: 10.5121/csit.2020.100409

IOF2020: Fostering business and software ecosystems for large-scale uptake of IoT in food and farming, in: Nelson, W. (Ed.), The International Tri-Conference for Precision Agriculture in 2017

Auteurs: Verdouw, C.N., Wolfert, S., Beers, G., Sundmaeker, H., Chatzikostas, G.,
Publié dans: PA17 - The International Tri-Conference for Precision Agriculture in 2017 - Hamilton, New Zealand, 2017, Page(s) 7
Éditeur: International Tri-Conference for Precision Agriculture in 2017
DOI: 10.5281/zenodo.1002903

IoF2020 - the Internet Of Meat: towards applications of Internet of Things in the meat supply chain.

Auteurs: Maselyne, Jarissa; Mertens, Kristof; Van Nuffel, Annelies; Scholten, Huub; Athanasiadis, Ioannis; Larrañaga, Mikel; Fernández, Izaskun.
Publié dans: Papers presented at the 8th European Conference on Precision Livestock Farming, Numéro 8, 2017
Éditeur: 8th European Conference on Precision Livestock Farming

Guidelines for governance of data sharing in agri-food networks, in: Nelson, W. (Ed.), The International Tri-Conference for Precision Agriculture in 2017

Auteurs: Wolfert, S., Bogaardt, M.J., Ge, L., Soma, K., Verdouw, C.N.,
Publié dans: 2017, Page(s) 11
Éditeur: -
DOI: 10.5281/zenodo.893700

Field trial to demonstrate the intelligent dairy assistant (IDA) system on dairy farms

Auteurs: Rutten, C.J.; Molenaar, N.; Hogewerf, P.; Gosliga, Van, S.P.; Lokhorst, C.
Publié dans: 9th European Conference on Precision Livestock Farming, ECPLF 2019 - Cork, Ireland, Numéro 1, 2019, Page(s) 277-283, ISBN 9781-841706542
Éditeur: Teagasc

Collective Action in Farm Data Management

Auteurs: Krijn Poppe, Jos Verstegen and Sjaak Wolfert
Publié dans: 2018
Éditeur: ICA conference 2018

International Agriculture Congress And International For Food And Agriculture

Auteurs: Sjaak Wolfert
Publié dans: 2018
Éditeur: International Agriculture Congress And International For Food And Agriculture

Towards Animal Welfare in Poultry Farms through Semantic Technologies

Auteurs: Esnaola-Gonzalez I., Fernandez I., Ferreiro S., Garcia A., Gomez M., Lazaro I., Garcia E.
Publié dans: 2019
Éditeur: IoT Connected World & Semantic Interoperability Workshop (IoT-CWSI)

Smartomizer – Proactivity and Traceability in Orchard Spray

Auteurs: Lars T. Berger Pulverizadores Fede S.L ; Emilio Gil; Paula Ortega
Publié dans: 2019
Éditeur: Suprofruit2019

Book of Abstracts of the 71st Annual Meeting of the European Federation of Animal Science

Auteurs: Scientific Committee
Publié dans: 2020, Page(s) p. 524), ISBN 978-90-8686-349-5
Éditeur: Wageningen Academic Publishers
DOI: 10.3920/978-90-8686-900-8

Connected Cows: Utilizing Fog and Cloud Analytics toward Data-Driven Decisions for Smart Dairy Farming

Auteurs: Mohit Taneja, Nikita Jalodia, Paul Malone, John Byabazaire, Alan Davy, Cristian Olariu
Publié dans: IEEE Internet of Things Magazine, Numéro 2/4, 2019, Page(s) 32-37, ISSN 2576-3180
Éditeur: IEEE
DOI: 10.1109/iotm.0001.1900045

Smart Farming Techniques for Climate Change Adaptation in Cyprus

Auteurs: George Adamides, Nikos Kalatzis, Andreas Stylianou, Nikolaos Marianos, Fotis Chatzipapadopoulos, Marianthi Giannakopoulou, George Papadavid, Vassilis Vassiliou, Damianos Neocleous
Publié dans: Atmosphere, Numéro 11/6, 2020, Page(s) 557, ISSN 2073-4433
Éditeur: Rotoweb Cantelli
DOI: 10.3390/atmos11060557

Development of an empirical tomato crop disease model: a case study on gray leaf spot

Auteurs: Hui Wang, Jorge Antonio Sanchez-Molina, Ming Li, Manuel Berenguel
Publié dans: European Journal of Plant Pathology, Numéro 156/2, 2020, Page(s) 477-490, ISSN 0929-1873
Éditeur: Kluwer Academic Publishers
DOI: 10.1007/s10658-019-01897-7

