The connected world : examining the Internet of Things : hearing before the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Fourteenth Congress, first session, February 11, 2015.

Συγγραφείς: United States. Congress. Senate. Committee on Commerce, Science, and Transportation

Θεματικοί όροι: Legislative hearings., Legislative hearings., Internet of things., Embedded Internet devices., Machine-to-machine communications., Agriculture -- Data processing., Artificial intelligence -- Agricultural applications., Computer networks -- Security measures., Privacy, Right of -- United States., Data protection -- United States., Agriculture -- Data processing., Artificial intelligence -- Agricultural applications., Computer networks -- Security measures., Data protection., Embedded Internet devices., Internet of things., Machine-to-machine communications., Privacy, Right of.

Other Titles: Examining the Internet of Things

Διαθέσιμο Online: https://purl.fdlp.gov/GPO/gpo67476
https://www.gpo.gov/fdsys/pkg/CHRG-114shrg99818/pdf/CHRG-114shrg99818.pdf
https://catalog.gpo.gov/fdlpdir/locate.jsp?ItemNumber=1041-C&SYS=000979488

Weakly and semi-supervised detection, segmentation and tracking of table grapes with limited and noisy data

Συγγραφείς: Ciarfuglia, Thomas A., Motoi, Ionut M., Saraceni, Leonardo, Fawakherji, Mulham, Sanfeliu Cortés, Alberto, Nardi, Daniele

Συνεισφορές: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents

Θεματικοί όροι: Àrees temàtiques de la UPC::Informàtica, Agriculture -- Data processing, Computer vision, Detection grapes, Segmentation grapes, Tracking grapes, Neural nets, Agricultura -- Informàtica, Visió per ordinador

Περιγραφή αρχείου: application/pdf

Relation: https://www.sciencedirect.com/science/article/pii/S0168169923000121; info:eu-repo/grantAgreement/EC/H2020/101016906/EU/A Collaborative Paradigm for Human Workers and Multi-Robot Teams in Precision Agriculture Systems/CANOPIES; http://hdl.handle.net/2117/408683

Διαθεσιμότητα: http://hdl.handle.net/2117/408683
https://doi.org/10.1016/j.compag.2023.107624

Parallel Programming to Analyze Crop-Health in Real-Time

Συγγραφείς: Molina Muñoz, Angie Natalia, Brunn, Ansgar, Chaparro, Javier, Pérez, Alexander

Συνεισφορές: Ecitrónica

Πηγή: https://geodaesie.info/zfv/heftbeitrag/8375.

Θεματικοί όροι: Agricultura - Procesamiento de datos, Agricultura - Aspectos ambientales, Agriculture - Data processing, Agriculture - Environmental aspects, Parallel programming, Plants health, NDVI, OpenCV, CUDA, NVIDIA Jetson

Περιγραφή αρχείου: 6 páginas; application/pdf

Relation: zfv 2/2019. 144. Jg.; 77; 72; N/A; ZFV; Aasen, H., Honkavaara, E., Lucieer, A., Zarco-Tejada, P. J. (2018): Quantitative remote sensing at ultra-high resolution with uav spectroscopy: A review of sensor technology, measurement procedures, and data correction workflows. Remote Sensing, 10 (7), 2018. ISSN 2072-4292. DOI:10.3390/rs10071091. www.mdpi.com/2072- 4292/10/7/1091.; Albertz, J. (2001): Einführung in die Fernerkundung: Grundlagen der Interpretation von Luft- und Satellitenbildern. Wiss. Buchges. ISBN 9783534146246. https://books.google.de/books?id=KdFAAAACAAJ.; European Commission (2018): La investigación y la innovación agraria. http://ec.europa.eu/agriculture/research-innovation/index_es.htm.; Halfacree, G. (2017): Nvidia Jetson TK1 – Full Board. https://www.flickr. com/photos/120586634@N05/14672953894.; Harris, M. (2017): An even easier introduction to CUDA. https:// devblogs.nvidia.com/even-easier-introduction-cuda.; NVDIA Corporation (2018): CUDA zone, 2018. https://developer.nvidia. com/cuda-zone; NVIDIA Corporation (2018): Embedded system – build something amazing. https://www.nvidia.com/en-us/autonomous-machines/ embedded-systems.; OpenCV (2018): OpenCV – About. https://opencv.org/about.html. Parrot Sequoia Team (2018): Parrot Sequoia+. www.parrot.com/ business-solutions-us/parrot-professional/parrot-sequoia#parrotsequoia-.; Pix4D Team (2018): Pix4d. https://pix4d.com/sequoia-faq.; Sanders, J., Kandrot, E. (2015): CUDA by Example: An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional, 6th edition, 2015. ISBN 0131387685, 9780131387683.; Storti, D., Yurtoglu, M. (2015): CUDA for Engineers: An Introduction to High-Performance Parallel Computing. Addison-Wesley Professional, 6th edition, 2015. ISBN 013417741X, 9780134177410.; Taipale, E. (2017): NDVI and your farm: understanding NDVI for plant health insights. https://sentera.com/understanding-ndvi-planthealth.; Weier, J., Herring, D. (2018): Measuring Vegetation (NDVI & EVI). https://earthobservatory.nasa.gov/Features/MeasuringVegetation.; https://repositorio.escuelaing.edu.co/handle/001/1429

