Integration of IT solutions for resource management in environmentally sustainable agriculture

Open Access

Issue		BIO Web Conf. Volume 145, 2024 International Scientific Forestry Forum 2024: Forest Ecosystems as Global Resource of the Biosphere: Calls, Threats, Solutions (Forestry Forum 2024)


Article Number		06008
Number of page(s)		9
Section		Forestry, Forest Management and Multipurpose Use of Forests
DOI		https://doi.org/10.1051/bioconf/202414506008
Published online		28 November 2024

Tholhappiyan, T., Sankar, S., Selvakumar, V., & Robert, P. (2023). Agriculture Monitoring System with Efficient Resource Management using IoT. 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), 1628-1633. https://doi.org/10.1109/ICAISS58487.2023.10250720. [Google Scholar]
Savchenko M., Tynchenko V. Unsupervised Production Machinery Data Labeling Method Based on Natural Language Processing //2024 International Russian Smart Industry Conference (SmartIndustryCon). – IEEE, 2024. – С. 416-421. [Google Scholar]
Larichev, P., Tynchenko, V., & Nekrasov, I. (2024, May). Application of Petri Nets for Modeling Ore Flows to Create Dynamic Management and Quality Control System in Mineral Resource Complexes. In 2024 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) (pp. 1089-1094). IEEE. [Google Scholar]
Ali, A., Hussain, T., Tantashutikun, N., Hussain, N., & Cocetta, G. (2023). Application of Smart Techniques, Internet of Things and Data Mining for Resource Use Efficient and Sustainable Crop Production. Agriculture. https://doi.org/10.3390/agriculture13020397. [Google Scholar]
Martyushev N. V. et al. Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption //Energies. – 2023. – Т. 16. – №. 2. – С. 729. [CrossRef] [Google Scholar]
Shutaleva A. et al. Sustainability of inclusive education in schools and higher education: Teachers and students with special educational needs //Sustainability. – 2023. – Т. 15. – №. 4. – С. 3011. [CrossRef] [Google Scholar]
Zhao, W., Wang, M., & Pham, V. (2023). Unmanned Aerial Vehicle and Geospatial Analysis in Smart Irrigation and Crop Monitoring on IoT Platform. Mobile Information Systems. https://doi.org/10.1155/2023/4213645. [Google Scholar]
Investigation of properties of laminar antiferromagnetic nanostructures / B. V. Malozyomov, V. S. Tynchenko, V. A. Kukartsev [et al.] // CIS Iron and Steel Review. – 2024. – Vol. 27. – P. 84-90.DOI 10.17580/cisisr.2024.01.13.. [CrossRef] [Google Scholar]
Panfilova T. A., Kukartsev V. A., Tynchenko V. S.,Mikhalev A. S., Xiaogang Wu Treatment of wastewater from mining industrial enterprises from phenols. MIAB. Mining Inf. Anal. Bull. 2024;(7-1):72-82. [In Russ]. DOI: 10.25018/0236_1493_2024_71_0_72. [Google Scholar]
Elbasi, E., Mostafa, N., AlArnaout, Z., Zreikat, A., Cina, E., Varghese, G., Shdefat, A., Topcu, A., Abdelbaki, W., Mathew, S., & Zaki, C. (2023). Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review. IEEE Access, 11, 171-202. https://doi.org/10.1109/ACCESS.2022.3232485. [CrossRef] [Google Scholar]
Alahmad, T., Neményi, M., & Nyéki, A. (2023). Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review. Agronomy. https://doi.org/10.3390/agronomy13102603. [Google Scholar]
Degtyarevaa K. et al. Automated System for Accounting of Customers and Orders//2024 23rd International Symposium INFOTEH-JAHORINA (INFOTEH). – IEEE, 2024. – С. 1-4. [Google Scholar]
Bassine, F., Epule, T., Kechchour, A., & Chehbouni, A. (2023). Recent applications of machine learning, remote sensing, and iot approaches in yield prediction: a critical review. ArXiv, abs/2306.04566. https://doi.org/10.48550/arXiv.2306.04566. [Google Scholar]
Kukartsev V. et al. Application of non-parametric learning method in soil suitability assessment in present day economy //Journal of Infrastructure, Policy and Development. – 2024. – Т. 8. – №. 7. – С. 4074. [CrossRef] [Google Scholar]
Epikhin A.I., Kukartseva O.I., Tynchenko V.S., Nguyen V.X. Energy saving and energy efficiency assessment of a coal mining enterprise. Sustainable Development of Mountain Territories. 2024, vol. 16, no. 2, pp. 679–691. DOI: https://doi.org/10.21177/1998-4502-2024-16-2-679-691. [CrossRef] [Google Scholar]
Filina O. A. et al. Increasing the Efficiency of Diagnostics in the Brush-Commutator Assembly of a Direct Current Electric Motor //Energies. – 2023. – Т. 17. – №. 1. – С. 17. [CrossRef] [Google Scholar]