An IoT Architecture for Water Resource Management in Agroindustrial Environments: A Case Study in Almería (Spain)

Auteurs: Manuel Muñoz, Juan Gil, Lidia Roca, Francisco Rodríguez, Manuel Berenguel
Publié dans: Sensors, Numéro 20/3, 2020, Page(s) 596, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s20030596

Machine learning based fog computing assisted data-driven approach for early lameness detection in dairy cattle

Auteurs: Mohit Taneja, John Byabazaire, Nikita Jalodia, Alan Davy, Cristian Olariu, Paul Malone
Publié dans: Computers and Electronics in Agriculture, Numéro 171, 2020, Page(s) 105286, ISSN 0168-1699
Éditeur: Elsevier BV
DOI: 10.1016/j.compag.2020.105286

Greenhouse Models as a Service (GMaaS) for Simulation and Control

Auteurs: M. Muñoz, J.L. Guzmán, J.A. Sánchez, F. Rodríguez, M. Torres
Publié dans: IFAC-PapersOnLine, Numéro 52/30, 2019, Page(s) 190-195, ISSN 2405-8963
Éditeur: IFAC
DOI: 10.1016/j.ifacol.2019.12.520

The Internet of Things enhancing animal welfare and farm operational efficiency

Auteurs: Craig Michie, Ivan Andonovic, Christopher Davison, Andrew Hamilton, Christos Tachtatzis, Nicholas Jonsson, Carol-Anne Duthie, Jenna Bowen, Michael Gilroy
Publié dans: Journal of Dairy Research, Numéro 87/S1, 2020, Page(s) 20-27, ISSN 0022-0299
Éditeur: Cambridge University Press
DOI: 10.1017/s0022029920000680

Detecting Heat Stress in Dairy Cattle Using Neck-Mounted Activity Collars

Auteurs: Christopher Davison, Craig Michie, Andrew Hamilton, Christos Tachtatzis, Ivan Andonovic, Michael Gilroy
Publié dans: Agriculture, Numéro 10/6, 2020, Page(s) 210, ISSN 2077-0472
Éditeur: MDPI
DOI: 10.3390/agriculture10060210

An automatic method based on daily in situ images and deep learning to date wheat heading stage

Auteurs: Kaaviya Velumani, Simon Madec, Benoit de Solan, Raul Lopez-Lozano, Jocelyn Gillet, Jeremy Labrosse, Stephane Jezequel, Alexis Comar, Frédéric Baret
Publié dans: Field Crops Research, Numéro 252, 2020, Page(s) 107793, ISSN 0378-4290
Éditeur: Elsevier BV
DOI: 10.1016/j.fcr.2020.107793

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

Auteurs: David Raba, Alejandro Estrada‐Moreno, Javier Panadero, Angel A. Juan
Publié dans: International Transactions in Operational Research, Numéro 27/6, 2020, Page(s) 2785-2816, ISSN 0969-6016
Éditeur: Blackwell Publishing
DOI: 10.1111/itor.12776

A Review of Climate-Smart Agriculture Applications in Cyprus

Auteurs: George Adamides
Publié dans: Atmosphere, Numéro 11/9, 2020, Page(s) 898, ISSN 2073-4433
Éditeur: Rotoweb Cantelli
DOI: 10.3390/atmos11090898

A New IoT-based Platform for Greenhouse Crop Production

Auteurs: M. Munoz, J.L. Guzman, J.A. Sanchez, F. Rodriguez, M. Torres, M. Berenguel
Publié dans: IEEE Internet of Things Journal, 2020, Page(s) 1-1, ISSN 2327-4662
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/jiot.2020.2996081

Improving automatic climate control with decision support techniques to minimize disease effects in greenhouse tomatoes

Auteurs: Joaquín Cañadas, Jorge Antonio Sánchez-Molina, Francisco Rodríguez, Isabel María del Águila
Publié dans: Information Processing in Agriculture, Numéro 4/1, 2017, Page(s) 50-63, ISSN 2214-3173
Éditeur: --
DOI: 10.1016/j.inpa.2016.12.002

Big Data in Smart Farming – A review

Auteurs: Sjaak Wolfert, Lan Ge, Cor Verdouw, Marc-Jeroen Bogaardt
Publié dans: Agricultural Systems, Numéro 153, 2017, Page(s) 69-80, ISSN 0308-521X
Éditeur: Applied Science Publishers
DOI: 10.1016/j.agsy.2017.01.023

Internet of Things in agriculture.

