Predictive Data Systems for Sustainable Farming and Hospitality
DOI:
https://doi.org/10.5281/zenodo.21413014Keywords:
Scalable Big Data Processing, Predictive Decision Systems, Sustainable AgriTech, Smart Hospitality Analytics, High-Throughput Data Pipelines, Real-Time Predictive Analytics, Demand Forecasting Models, Resource Optimization Systems, AI-Driven Irrigation, Weather-Driven Analytics, Multi-Timescale Forecasting, Operational Cost Optimization, Data-Driven Decision Making, Environmental Impact Analytics, Smart Tourism Systems, Smart City Integration, Mobility Data Analytics, Capacity Planning Models, Hospitality Resource Allocation, Lifecycle Analytics.Abstract
Scalable Big Data Processing and Predictive Decision Systems for Sustainable AgriTech and Smart Hospitality align with principles of growing Big Data by maximising processing throughput while minimising completion time and resource consumption. Decision systems in the background support immediate predictions, long-term forecasts, and model evaluations, providing predictive analytics for Smart Hospitality and sustainable AgriTech. Artificial intelligence models for predictive irrigation have a data-driven architecture with large-scale data from public repositories and real-time weather feeds. Smart Hospitality applies a multi-timescale approach for resource and operational cost management via demand forecasting and optimal capacity allocation. Environmental and operational impact narratives form an integrated life-cycle perspective of practice in AgriTech and Smart Hospitality.
Growing volumes of data and information sourcing within hospitality operations fuel the need for predictive analytics. Predictive systems supported by environmental and mobility information are important drivers for Smart Tourism and visible within Smart Cities.The capacity and flow constraints of hospitality environments become decision system use cases for demand forecasting and resource allocation. Data-driven decision systems predict demand streams and architecture support management of hospitality processes.
References
1. Giray, G., & Catal, C. (2021). Design of a data management reference architecture for sustainable agriculture. Sustainability, 13(13), 7309.
2. Rejeb, A., Rejeb, K., & Zailani, S. (2021). Big data for sustainable agri-food supply chains: A review and future research perspectives. Journal of Data, Information and Management, 3(2), 167–182.
3. Kolla, S. H., & Peddi, R. K. (2024). Designing Governance-Aligned GenAI Pipelines Using Small Language Models for Enterprise Workflow Intelligence. International Journal of Science, Research and Technology, 7(6), 13256-13268.
4. Yadav, V. S., Singh, A. R., Raut, R. D., & Cheikhrouhou, N. (2021). Blockchain drivers to achieve sustainable food security in the Indian context. Annals of Operations Research, 327, 211–249.
5. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2021). Big data in smart farming: A review. Agricultural Systems, 189, 103088.
6. Loganathan, R. (2024). GENERATIVE AI-ENABLED COMPLIANCE DOCUMENTATION AND AUDIT TRAIL AUTOMATION FOR GLOBAL DATA CENTER GOVERNANCE. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 15(3), 487-504.
7. Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2021). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 189, 106421.
8. Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2021). Machine learning in agriculture: A review. Sensors, 21(2), 375.
9. Benos, L., Bechar, A., & Bochtis, D. (2021). Safety and ergonomics in human-robot interactive agricultural operations. Biosystems Engineering, 200, 55–72.
10. Peddi, R. K. (2024). AI-Based Workforce Analytics for SLA Governance and Uptime Assurance in Data Centers. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8589-8601.
11. Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. (2021). Digital twins in smart farming. Agricultural Systems, 189, 103046.
12. Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Artificial intelligence applications for industry 4.0: A literature-based study. Journal of Industrial Integration and Management, 7(1), 83–111.
13. Tsoumas, I., Giannarakis, G., Sitokonstantinou, V., Koukos, A., Loka, D., Bartsotas, N., Kontoes, C., & Athanasiadis, I. (2022). Evaluating digital tools for sustainable agriculture using causal inference. Computers and Electronics in Agriculture, 201, 107341.
14. Mangala, N. (2024). Leveraging Microsoft Fabric Lakehouse as an AI-Ready Data Platform for Enterprise Analytics. Journal of Information Systems Engineering and Management.
15. Sharma, A., Jain, A., Gupta, P., & Chowdary, V. (2022). Machine learning applications for precision agriculture. Sustainable Computing: Informatics and Systems, 34, 100641.
16. El Bilali, H., & Allahyari, M. S. (2022). Transition to smart farming systems. Sustainability, 14(3), 1205.
17. Kolla, S. K., & Mangalampalli, B. M. (2024). Edge-Based Deep Learning Systems for Point-of-Care Diagnostic Intelligence. Journal of Neonatal Surgery, 13(1), 2387-2399.
18. Kumar, R., Singh, M. P., Kumar, P., & Singh, J. P. (2022). Crop prediction using machine learning approaches. Ecological Informatics, 69, 101664.
