Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things DOI Open Access
Hsin‐Te Wu, Jianping Li, Mu‐Yen Chen

et al.

Journal of Organizational and End User Computing, Journal Year: 2024, Volume and Issue: 36(1), P. 1 - 19

Published: Nov. 29, 2024

This paper proposes building a sustainable development computing system for large organizations based on AI and IoT. The leverages to calculate the carbon emissions caused by organizations' activities utilizes IoT devices monitor compute environmental coefficients. also employs automated achieve net-zero emissions. By integrating weather forecast information from meteorological agencies understand external conditions, consulting knowledge database devise appropriate response strategies, can activate relevant equipment improve both organization's living environment emission processes. feasibility practical application of this will be demonstrated through actual simulations enhance its viability effectiveness.

Language: Английский

The Economic and Technological Challenges of the Agri-Development Implementation Model in the Case of the Wielkopolska Region in Poland DOI Creative Commons
Leszek Wanat, Jan Sikora, L. Majchrzak

et al.

Agriculture, Journal Year: 2025, Volume and Issue: 15(4), P. 412 - 412

Published: Feb. 15, 2025

This study discusses key issues relating to the agri-development perspective, which is based on “numbered” agriculture model. Selected economic and technological dilemmas related agribusiness development in Wielkopolska region of Poland were reviewed. Based not only a literature review, but also our own research, we identified current challenges for farmers terms innovation, green energy, environmental ideas. Using diagnostic survey method, with agricultural practitioners as experts, potential directions regional assessed from perspective programming next stages “agricultural revolution”. Individual in-depth interviews conducted purposely invited Wielkopolska, one most agriculturally developed regions Poland. By verifying ex post assessment pillars Agriculture “3.0” “4.0” concepts’ adaptation model, carried out respondents’ farms, optimal model farm operation was sought. The assumed implementation had taken place that “Agriculture 5.0” under conditions evaluated, possible. so-defined hypothesis partially confirmed (conditionally). provides path idea N.0”, value “N” yet known. Finally, conclusions recommendations Wielkopolska’s formulated.

Language: Английский

Citations

0

Weather-Driven Predictive Models for Jassid and Thrips Infestation in Cotton Crop DOI Open Access
Rubaba Hamid Shafique, Sharzil Haris Khan,

Jihyoung Ryu

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 2803 - 2803

Published: March 21, 2025

Agriculture is a vital contributor to global food security but faces escalating threats from environmental fluctuations and pest incursions. Among the most prevalent destructive pests, Jassid (Amrasca biguttula) Thrips (Thrips tabaci) frequently afflict cotton, okra, other major crops, resulting in substantial yield losses worldwide. This paper integrates five machine learning (ML) models predict incidence based on key meteorological attributes, including temperature, relative humidity, wind speed, sunshine hours, evaporation. Two ensemble strategies, soft voting stacking, were evaluated enhance predictive performance. Our findings indicate that stacking yields superior results, achieving high multi-class AUC scores (0.985). To demystify underlying mechanisms of best-performing ensemble, this study employed SHapley Additive exPlanations (SHAP) quantify contributions individual weather parameters. The SHAP analysis revealed Standard Meteorological Week, evaporation, humidity consistently exert strongest influence forecasts. These insights align with biological studies highlighting role seasonality humid conditions fostering proliferation. Importantly, explainable approach bolsters practical utility AI-based solutions for integrated management (IPM), enabling stakeholders—farmers, extension agents, policymakers—to trust effectively operationalize data-driven recommendations. Future research will focus integrating real-time data satellite imagery further prediction accuracy, as well incorporating adaptive techniques refine model performance under varying climatic conditions.

Language: Английский

Citations

0

Digital motivation, knowledge, and skills: Pathways to adaptive millennial farmers DOI Creative Commons

Hari Otang Sasmita,

Amiruddin Saleh, Wahyu Budi Priatna

et al.

Open Agriculture, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 1, 2025

Abstract The transformation of the agricultural sector amidst decline in farmer regeneration era Industrial Revolution 4.0 and threat climate change demands a new approach that combines digital technology with adaptability human resources to deal change. It is important understand how effectively individual farmers respond arising from uncertainty, complexity, rapid changes their work environments, which are often associated unclear challenges. Measuring level competence, online participation, millennial can form basis for formulating resource development strategies. aim this study analyze mechanism communication competence influencing small-scale facing technological disruptions. Data 345 were obtained survey conducted Bogor Regency, Indonesia. Partial least squares structural equation modeling method was applied test hypothetical model. findings showed motivation has positive significant relationship knowledge skills. In addition, skills have statistically impact on adaptive performance farmers, as improve through increased involvement participation. This contributes micro-analysis perspective providing relevant implications policymakers an effort produce who competencies

Language: Английский

Citations

0

Digitalization in AgriEngineering 5.0 DOI
Serra Aksoy, Pınar Demircioğlu, İsmail Böğrekçi

et al.

Lecture notes in mechanical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 449 - 462

Published: Jan. 1, 2025

Citations

0

Towards the Development of eXplainable Digital Twins for Precision Agriculture DOI
Prashant Gupta, Bireshwar Dass Mazumdar, Subash Nataraja Pillai

et al.

Published: Aug. 2, 2024

Language: Английский

Citations

0

Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things DOI Open Access
Hsin‐Te Wu, Jianping Li, Mu‐Yen Chen

et al.

Journal of Organizational and End User Computing, Journal Year: 2024, Volume and Issue: 36(1), P. 1 - 19

Published: Nov. 29, 2024

This paper proposes building a sustainable development computing system for large organizations based on AI and IoT. The leverages to calculate the carbon emissions caused by organizations' activities utilizes IoT devices monitor compute environmental coefficients. also employs automated achieve net-zero emissions. By integrating weather forecast information from meteorological agencies understand external conditions, consulting knowledge database devise appropriate response strategies, can activate relevant equipment improve both organization's living environment emission processes. feasibility practical application of this will be demonstrated through actual simulations enhance its viability effectiveness.

Language: Английский

Citations

0