Auteurs: C Verdouw
Publié dans: CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, Numéro 11/035, 2016, ISSN 1749-8848
Éditeur: CAB International
DOI: 10.1079/PAVSNNR201611035

Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouse

Auteurs: Jorge Antonio Sanchez-Molina, Li Ming, Francisco Rodriguez, Jose Luis Guzman, Wang Hui, Yang Xinting
Publié dans: International Journal of Agricultural and Biological Engineering, Numéro 10/4, 2017, Page(s) 66-76, ISSN 1934-6344
Éditeur: International Journal of Agricultural and Biological Engineering (IJABE)
DOI: 10.25165/j.ijabe.20171004.2398

Agricultural cooperatives and the role of organisational models in new intelligent traceability systems and big data analysis

Auteurs: Cynthia Giagnocavo, Fernando Bienvenido, Li Ming, Zhao Yurong, Jorge Antonio Sanchez-Molina, Yang Xinting
Publié dans: International Journal of Agricultural and Biological Engineering, Numéro 10/5, 2017, Page(s) 115-125, ISSN 1934-6344
Éditeur: International Journal of Agricultural and Biological Engineering (IJABE)
DOI: 10.25165/j.ijabe.20171005.3089

Architecture framework of IoT-based food and farm systems: A multiple case study

Auteurs: Cor Verdouw, Harald Sundmaeker, Bedir Tekinerdogan, Davide Conzon, Teodoro Montanaro
Publié dans: Computers and Electronics in Agriculture, Numéro 165, 2019, Page(s) 104939, ISSN 0168-1699
Éditeur: Elsevier BV
DOI: 10.1016/j.compag.2019.104939

Ethics of smart farming: Current questions and directions for responsible innovation towards the future

Auteurs: Simone van der Burg, Marc-Jeroen Bogaardt, Sjaak Wolfert
Publié dans: NJAS - Wageningen Journal of Life Sciences, 2019, Page(s) 100289, ISSN 1573-5214
Éditeur: Koninklijk Landbouwkundige Vereniging/Royal Netherlands Society of Agricultural Sciences
DOI: 10.1016/j.njas.2019.01.001

Enabling Large-Scale IoT-Based Services through Elastic Publish/Subscribe

Auteurs: Sergio Vavassori, Javier Soriano, Rafael Fernández
Publié dans: Sensors, Numéro 17/9, 2017, Page(s) 2148, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s17092148

A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd

Auteurs: Francisco Maroto-Molina, Jorge Navarro-García, Karen Príncipe-Aguirre, Ignacio Gómez-Maqueda, José E. Guerrero-Ginel, Ana Garrido-Varo, Dolores C. Pérez-Marín
Publié dans: Sensors, Numéro 19/10, 2019, Page(s) 2298, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s19102298

Characterization of LoRa Point-to-Point Path-Loss: Measurement Campaigns and Modeling Considering Censored Data

Auteurs: Gilles Callebaut, Liesbet Van der Perre
Publié dans: IEEE Internet of Things Journal, 2019, Page(s) 1-1, ISSN 2327-4662
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/jiot.2019.2953804

A Bayesian framework for joint structure and colour based pixel-wise classification of grapevine proximal images

Auteurs: F. Abdelghafour, R. Rosu, B. Keresztes, C. Germain, J.P. Da Costa
Publié dans: Computers and Electronics in Agriculture, Numéro 158, 2019, Page(s) 345-357, ISSN 0168-1699
Éditeur: Elsevier BV
DOI: 10.1016/j.compag.2019.02.017

Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing

Auteurs: Simone van der Burg, Leanne Wiseman, Jovana Krkeljas
Publié dans: Ethics and Information Technology, 2020, ISSN 1388-1957
Éditeur: Kluwer Academic Publishers
DOI: 10.1007/s10676-020-09543-1

Internet of Things in arable farming: Implementation, applications, challenges and potential

Auteurs: Andrés Villa-Henriksen, Gareth T.C. Edwards, Liisa A. Pesonen, Ole Green, Claus Aage Grøn Sørensen
Publié dans: Biosystems Engineering, Numéro 191, 2020, Page(s) 60-84, ISSN 1537-5110
Éditeur: Academic Press
DOI: 10.1016/j.biosystemseng.2019.12.013

Digital twins in smart farming

Auteurs: Cor Verdouw, Bedir Tekinerdogan, Adrie Beulens, Sjaak Wolfert
Publié dans: Agricultural Systems, Numéro 189, 2021, Page(s) 103046, ISSN 0308-521X
Éditeur: Applied Science Publishers
DOI: 10.1016/j.agsy.2020.103046

Improving the Performance of Vegetable Leaf Wetness Duration Models in Greenhouses Using Decision Tree Learning

Auteurs: Hui Wang, Jorge Sanchez-Molina, Ming Li, Francisco Rodríguez Díaz
Publié dans: Water, Numéro 11/1, 2019, Page(s) 158, ISSN 2073-4441
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/w11010158

