Gajinov, S., Popovic, T., Drajic, D., Gligoric, N. and Krco, S. (2022) ” Qualitative parameter analysis for Botrytis cinerea forecast modelling using IoT sensor networks’, Journal of Networking and Network Applications, Vol.2, Issue 3, pp,120-135 DOI:10.33969/J-NaNA.2022.020305
Reis-Pereira, M.,Tosin, R., Martins, R., Neves dos Santos, F., Tavares, F and Cunha, M. (2022) “Kiwi Plant Canker Diagnosis Using Hyperspectral Signal Processing and Machine Learning: Detecting Symptoms Caused by Pseudomonas syringae pv. actinidiae”, Plants2022, 11, 2154. https://doi.org/10.3390/plants11162154
Gonzalez-Vidal, A., Ramallo-Gonzalez, A.P and Skarmeta, A.F. (2022) ‘Intrinsic and extrinsic quality of data for open data repositories’, ICT Express, https://doi.org/10.1016/j.icte.2022.06.001
Roussaki, I., Doolin, K., Skarmeta, A., Routis, G., Lopez-Morales, J., Claffey, E., Mora, M., Martinez, J.A (2022) “Building an interoperable space for smart agriculture”, Digital Communication and Networks, https://doi.org/10.1016/j.dcan.2022.02.004
Campos, E.M., Saura, P.F., Gonzales-Vidal, A., Herandez-Ramos, J., Bernabe, J.B., Baldini, G., Skarmeta, A. (2021), “Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges”, https://arxiv.org/abs/2108.00974
Charvat K., Bergheim R., Bērziņš R., Zadražil F., Langovskis D., Vrobel J., Horakova S. (2021), “Map Whiteboard Cloud Solution for Collaborative Editing of Geographic Information”. Cloud Computing and Data Science 2(2):36-5. Available from: https://ojs.wiserpub.com/index.php/CCDS/article/view/897
da Silva, D.Q., Aguiar, A.S., dos Santos, F.N., Sousa, A.J., Rabino, D., Biddoccu, M., Bagagiolo, G., and Delmastro, M. (2021), ” Measuring Canopy Geometric Structure Using Optical Sensors Mounted on Terrestrial Vehicles: A Case Study in Vineyards”. Agriculture2021, 11, 208. https://doi.org/10.3390/agriculture11030208
Azpiroz, I., Oses, N, Quartulli, M., Olaizola, I.G., Guidotti, D., and Marchi, S (2021) “Comparison of Climate Reanalysis and Remote-Sensing Data for Predicting Olive Phenology through Machine-Learning Methods”. Remote Sensors, 13, 1224. https://doi.org/10.3390/rs1306122
López-Morales, J.A., Martínez J.A. and Skarmeta A.F. (2021), “ Improving Energy Efficiency of Irrigation Wells by Using an IoT-Based Platform”. Electronics, 10(3), 250. https://doi.org/10.3390/electronics10030250
Alcaniz, T., Gonzalez-Vidal, A., Ramallo, A. and Skarmeta, A. (2021), “Quality of Information within Internet of Things Data” Available from DOI: 10.5772/intechopen.95844
Bordel, B. Alcarria R. and Robles T. “Controlling Supervised Industry 4.0 Processes through Logic Rules and Tensor Deformation Functions,” (2021) Informatica, 1-29. doi:10.15388/20-INFOR441
González-Vidal, A., Rathore, P., Rao, A.S., Mendoza-Bernal, J., Palaniswami, M. and Skarmeta-Gómez., A.F. (2021), “Missing Data Imputation with Bayesian Maximum Entropy for Internet of Things Applications,” in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2020.2987979
Oses,N., Azpiroz, I., Marchi, S., Guidotti, D., Quartulli, M. and Olaizol, I.G. (2020), “Analysis of Copernicus’ ERA5 Climate Reanalysis Data as a Replacement for Weather Station Temperature Measurements in Machine Learning Models for Olive Phenology Phase Prediction, “ Sensors 2020, 20, 6381. https://doi.org/10.3390/s20216381
López-Morales, J.A., Martínez, J.A., and Skarmeta, A.F. (2020), “Digital Transformation of Agriculture through the Use of an Interoperable Platform” Sensors2020, 20, 1153. https://doi.org/10.3390/s20041153
Jallal, M., Gonzalez-Vidal, A., Skarmeta, A.F, Chabaa, S. and Zeroual, A. (2020) , “A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction” Applied Energy, 268, 10.1016/j.apenergy.2020.114977
González-Vidal, A., Alcaniz, T., Iggena, T., Bin Ilyas, E. and Skarmeta, A.F. “Domain Agnostic Quality of Information Metrics in IoT-Based Smart Environments”, Intelligent Environments 2020, doi:10.3233/AISE200059 pdf
