Suchergebnisse - S. I: Intelligent Computing Methodologies in Machine learning for IoT Applications

Comparison of Tree‐Based Machine Learning Algorithms for Classification of Livestock Breeds Based On Post‐Thaw Spermatological Parameters.

Autoren: Özen, Doğukan Özen, Hülya Gül, Elif Bersu et al.

Quelle: Veterinary Medicine & Science. Sep2025, Vol. 11 Issue 5, p1-10. 10p.

Schlagworte: Livestock breeds, Machine learning, Semen analysis, CART algorithms, Classification, Cattle breeds

Biological innovation evaluation in higher education for the reform and exploration of innovation and entrepreneurship course teaching.

Autoren: Zhou, Haijuan Hou, Yali Qi, Xiaomeng et al.

Quelle: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 4, p1-14, 14p

Schlagwörter: BIOTECHNOLOGY, INTERNET of things, INNOVATION management, INNOVATIONS in business, AUTHENTIC assessment, HIGHER education, MACHINE learning

Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review.

Autoren: Akbarein, Hesameddin Taaghi, Mohammad Hussein Mohebbi, Mahyar et al.

Quelle: Veterinary Medicine & Science. May2025, Vol. 11 Issue 3, p1-29. 29p.

Schlagworte: Machine learning, Artificial intelligence, Veterinary medicine, Resource allocation, Medical research

SideCow-VSS: A Video Semantic Segmentation Dataset and Benchmark for Intelligent Monitoring of Dairy Cows Health in Smart Ranch Environments.

Autoren: Yao, Lei Liu, Jin Hong, Weinan et al.

Quelle: Veterinary Sciences. Nov2025, Vol. 12 Issue 11, p1104. 13p.

TYPES AND APPLICATIONS OF INNOVATIVE ARTIFICIAL INTELLIGENCE IN POULTRY FARMS.

Autoren: ABD EL-GHANY, Wafaa A.¹ wafaa.soliman@cu.edu.eg

Quelle: Online Journal of Animal & Feed Research (OJAFR). Jul2025, Vol. 15 Issue 4, p237-245. 9p.

A Systematic Review of IoT Technology and Applications in Animals.

Autoren: OZGER, Zeynep Banu CIHAN, Pınar GOKCE, Erhan

Quelle: Kafkas Üniversitesi Veteriner Fakültesi Dergisi. Jul/Aug2024, Vol. 30 Issue 4, p411-431. 21p.

Schlagworte: Internet of things, Precision farming, Animal behavior, Farm management, Livestock farms

OPtimized Data Management for IOT-Driven Healthcare: A Hybrid Indexing Framework for Beyond Visual Line of Sight (BVLoS) Flights.

Autoren: Pratima, Depa Mohammed, Moulana

Quelle: Journal of Pharmaceutical Innovation; Feb2026, Vol. 21 Issue 1, p1-12, 12p

Predictive Modelling Of Stress Levels: A Comparative Analysis Of Machine Learning Algorithms.

Autoren: Sasane, Sumit Mulla, Zameer Ahmed S.

Quelle: Journal of Advanced Zoology. 2024 Supplement, Vol. 45, p153-158. 6p.

Machine learning-based clinical mastitis detection in dairy cows using milk electrical conductivity and somatic cell count.

Autoren: Pan, Lihong Chen, Xiao Han, Ding et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-9. 9p.

Application of Artificial Intelligence Technologies as an Intervention for Promoting Healthy Eating and Nutrition in Older Adults: A Systematic Literature Review.

Autoren: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju et al.

Quelle: Nutrients. Oct2025, Vol. 17 Issue 20, p3223. 33p.

An extensive analysis of machine learning techniques for identifying glaucoma.