Infield optimized route planning in harvesting operations for risk of soil compaction reduction

Auteurs: Andrés Villa‐Henriksen, Nick Skou‐Nielsen, Lars Juhl Munkholm, Claus A. G. Sørensen, Ole Green, Gareth T. C. Edwards
Publié dans: Soil Use and Management, 2020, ISSN 0266-0032
Éditeur: CABI Publishing
DOI: 10.1111/sum.12654

Automatic Tomato and Peduncle Location System Based on Computer Vision for Use in Robotized Harvesting

Auteurs: M. Benavides, M. Cantón-Garbín, J. A. Sánchez-Molina, F. Rodríguez
Publié dans: Applied Sciences, Numéro 10/17, 2020, Page(s) 5887, ISSN 2076-3417
Éditeur: MDPI
DOI: 10.3390/app10175887

Nitrate Content Control in Green Vegetables Grown Under LED Lighting

Auteurs: Celine C.S. Nicole, M.P.C.M. Krijn, Udo van Slooten
Publié dans: Plant Factory Using Artificial Light, 2019, Page(s) 99-110, ISBN 9780128139738
Éditeur: Elsevier
DOI: 10.1016/b978-0-12-813973-8.00010-5

Use of IoT technologies for irrigation and plant protection

Auteurs: Theocharis Moysiadis, George Adamides, Andreas Stylianou, Nikolaos Zotos, Marianthi Giannakopoulou, George Alexiou
Publié dans: Bio-Economy and Agri-production, 2021, Page(s) 175-194, ISBN 9780128197745
Éditeur: Elsevier
DOI: 10.1016/b978-0-12-819774-5.00010-2

IoT European Large-Scale Pilots – Integration, Experimentation and Testing

Auteurs: Guillén, Sergio; Sala, Pilar; Fico, Giuseppe; Arredondo, María Teresa; Cano, Alicia; Posada, Jorge; Gutiérrez, German; Palau, Carlos; Votis, Konstantinos; Verdouw, C.N.; Wolfert, J.; Beers, G.; Sundmaeker, H.; Chatzikostas, Grigoris; Ziegler, Sébastian; Hemmens, Christopher; Holst, Marita; Stahlbröst, Anna; Scudiero, Lucio; Reale, C.; Krco, S.; Drajic, D.; Eisenhauer, M.; Jahn, M.; Valino, J.
Publié dans: Cognitive Hyperconnected Digital Transformation, Numéro 3, 2017, Page(s) 221-282
Éditeur: SINTEF

Optimizing Plant Factory Performance for Local Requirements

Auteurs: R.J.P. Janssen, M.P.C.M. Krijn, T. van den Bergh, R.F.M. van Elmpt, Celine C.S. Nicole, Udo van Slooten
Publié dans: Plant Factory Using Artificial Light, 2019, Page(s) 281-293, ISBN 9780128139738
Éditeur: Elsevier
DOI: 10.1016/b978-0-12-813973-8.00025-7

Semantic Technologies Towards Accountable Artificial Intelligence: A Poultry Chain Management Use Case

Auteurs: Iker Esnaola-Gonzalez
Publié dans: Artificial Intelligence XXXVII - 40th SGAI International Conference on Artificial Intelligence, AI 2020, Cambridge, UK, December 15–17, 2020, Proceedings, Numéro 12498, 2020, Page(s) 215-226, ISBN 978-3-030-63798-9
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-030-63799-6_17

Factors critical to plant factory performance

Auteurs: M.P.C.M. Krijn, R.F.M. van Elmpt, S.L. van de Voort, C.C.S. Nicole, G. van der Feltz, T. van den Bergh
Publié dans: Acta Horticulturae, Numéro 1227, 2018, Page(s) 615-622, ISSN 0567-7572
Éditeur: International Society for Horticultural Science
DOI: 10.17660/actahortic.2018.1227.78

Women in Precision Agriculture - Technological breakthroughs, Challenges and Aspirations for a Prosperous and Sustainable Future

Auteurs: J. Maselyne
Publié dans: 2021, ISBN 978-3-030-49244-1
Éditeur: Springer
DOI: 10.1007/978-3-030-49244-1

Aligning business processes and IT of multiple collaborating organisations

Auteurs: Ayalew Kassahun
Publié dans: 2017
Éditeur: University
DOI: 10.18174/414988

Dairy cow behaviour in relation to precision mineral supplementation

Auteurs: Foged H
Publié dans: 2019
Éditeur: ResearchGate

Flowability of mineral feed supplements for precision mineral supplementation

Auteurs: Foged H. Madsen J.
Publié dans: 2019
Éditeur: ResearchGate

LoRa Physical Layer Evaluation for Point-to-Point Links and Coverage Measurements in Diverse Environments

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