Διαθεσιμότητα: https://repositorio.escuelaing.edu.co/handle/001/1429
https://doi.org/10.12902/zfv-0249-2019

When the world makes sense

Συγγραφείς: Lee, Anne

Πηγή: New Zealand dairy exporter (1988), Aug 2022; v.97 n.12:p.28-29
Dairy exporter

Σύνδεσμος πρόσβασης: https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE83154624

Ensembles of wrappers for automated feature selection in fish age classification

Συγγραφείς: Bermejo Sánchez, Sergi

Συνεισφορές: Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica

Πηγή: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname

Θεματικοί όροι: 0106 biological sciences, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica, Support vector machines, Nearest neighbor classifiers, 02 engineering and technology, Automated fish age classification, 01 natural sciences, Agriculture -- Data processing, Informàtica::Aplicacions de la informàtica [Àrees temàtiques de la UPC], Feature selection, 0202 electrical engineering, electronic engineering, information engineering, Agricultura -- Informàtica, Àrees temàtiques de la UPC::Enginyeria agroalimentària::Agricultura, Statistical pattern recognition, 14. Life underwater, Atlantic cod otoliths, Enginyeria agroalimentària::Agricultura [Àrees temàtiques de la UPC]

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://upcommons.upc.edu/bitstream/2117/100219/7/COMPAG%2b13%2bJan%2b07%2b%28d%29-accepted%2bversion%281%29.pdf
http://hdl.handle.net/2117/100219
https://upcommons.upc.edu/bitstream/2117/100219/7/COMPAG%2b13%2bJan%2b07%2b%28d%29-accepted%2bversion%281%29.pdf
https://www.sciencedirect.com/science/article/pii/S0168169916301430
https://europepmc.org/abstract/AGR/IND605611093
https://core.ac.uk/display/81579948
https://upcommons.upc.edu/handle/2117/100219
https://dblp.uni-trier.de/db/journals/cea/cea134.html#Bermejo17

Sensorització de robot agrícola per a la monitorització de cultiu en instal·lació agrivoltaica

Συγγραφείς: Díaz Barón, Eva

Συνεισφορές: Caballero Flores, David, García Ruiz, Francisco José, Universitat Politècnica de Catalunya. Departament d'Enginyeria Mecànica, Universitat Politècnica de Catalunya. Centre de Cooperació per al Desenvolupament, CDEI-DM - Centre de Disseny d'Equips Industrials-Dinàmica de Màquines

Πηγή: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Θεματικοί όροι: Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Cooperació per al desenvolupament::Projectes de cooperació, Sensors, Àrees temàtiques de la UPC::Enginyeria electrònica::Instrumentació i mesura::Sensors i actuadors, Agrotech, Agriculture--Data processing, Robotics, Agri-PV

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://hdl.handle.net/2117/406032

[Business : KPI] [part 2]
[Business : key performance indicators]

Συγγραφείς: Grigg, Joanna, Gray, Lynda, Taylor, Sandra

Πηγή: Country-wide (2010), Jan 2019; v.41 n.1:p.26-30

Σύνδεσμος πρόσβασης: https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE39331469

App'titude for tech; A job done even more efficiently; Data drives decisions; Iot : Internet of Things; Under the guidance of FarmIQ; Agrigate to extend free service; Synergies with information; Upping on-farm connectivity; Technology directory

Συγγραφείς: Christian, Glenys

Πηγή: New Zealand dairy exporter (1988), Aug 2017; v.93 n.1:p.53-72
Dairy exporter