Bordel, B., Alcarria, R and Robles T. “Supervising Industrial Distributed Processes Through Soft Models, Deformation Metrics and Temporal Logic Rules”. In: Rocha Á., Adeli H., Reis L., Costanzo S., Orovic I., Moreira F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_12
Magalhães, S.A.; Castro, L.; Moreira, G.; dos Santos, F.N.; Cunha, M.; Dias, J.; Moreira, A.P. (2021), “Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse”, Sensors, https://doi.org/10.3390/s21103569
Grainne Dilleen, Ethel Claffey, Anthony Foley, Kevin Doolin (2023), “Investigating knowledge dissemination and social media use in the farming network to build trust in smart farming technology adoption”, Journal of Business & Industrial Marketing, Volume 38 Issue 8, https://doi.org/10.1108/JBIM-01-2022-0060
Juan Antonio Martinez, Juan A Lopez-Morales, Antonio Skarmeta, UMU (2021), “Improving Energy Efficiency of Irrigation Wells by Using an IoT-Based Platform”, Electronics, https://doi.org/10.3390/electronics10030250
Juan Antonio López-Morales; Juan Antonio Martínez; Antonio F. Skarmeta (2021), “Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety”, Sensors, https://doi.org/10.3390/s21113867
Pinheiro I, Aguiar A, Figueiredo A, Pinho T, Valente A, Santos F. (2023), “Nano Aerial Vehicles for Tree Pollination”, Applied Science, https://doi.org/10.3390/app13074265
Mario San Emeterio de la Parte, José Fernán Martínez Ortega, Vicente Hernández Díaz, Néstor Lucas Martínez, (2023), “Big Data and precision agriculture: a novel spatio-temporal semantic IoT data management framework for improved interoperability”, Journal of Big Data, 10.1186/s40537-023-00729-0
Gligoric, N.; Popovic, T.; Drajic, D.; Gajinov, S.; Krco, S. (2021), “Qualitative Parameter Analysis for Botrytis cinerea Forecast Modelling Using IoT Sensor Networks”, Preprints, https://doi.org/10.20944/preprints202108.0072.v1
Sandro Augusto Magalhães, António Paulo Moreira, Filipe Neves dos Santos & Jorge Dias (2022), “Active Perception Fruit Harvesting Robots — A Systematic Review”, Journal of Intelligent Robotic Systems, https://link.springer.com/article/10.1007/s10846-022-01595-3
Aurora González-Vidal; José Mendoza-Bernal; Alfonso P. Ramallo; Miguel Ángel Zamora; Vicente Martínez; Antonio F. Skarmeta, (2022), “Smart operation of climatic systems in a greenhouse”, Agriculture, 10.3390/agriculture12101729
Sandro Augusto Magalhães ,Luís Castro , Germano Moreira ,Filipe Neves dos Santos , Mário Cunha, Jorge Dias and António Paulo Moreira (2023), “Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse”, Sensors, https://doi.org/10.3390/s21103569
Wolferts, Daniel; Stein, Elisabeth; Bernards, Ann-Kathrin; Reiners, René, (2022), “Differences between remote and analog design thinking through the lens of distributed cognition”, Frontiers in AI, https://doi.org/10.3389/frai.2022.915922
Arne J. Berre, Harald Sundmaeker, Daoud Urdu, Stefan Rilling, Ioanna Roussaki, Angelo Margugli, Kevin Doolin, Piotr Zaborowski, Rob Atkinson, Raul Palma, Marianna Faraldi (Submitted July 2023), “Interoperability Architectures for Digital Agri-food Platforms, COMPAG – Computers and Electronics in Agriculture”
Conferences
Azpiroz, I., Quartulli, M. and Olaizola, I.G (2022) ‘Methodology for Online Phenology Prediction Service Creation’ IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022, Kuala Lumpur, Malaysia 10.1109/IGARSS46834.2022.9883164
Juska,V.B and O’Riordan, A (2022) ‘Micro-Surface Engineering of Integrated Silicon Microtechnologies for the Development of Sensing and Biosensing Platforms;, ECS Meeting Abstracts, Volume MA2022-02, 2260 DOI 10.1149/MA2022-02612260mtgabs
Mueller, S., Plociennik, M. Zacharczuk, M., Fojud, A., Blaszczak, M., Laskowska, A., Palma, R and Wojtowicz, A. (2022) “Leveraging IoT solutions as a base for development of the agriculture advisory services”, 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 1-3 August, Barcelona, Spain 10.1109/COINS54846.2022.9854950
Bilbao-Arechabala, S. and Martinez-Rodriguez, B. (2022) “A practical approach to cross-agri-domain interoperability and integration” 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 1-3 August, Barcelona, Spain 10.1109/COINS54846.2022.9854999