Tynchenko Ya.A., Kukartsev V.V., Gladkov A.A., Panfilova T.A. Assessment of technical water quality in mining based on machine learning methods. Sustainable Development of Mountain Territories, 2024, vol. 16, no. 1, pp. 56–69. (In Russ.). DOI: 10.21177/1998-4502-2024-16-1-56-69. [CrossRef] [Google Scholar]
Brigida V. et al. Technogenic Reservoirs Resources of Mine Methane When Implementing the Circular Waste Management Concept //Resources. – 2024. – Т. 13. –№. 2. – С. 33. [CrossRef] [Google Scholar]
Fedorova N. et al. Cost-effectiveness of development strategy implementation: Key metrics and analysis methods for successful enterprise management //BIO Web of Conferences. – EDP Sciences, 2024. – Т. 116. – С. 05003. [CrossRef] [EDP Sciences] [Google Scholar]
Fedorova N. et al. Analytical methods and tools for business process optimization//BIO Web of Conferences. – EDP Sciences, 2024. – Т. 113. – С. 05009. [CrossRef] [EDP Sciences] [Google Scholar]
Kravtsov, K. et al. Creation of multi-link automatic parameter control systems at nuclear power plants. In 2024 12th International Conference on Smart Grid (icSmartGrid) (pp. 455-458). IEEE. [Google Scholar]
Degtyareva K. et al. Manufacturing of 20XMFL Steel Bushing Casting //2024 23rd International Symposium INFOTEH-JAHORINA (INFOTEH). – IEEE, 2024. – С. 1-5. [Google Scholar]
Kaung P. A., Isakov A. E., Panfilov I. A., Tynchenko V. V., Stupina A. A. Principles for forming environmentally safe and economically effective sustainable development of geo resources. MIAB. Mining Inf. Anal. Bull. 2024;(7-1):159-175. [In Russ]. DOI: 10.25018/0236_1493_2024_71_0_159. [Google Scholar]
Lomazov A. V. et al. Mathematical model for diagnosing a nonlinear elastic medium//Third International Conference on Optics, Computer Applications, and Materials Science (CMSD-III 2023). – SPIE, 2024. – Т. 13065. – С. 275-280. [Google Scholar]
Lomazov A. et al. Intelligent Support for Adaptive Constructing of Trajectory in Project Implementation Scenario Network //International Scientific Conference Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East. – Cham : Springer Nature Switzerland, 2023. – С. 243-251. [Google Scholar]
Bukhtoyarov V. et al. Adaptive Methods for the Structural Optimization of Neural Networks and Their Ensemble for Data Analysis //International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production. – Cham : Springer Nature Switzerland, 2023. – С. 143-157. [Google Scholar]
Malozyomov B. V. et al. Determination of the Performance Characteristics of a Traction Battery in an Electric Vehicle //World Electric Vehicle Journal. – 2024. – Т. 15. – №. 2. – С. 64. [CrossRef] [Google Scholar]
Motia, S., & Reddy, S. (2021). Exploration of machine learning methods for prediction and assessment of soil properties for agricultural soil management: a quantitative evaluation. Journal of Physics: Conference Series, 1950. https://doi.org/10.1088/1742-6596/1950/1/012037. [Google Scholar]
Kukartsev, V. et al. Using Machine Learning Techniques to Simulate Network Intrusion Detection. In 2024 International Conference on Intelligent Systems for Cybersecurity (ISCS) (pp. 1-4). IEEE. [Google Scholar]
Panfilov I. et al. Increasing competitiveness of enterprises by optimizing business processes as a factor of sustainable development of industrial region //E3S Web of Conferences. – EDP Sciences, 2024. – Т. 531. – С. 05019. [CrossRef] [EDP Sciences] [Google Scholar]
Panfilov, I. et al. Modeling of the casting process for casting” Flywheel” of cast iron SCH20. In 2024 12th International Conference on Smart Grid (icSmartGrid) (pp. 459-463). IEEE. [Google Scholar]
Lipatov A.; Belyanova E.; Petunina I. Prediction the biodegradation rate of soil contaminated with different oil concentrations // Results in Nonlinear Analysis. – 2024.– Т. 7, №. 1. – С. 24-34. doi: 10.31838/rna/2024.07.01.004 [Google Scholar]
Borodulin A. S. et al. A Method for Assessing the Adhesion Strength of an Elementary Fiber–Epoxy Matrix System //Polymer Science, Series D. – 2022. – Т. 15. – №. 4. – С. 517-522. [CrossRef] [Google Scholar]
Chukov N. A. et al. Synthesis and properties of polyetheretherketones //International Journal of Pharmaceutical Research. – 2020. – Т. 12. – №. Suppl. ry 2. – С. 1040-1045. [Google Scholar]
Nelub, V. Economic analysis of data protection in systems with complex architecture using neural network methods / V. Nelub, A. Gantimurov, A. Borodulin //Економiчний часопис-XXI. – 2020. – Vol. 185, No. 9-10. – P. 178-188. – DOI 10.21003/ea.V185-17. – EDN ESORRK. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.