Σύνδεσμος πρόσβασης: https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE28478077

Report card for the business; Monitor what’s critical; Definition needed [part 1]
Monitor what’s critical
Definition needed

Συγγραφείς: Grigg, Joanna

Πηγή: Country-wide (2010), Dec 2018; v.40 n.12:p.18-20

Σύνδεσμος πρόσβασης: https://ndhadeliver.natlib.govt.nz/delivery/DeliveryManagerServlet?dps_pid=IE37968392

Artificial Intelligence Applications in Agriculture and Food Quality Improvement

Συγγραφείς: Mohammad Ayoub Khan, Rijwan Khan, Pushkar Praveen

Πηγή: ebsco-3331833

Θεματικοί όροι: TECHNOLOGY & ENGINEERING / Agriculture / General, COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Food Science / General, Artificial intelligence, Agriculture--Data processing

Relation: http://dspace.kpfu.ru/xmlui/bitstream/net/184640/1/3331833.pdf; http://dspace.kpfu.ru/xmlui/bitstream/net/184640/2/3331833.epub; https://dspace.kpfu.ru/xmlui/handle/net/184640

Διαθεσιμότητα: https://dspace.kpfu.ru/xmlui/handle/net/184640

Review of electronic data processing of records and accounts for Iowa farmers

Συγγραφείς: Lemke, Harlan

Συνεισφορές: Economics, Department of Economics (LAS)

Θεματικοί όροι: Agriculture--Economic aspects, Agricultural and Resource Economics, Economics, Statistical Models, Agriculture--Data processing, Agricultural Economics

Περιγραφή αρχείου: application/pdf

Σύνδεσμος πρόσβασης: https://dr.lib.iastate.edu/bitstreams/5412b099-106c-4d1a-b44d-0cc25eb50c45/download
https://lib.dr.iastate.edu/rtd/16548/
https://ideas.repec.org/p/isu/genstf/1972010108000017547.html

Generative AI in Food Systems : Predictive Demand, Smart Supply Chains, and Sustainable Service Futures

Συγγραφείς: Geetika Madaan, Amrinder Singh, Bhupinder Pal Singh Chahal, Arokiaraj David, Gurmeet Singh

Resource Type: eBook.

Θέματα: Artificial intelligence, Artificial intelligence--Agricultural applicatons, Agriculture--Data processing

Categories: TECHNOLOGY & ENGINEERING / Agriculture / Sustainable Agriculture, BUSINESS & ECONOMICS / Industries / Agribusiness, COMPUTERS / Artificial Intelligence / General

Internet of Things and machine learning in agriculture: technological impacts and challenges De Gruyter frontiers in computational intelligence ;, v. 8./ edited by Vishal Jain, Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore.

Συγγραφείς: Jain Vishal, Chatterjee Jyotir Moy, Kumar Abhishek, Rathore Pramod Singh

Πηγή: EN05CEBSCO05C1765

Θεματικοί όροι: Agriculture -- Data processing, Internet of things, Artificial intelligence -- Agricultural applications, Machine learning, Agriculture -- Informatique, Internet des objets, Intelligence artificielle -- Applications agricoles, Apprentissage automatique, COMPUTERS / Information Technology, Electronic books

Relation: De Gruyter frontiers in computational intelligence. volume 8; De Gruyter frontiers in computational intelligence ;. v. 8.; http://dspace.kpfu.ru/xmlui/bitstream/net/180608/-1/2735191.pdf; https://dspace.kpfu.ru/xmlui/handle/net/180608

Διαθεσιμότητα: https://dspace.kpfu.ru/xmlui/handle/net/180608

Diseño e implementación de solución de deep learning sobre un sistema embebido, para la selección automática de mango ‘tommy atkins’

Συγγραφείς: Villota Cáceres, Juan Sebastián

Συνεισφορές: Chaparro Preciado, Javier Alberto, Estupiñan Escalante, Enrique, Apolo Apolo, Orly Enrique, Cano Tirado, David Alexánder

Θεματικοί όροι: Tecnología agrícola, Agricultural technology, Dispositivos con Internet integrado, Embedded Internet devices, Sistemas de computador embebidos, Embedded computer systems, Agricultura - Procesamiento de datos, Agriculture - Data processing, Computación en el borde, visión artificial en agricultura, sistemas embebidos, automatización, frutas, post-cosecha, microcontroladores, Edge Computing, computer vision in agriculture, embedded systems, automation, fruit, post-harvest, microcontroller