Autoren: Vinod Kumar R Sharmila Banu N

Quelle: International ophthalmology [Int Ophthalmol] 2025 Nov 07; Vol. 45 (1), pp. 466. Date of Electronic Publication: 2025 Nov 07.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Kluwer Country of Publication: Netherlands NLM ID: 7904294 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2630 (Electronic) Linking ISSN: 01655701 NLM ISO Abbreviation: Int Ophthalmol Subsets: MEDLINE

MeSH-Schlagworte: Machine Learning* , Glaucoma*/diagnosis , Tomography, Optical Coherence*/methods , Intraocular Pressure*/physiology , Diagnostic Techniques, Ophthalmological*, Humans ; Algorithms

Digital Sentience? Evaluating the Integration of AI‐Driven Tools in Animal Welfare Assessment.

Autoren: Platto, Sara¹ (AUTHOR) sara.platto@jhun.edu.cn

Quelle: Animal Research & One Health. Aug2025, Vol. 3 Issue 3, p344-347. 4p.

Adaptive and Energy-Efficient IoT Routing via DOS-RL with Bayesian Hyperparameter Tuning in SDN-Driven Architectures.

Autoren: Selvi, M. Senthamil Sudha, L.

Quelle: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 3, p173-192, 20p

Schlagwörter: WIRELESS sensor networks, SOFTWARE-defined networking, REINFORCEMENT learning, SENSOR networks, NETWORK performance

Exploring Machine Learning Methods for IoT Network Intrusion Detection Systems.

Autoren: Salama, Reda Alghamdi, Wajdi Yadav, Sameer et al.

Quelle: Journal of Advanced Zoology. 2023 Supplement, Vol. 44, p1045-1053. 9p.

Leveraging productivity indicators for anomaly detection in swine breeding herds with unsupervised learning.

Autoren: Pedro Mil-Homens, Mafalda Wang, Chong Trevisan, Giovani et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-16. 16p.

A Novel Lightweight Dairy Cattle Body Condition Scoring Model for Edge Devices Based on Tail Features and Attention Mechanisms.

Autoren: Liu, Fan Zhang, Yongan Liu, Yanqiu et al.

Quelle: Veterinary Sciences. Sep2025, Vol. 12 Issue 9, p906. 25p.

Designing A Cost-Effective And Affordable Iot Based Device For Skin Disease Identification.

Autoren: A. P., Swarnalatha K., Jagadeeshkumar R., Karthikeyan et al.

Quelle: Journal of Advanced Zoology. 2024, Vol. 45 Issue 4, p175-183. 9p.

Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence.

Autoren: Mazhar, Tehseen Talpur, Dhani Bux Shloul, Tamara Al et al.

Quelle: Brain Sciences (2076-3425); Apr2023, Vol. 13 Issue 4, p683, 30p

Schlagwörter: ARTIFICIAL intelligence, SMART cities, DEEP learning, MACHINE learning, INTERNET content, FACIAL transplantation

Capítulo 2: Aplicaciones del Internet de las Cosas (IoT) y la computación en la nube en el monitoreo ambiental: Revisión sistemática y análisis de datos

Autoren: Baena Navarro, Rubén Enrique Carriazo Regino, Yulieth Paola Macea Anaya, Mario Ramón

Quelle: https://repositorio.unicordoba.edu.co/entities/publication/2969cc27-7e56-4481-845d-db2325dd3268.

Schlagwörter: 000 - Ciencias de la computación, información y obras generales, Internet de las Cosas, Computación en la Nube, Monitoreo Ambiental, Análisis de Datos, Salud Pública, Internet of things, Cloud computing, Environmental monitoring, Data analysis, Public health

Dateibeschreibung: 16 p.; application/pdf

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Verfügbarkeit: https://hdl.handle.net/20.500.12494/59316

Dosimetría ambiental mediante IoT: innovaciones y aplicaciones avanzadas

Autoren: Baena-Navarro, Rubén Carriazo-Regino, Yulieth Macea-Anaya, Mario

Schlagwörter: Dosimetría

Dateibeschreibung: application/pdf

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