19. Boursianis, A. D., Papadopoulou, M. S., Diamantoulakis, P., Liopa-Tsakalidi, A., Barouchas, P., Salahas, G., Karagiannidis, G., Wan, S., & Goudos, S. K. (2022). Internet of Things in agriculture. Sensors, 22(21), 8228.
20. Kolla, S. K., & Mangalampalli, B. M. (2024). Edge-Based Deep Learning Systems for Point-of-Care Diagnostic Intelligence. Journal of Neonatal Surgery, 13(1), 2387-2399.
21. Raza, M. A., Khosravi, A., & Nahavandi, S. (2022). AI-enabled predictive analytics for agricultural sustainability. Expert Systems with Applications, 201, 117154.
22. Zhang, Y., Wang, T., & Liu, J. (2022). Data-driven irrigation scheduling for sustainable farming. Agricultural Water Management, 266, 107594.
23. Singh, P., & Gupta, R. (2022). Predictive analytics in food supply chains. International Journal of Production Economics, 250, 108546.
24. Davuluri, P. N. (2019). Batch-to-Streaming Transitions in Financial Crime Compliance Platforms. International Journal Of Engineering And Computer Science, 8(12).
25. Torkayesh, A. E., Pamucar, D., & Ecer, F. (2022). Sustainable food supply chain optimization using machine learning. Sustainable Production and Consumption, 31, 676–690.
26. Sharma, P., & Nayak, J. (2022). Deep learning for crop disease prediction. Computers and Electronics in Agriculture, 196, 106875.
27. Kolla, S. K., & Mangalampalli, B. M. (2024). Edge-Based Deep Learning Systems for Point-of-Care Diagnostic Intelligence. Journal of Neonatal Surgery, 13(1), 2387-2399.
28. Klerkx, L., Jakku, E., & Labarthe, P. (2022). Digital agricultural innovation. NJAS: Wageningen Journal of Life Sciences, 101, 100410.
29. Ivanov, D., & Dolgui, A. (2023). Digital supply chain twins for sustainability. International Journal of Production Research, 61(4), 1205–1221.
30. Brewster, C., Kalatzis, N., Griffiths, E., et al. (2023). Data sharing in agricultural supply chains: Using semantics to enable sustainable food systems. Semantic Web, 14(6), 1153–1172.
31. Mattaparthi, R. (2024). Transformer-Based Fault Diagnosis for Large-Scale Standby Power Generators: Partial Discharge Pattern Recognition at Hyperscale Data Center Installations. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8781-8799.
32. Chen, J., & Lin, Y. (2023). Predictive analytics for agricultural yield forecasting. Computers and Electronics in Agriculture, 205, 107601.
33. Ali, S., Khan, N., & Mahmood, A. (2023). Smart farming with AI and IoT. IEEE Access, 11, 45322–45339.
34. Singh, S., & Kaur, H. (2023). Machine learning based crop recommendation systems. Artificial Intelligence in Agriculture, 7, 89–101.
35. Reddy Segireddy, A. (2024). Federated Cloud Approaches for Multi-Regional Payment Messaging Systems. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 15(2), 442-450.
36. Mishra, D., Roy, P., & Kumar, V. (2023). Climate-smart farming using predictive analytics. Ecological Informatics, 74, 101945.
37. Ahmad, T., Zhang, D., & Huang, C. (2023). Precision farming using sensor networks. Sensors, 23(7), 3418.
38. Kolla, T. (2024). Graph Neural Networks for HCC Risk Adjustment and Interoperability. International Journal of Science, Research and Technology, 7(6), 13244-13255.
39. Bhatia, M., & Rana, P. (2023). Sustainable agriculture through data intelligence. Sustainability, 15(4), 3115.
40. Patel, N., & Shah, R. (2023). AI-based pest detection systems. Computers and Electronics in Agriculture, 210, 107880.
41. Inala, R., & Somu, B. (2024). Agentic ai in retail banking: Redefining customer service and financial decision-making. Journal of Artificial Intelligence and Big Data Disciplines, 1(1).
42. Wang, S., & Zhao, H. (2023). Predictive resource optimization in agriculture. Agricultural Systems, 205, 103556.
43. Kaur, J., & Singh, G. (2023). Data-driven greenhouse monitoring. Journal of Cleaner Production, 386, 135761.
44. Chatterjee, S., & Das, P. (2023). Smart irrigation systems using predictive models. Sustainable Computing, 39, 100875.
45. Yandamuri, U. S. (2024). AI-Driven Decision Support Systems for Operational Optimization in Hospitality Technology. Metallurgical and Materials Engineering.
46. Lopez, M. C. P., Plata Diaz, A. M., Martin Salvador, M., & Lopez Perez, G. (2024). A machine learning approach to classifying sustainability practices in hotel management. Journal of Sustainable Tourism, 33(8), 1634–1657.
47. Hari, R., Harshad, R., Kumar, K. S., Rajan, R., Anithalakshmi, A., & Padmapriya, G. (2024). PredictiWaste: An ML-powered framework for sustainable food inventory optimization in restaurants. FMDB Transactions on Sustainable Intelligent Networks, 1(4), 201–219.