Περιγραφή αρχείου: 148 páginas; application/pdf

Relation: FAO. (2024). Major Tropical Fruits Market Review: Preliminary Results 2024 (inf. téc.) (Ac- cessed on 28 january 2025). Food y Agriculture Organization of the United Nations. Rome. https://openknowledge.fao.org/handle/20.500.14283/cd3818en; USDA. (2007). United States Standards for Grades of Mangos (inf. téc.) (Accessed on 28 january 2024). United States Department of Agriculture. https://www.ams.usda.gov/grades- standards/mango-grades-and-standards; Barman, U., Choudhury, R., Sahu, D., & Barman, G. (2020). Comparison of convolution neural networks for smartphone image based real time classification of citrus leaf disease. Computers and Electronics in Agriculture, 177, 105661. https://doi.org/https://doi.org/ 10.1016/j.compag.2020.105661; Frutícola, P. (2024). Colombia: exportación de mango azúcar a EE.UU. con proyección de crecimiento [Accessed on 13 march 2024]. https://www.portalfruticola.com/noticias/ 2024/03/13/colombia-exportacion-de-mango-azucar-a-ee-uu-con-proyeccion-de- crecimiento/; Ghazal, S., Qureshi, W. S., Khan, U. S., Iqbal, J., Rashid, N., & Tiwana, M. I. (2021). Analysis of visual features and classifiers for Fruit classification problem. Computers and Electronics in Agriculture, 187, 106267. https://doi.org/https://doi.org/10.1016/j.compag.2021. 106267; UNECE. (2023). UNECE Standard FFV-45 concerning the marketing and commercial quality control of Mangoes (inf. téc.) (Accessed on 28 january 2024). United Nations Economic Commission for Europe. https://unece.org/trade/wp7/FFV-Standards; Díaz Gómez, A., et al. (2024). Sistema de detección de distancia en tiempo real mediante dashcams [B.S. thesis] [Accessed on 7 february 2025]. https://rodin.uca.es/handle/ 10498/33602; Ramírez Alberto, L. (2021). Desarrollo de un sistema para la identificación temprana de la antracnosis en frutos de mango basado en visión de máquina. https://repositorio.unal. edu.co/handle/unal/80092; Zawbaa, H. M., Hazman, M., Abbass, M., & Hassanien, A. E. (2014). Automatic fruit classifica- tion using random forest algorithm. 2014 International Conference on Hybrid Intelligent Systems (HIS), 164-168. https://doi.org/https://doi.org/10.1109/HIS.2014.7086191; Tan, M., & Le, Q. V. (2019). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. International Conference on Machine Learning. https://doi.org/https://doi. org/10.48550/arXiv.1905.11946; Padda, M. S., do Amarante, C. V. T., Garcia, R. M., Slaughter, D. C., & Mitcham, E. J. (2011). Methods to analyze physico-chemical changes during mango ripening: A mul- tivariate approach. Scientia Horticulturae, 128(2), 108-118. https://doi.org/10.1016/j. postharvbio.2011.06.002; González-Fernández, J., & Hormaza, J. (2020). Plagas y enfermedades del mango (Mangifera indica L.) [Accessed on 20 December 2024]. CSIC-IHSM La Mayora. https://www. mango.org/wp-content/uploads/2020/08/Mango_Plagas_y_Enfermedades_SPN.pdf; Montenegro Bermudez, A. F. (2021). Detección y clasificación de antracnosis en mango usando imágenes hiperespectrales y técnicas de aprendizaje profundo [Accessed on 20 Decem- ber 2024]. https://repositorio.unal.edu.co/handle/unal/81735; Pereira, L. F. S., Barbon Jr, S., Valous, N. A., & Barbin, D. F. (2018). Predicting the ripening of papaya fruit with digital imaging and random forests. Computers and Electronics in Agriculture, 145, 76-82. https://doi.org/https://doi.org/10.1016/j.compag.2017.12.029; Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017). MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. arXiv preprint arXiv:1704.04861. https://doi.org/https: //doi.org/10.48550/arXiv.1704.04861; Zhao, X., Wang, L., Zhang, Y., Han, X., Deveci, M., & Parmar, M. (2024). A review of convolutional neural networks in computer vision. Artificial Intelligence Review, 57(99), 1-43. https://doi.org/https://doi.org/10.1007/s10462-024-10721-6; ONNX Community. (2024). ONNX: Open Neural Network Exchange [Accessed on 30 january 2025].; Núñez Bueno, L. (1996). Las moscas de las frutas en Colombia e incidencia en la fruticultura colombiana [Accessed on 15 November 2023]. Revista Colombiana de Entomología. https://repository.agrosavia.co/handle/20.500.12324/20433; ICA. (2022). Con un embarque de 20 toneladas, Colombia inició la exportación de mango fresco a Estados Unidos [Accessed on 20 December 2024]. https://www.ica.gov.co/noticias/ica- embarque-20toneladas-mango; Ploetz, R. C. (2003). Diseases of tropical fruit crops. CABI. https : / / doi . org / 10 . 1079 / 9780851993904.0000; You, J., Li, X., Low, M., Lobell, D., & Ermon, S. (2017). Deep gaussian process for crop yield prediction based on remote sensing data. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/https://doi.org/10.1609/aaai.v31i1.11172; Suharjito, Elwirehardja, G. N., & Prayoga, J. S. (2021). Oil palm fresh fruit bunch ripeness classification on mobile devices using deep learning approaches. Computers and Elec- tronics in Agriculture, 188, 106359. https://doi.org/https://doi.org/10.1016/j.compag. 2021.106359; https://repositorio.escuelaing.edu.co/handle/001/3579; Universidad Escuela Colombiana de Ingeniería; Repositorio Digital; https://repositorio.escuelaing.edu.co/