Routis, G., Paraskevopoulos, M., Vetsikas, I.A, Roussaki, I., Stavrakoudis, D. and Katsantonis, D. (2022) “Data-Driven and Interoperable Smart Agriculture: An IoT-based Use-Case for Arable Crops”, 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 1-3 August, Barcelona, Spain.10.1109/COINS54846.2022.9855001
Gallo, P., Daidone, F., Sgroi, F. and Avantaggiato, M. (2022) “AgriChain: Blockchain Syntactic and Semantic Validation for Reducing Information Asymmetry In Agri-Food’, CEUR Workshop Proceedings June 20-23, Rome, Italy http://ceur-ws.org/Vol-3166/paper08.pdf
Bordel, B., Alcarria, R., de la Torre, G., Carretero, I. and Robles, T. (2022) “Increasing the efficiency and workers wellbeing in the European Bakery Industry: An Industry 4.0 Case Study”, ICITS 2022, pp646-658 DOI: 10.1007/978-3-030-96293-7_54
Abdipourchenarestansofla, M., Schroth, C. (2022) “The importance of data quality assessment for machinery data in the field of agriculture”, 79th International Conference on Agricultural Engineering, Online, DOI:10.51202/9783181023952-495
Bordel, B., Alcarria, R., Robles, T., de la Torre, G. and Carretero, I. (2021) ‘Digital user-industry interactions and Industry 4.0 services to improve customers’ experience and satisfaction in the European bakery sector’, 2021 16th Iberian Conference on Information Systems and Technologies (CISTI), 23 – 26 June 2021, Chaves, Portugal, doi: 10.23919/CISTI52073.2021.9476568
Fernandez Pesado, P.J., Rubio Melon, A., Escudero Barbero, R., Sanchez Hernandez B., Caceres Losada, J.L, Calero Gil, R. (2021) ‘The Digitalization of The Field. Use Of Remote Sensing and New Technologies as Sustainable Tools In The Management Of Modern Irrigation. R&D&I Projects: Optireg and DEMETER’, XXXVIII Congreso Nacional de Riegos, Cartagena, 3-5 November 2021, https://repositorio.upct.es/bitstream/handle/10317/10111/B-03-2021.pdf?sequence=4&isAllowed=y
M. Płóciennik et al., “Leveraging Agri-food IoT Solutions to Connect Apiary Owners and Farmers,” 2021 16th International Conference on Telecommunications (ConTEL), 2021, pp. 152-157, doi: 10.23919/ConTEL52528.2021.9495980.
Bader, S., Pullmann, J., Mader, C., Tramp, S., Quix, C., Muller, A., Akyurek, H., Bockmann, M., Imbusch, B., Lipp, J.,Geilser, S. and Lange, C. (2020), “The International Data Spaces Information Model – An Ontology for Sovereign Exchange of Digital Content”, International Semantic Web Conference 2020, pp 176-192. DOI:10.1007/978-3-030-62466-8_12
Bordel, B., Alcarria, R. and Robles, T. (2020) “Supervising Industrial Distributed Processes Through Soft Models, Deformation Metrics and Temporal Logic Rules”, WorldCIST 2020: Trends and Innovations in Information Systems and Technologies, June 2020, https://doi.org/10.1007/978-3-030-45691-7_12
R. Arias Calderon, S. Arias Calderon, P. Martins, A. Cordeiro, J.M Silvestre (2020), “Validation of a fluorometer sensor for characterization of olive varieties and evaluation of fruit ripeness index with non-destructive measurement: preliminary results. A: II Simposio Ibérico de Ingeniería Hortícola: Agricultura 4.0: Ponte de Lima, Portugal: 4- 6 de marzo, 2020, p. 489-493.
JA. Lopez-Morales, A. F. Skarmeta and J. A. Martinez, “Agri-food Research Centres as Drivers of Digital Transformation for Smart Agriculture,” 2020 Global Internet of Things Summit (GIoTS), Dublin, Ireland, 2020, pp. 1-5, doi: 10.1109/GIOTS49054.2020.9119646.
N. Oses, I. Azpiroz, M. Quartulli, I. Olaizola, S. Marchi and D. Guidotti, “Machine Learning for olive phenology prediction and base temperature optimisation,” 2020 Global Internet of Things Summit (GIoTS), Dublin, Ireland, 2020, pp. 1-6, doi: 10.1109/GIOTS49054.2020.9119611.
I. Roussaki, P. Kosmides, G. Routis, K. Doolin, V. Pevtschin and A. Marguglio, “A Multi-Actor Approach to promote the employment of IoT in Agriculture,” 2019 Global IoT Summit (GIoTS), Aarhus, Denmark, 2019, pp. 1-6, doi: 10.1109/GIOTS.2019.8766416.