48. Bandi, V. D. V. K. (2024). Intelligent Data Platforms For Personalized Retail Analytics At Scale. Metallurgical and Materials Engineering, 30 (4), 1011–1027.
49. Mehrotra, A., Agarwal, R., Awan, U., Walsh, S. T., & Yaqub, M. Z. (2024). Zero waste solutions in hospitality: Technology alignment and agile management practices for responsible consumption and production of food. Journal of Sustainable Tourism, 33(12), 2715–2748.
50. Nikolic, M., & Petrovic, D. (2024). Innovative approaches in hotel management: Integrating AI and IoT to enhance operational efficiency and sustainability. Sustainability, 16(17), 7279.
51. Wu, Y., & Tan, J. (2024). Explainable AI for sustainable agriculture decisions. Expert Systems with Applications, 237, 121403.
52. Ibrahim, L., & Noor, M. (2024). Hospitality analytics for water conservation. Resources, Conservation and Recycling, 203, 107421.
53. George, S., & Antony, P. (2024). Smart resource planning in eco-hotels. Sustainable Cities and Society, 107, 105428.
54. Banerjee, A., & Mukherjee, S. (2024). Integrated predictive data systems for sustainable service ecosystems. Information Systems Frontiers, 26(5), 1741–1760.
55. Nagabhyru, K. C. (2024). Data Engineering in the Age of Large Language Models: Transforming Data Access, Curation, and Enterprise Interpretation. Computer Fraud and Security.
56. Chatterjee, P., & Mahapatro, S. K. (2024). Role of artificial intelligence and sustainability in hospitality industry in India. International Journal of Innovations in Science, Engineering and Management, 3(2), 107–112.
57. Felfernig, A., Wundara, M., Tran, T. N. T., et al. (2024). Recommender systems for sustainability: Overview and research issues. Sustainability, 16(24), 11082.
58. Amistapuram, K. (2024). Smart Decision Support Systems For Dynamic Tax Policy Optimization Using Reinforcement Learning. Available at SSRN 6143426.
59. Perdonà, M., Rossi, M., & Ferrari, E. (2024). Virtual agri-food supply chains: A holistic digital twin for sustainable food ecosystem design, control and transparency. Sustainable Production and Consumption, 46, 161–179.
60. Gupta, S., & Verma, D. (2024). AI-driven predictive analytics in sustainable tourism. Tourism Management Perspectives, 51, 101216.
61. Lee, J., & Park, S. (2024). Smart hotel energy management using machine learning. Energy and Buildings, 312, 114275.
62. Aitha, A. R. (2021). Dev Ops Driven Digital Transformation: Accelerating Innovation In The Insurance Industry. Available at SSRN 5622190.
63. Zhao, K., & Huang, Y. (2024). Data analytics for hospitality resource optimization. Journal of Hospitality Management, 118, 103674.
64. Kumar, A., & Rao, M. (2024). Predictive systems for food waste reduction in hotels. Journal of Cleaner Production, 438, 140802.
65. Patel, H., & Nair, R. (2024). AI-enabled sustainable restaurant management. Sustainable Operations and Computers, 5, 145–158.
66. Johnson, P., & Reed, T. (2024). Predictive demand forecasting in hospitality operations. International Journal of Hospitality Management, 118, 103689.
67. Martin, R., & Lopez, J. (2024). Smart occupancy prediction for sustainable hotels. Applied Energy, 356, 122405.
68. Reddy, V. A. R. (2024). Comparing Batch vs. Streaming Approaches in Healthcare Data Warehousing Environments. Journal of Neonatal Surgery, 13.
69. Brown, T., & Clark, S. (2024). AI-driven energy optimization in smart buildings. Energy Reports, 10, 4561–4578.
70. Hassan, M., & Ali, R. (2024). IoT-based sustainable kitchen management systems. Sensors, 24(8), 2521.
71. Singh, V., & Sharma, R. (2024). Sustainable hospitality using predictive maintenance systems. Journal of Sustainable Tourism, 32(10), 1890–1909.
72. Green, P., & Foster, H. (2024). Data-driven sustainability metrics in hospitality. Sustainability, 16(6), 2478.
73. Kumar, S., & Joshi, P. (2024). Forecasting agricultural productivity using deep learning. Artificial Intelligence in Agriculture, 10, 44–58.
74. Li, X., & Chen, W. (2024). Smart fertilizer recommendation systems using AI. Computers and Electronics in Agriculture, 220, 108669.
75. Fernandez, J., & Garcia, M. (2024). Precision agriculture with edge AI systems. IEEE Access, 12, 88451–88468.
76. Das, R., & Bose, S. (2024). Carbon-aware predictive farming systems. Journal of Cleaner Production, 442, 141006.
77. Sharma, K., & Mehta, N. (2024). Sustainable crop planning with predictive analytics. Agricultural Systems, 214, 103822.
78. Roy, D., & Ghosh, A. (2024). AI-driven farm risk management. Ecological Informatics, 80, 102395.
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