Διαθεσιμότητα: https://repositorio.escuelaing.edu.co/handle/001/3579
https://repositorio.escuelaing.edu.co/
https://catalogo-intra.escuelaing.edu.co/cgi-bin/koha/catalogue/detail.pl?biblionumber=24090

IoT Techniques for Digital Agriculture Monitoring and Soil Nutrients Assessment

Συγγραφείς: Marina T. Stojanova, Author, Dragutin A. Djukic, Author, Monika Stojanova, Author, Aziz Şatana, Author

Resource Type: eBook.

Θέματα: Plant nutrients--Monitoring, Agriculture--Data processing, Internet of things--Industrial applications, Soils and nutrition

Categories: BUSINESS & ECONOMICS / Industries / Agribusiness, TECHNOLOGY & ENGINEERING / Agriculture / Agronomy / Crop Science, COMPUTERS / Internet of Things (IoT)

Python for Agriculturists

Συγγραφείς: Muhammad Azhar Iqbal

Resource Type: eBook.

Θέματα: Python (Computer program language), Agriculture--Data processing

Categories: TECHNOLOGY & ENGINEERING / Agriculture / General

Blockchain and Digital Twin Applications in Smart Agriculture

Συγγραφείς: Amit Kumar Tyagi, Shrikant Tiwari

Resource Type: eBook.

Θέματα: Agricultural innovations, Agriculture--Data processing, Blockchains (Databases)--Industrial applications, Digital twins (Computer simulation)--Industrial applications

Categories: TECHNOLOGY & ENGINEERING / Agriculture / Agronomy / General, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Blockchain

Sustainable Agriculture Applications Using Large Language Models

Συγγραφείς: Raghavendra, M. Devadas, Vani, Hiremani, Praveen, Gujjar Jagannath, Lubna, Ambreen, Harold, Andrew Patrick

Resource Type: eBook.

Θέματα: Artificial intelligence--Agricultural applications, Agriculture--Data processing

Categories: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Agriculture / Sustainable Agriculture

Digital Technologies and Tools for Smart Agriculture

Συγγραφείς: Madhumathi Ramasamy, Karthigha Mohan, Pethuru Raj, Kai Sheng

Resource Type: eBook.

Θέματα: Agricultural innovations, Artificial intelligence--Agricultural applications, Agriculture--Data processing

Categories: SCIENCE / General, SCIENCE / Life Sciences / Botany, SCIENCE / Life Sciences / Ecology, SCIENCE / Environmental Science

Smart Systems : Methodological Approaches and Applications

Συγγραφείς: Faisal Talib, Muhammed Muaz

Resource Type: eBook.

Θέματα: Manufacturing processes--Data processing, Self-organizing systems, Systems engineering, Agriculture--Data processing, Artificial intelligence--Industrial applications, Expert systems (Computer science)

Categories: TECHNOLOGY & ENGINEERING / Electrical, TECHNOLOGY & ENGINEERING / Electronics / General, TECHNOLOGY & ENGINEERING / Mechanical, TECHNOLOGY & ENGINEERING / Manufacturing