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All Journal Techno Agriculturae Studium of Research Research of Scientia Naturalis Journal of Social Entrepreneurship and Creative Technology
Lars Jensen
University of Copenhagen
Agriculture, Biological Sciences & Forestry Chemistry Decision Sciences, Operations Research & Management Physics

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INTEGRATING DIGITAL TECHNOLOGIES IN AGRICULTURE LEVERAGING DRONES, SENSORS, AND AI FOR PRECISION CROP MANAGEMENT Lars Jensen; Maria Nielsen; Ismail Ismail
Techno Agriculturae Studium of Research Vol. 3 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v3i3.4215

Abstract

Agricultural production increasingly faces climate variability, resource scarcity, environmental degradation, and rising demands for sustainable food systems, creating an urgent need for precise and adaptive crop management. This study examines how integrated drones, wireless field sensors, and artificial intelligence can enhance precision crop management by transforming heterogeneous agricultural data into actionable decision intelligence. A mixed-methods field-based design combined quasi-experimental comparisons, drone-based remote sensing, continuous sensor monitoring, multimodal data integration, artificial intelligence modeling, agronomic measurements, and stakeholder interviews to evaluate technological and operational performance. The findings indicate that integrated digital management improved crop-stress detection, accelerated management responses, increased productivity, and enhanced water, fertilizer, and pesticide-use efficiency compared with conventional practices. Multimodal integration generated stronger predictive performance than isolated technologies by combining spatial, temporal, and environmental information, while human validation remained essential for adapting algorithmic recommendations to field conditions. The study concludes that effective precision agriculture depends not on technology quantity but on integration quality and the capacity to translate data into timely, interpretable, and contextually relevant interventions. The proposed Integrated Agricultural Digital Intelligence Framework establishes a continuous Sense–Integrate–Analyze–Decide–Act–Learn cycle, providing a foundation for adaptive, resource-efficient, and sustainable crop management across diverse agricultural contexts worldwide.
THE PROCEDURAL GENERATION OF LUDIC NARRATIVES: AN INNOVATIVE TECHNOLOGICAL APPROACH TO DYNAMIC STORYTELLING IN GAME DESIGN Lars Jensen; Lim Haeun; Pieter Hendriks
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i6.2968

Abstract

The evolution of dynamic storytelling in game design has been significantly influenced by advances in procedural generation techniques, allowing for the creation of adaptive and player-driven narratives. While traditional narratives in games follow a linear path, procedural generation enables stories to evolve based on player choices, offering unique and personalized experiences. This research aims to explore the potential of procedural narrative generation in enhancing player engagement and learning outcomes in educational games. The study employs a mixed-methods approach, combining quantitative analysis of player engagement, knowledge retention, and problem-solving abilities with qualitative insights from participant interviews. A total of 240 participants were divided into three groups: those who interacted with games featuring fully procedural narratives, semi-procedural narratives, and traditional static narratives. The results show that players in the fully procedural narrative group demonstrated higher levels of engagement and cognitive performance, particularly in knowledge retention and problem-solving. These findings indicate that procedural narratives can significantly enhance player immersion and educational outcomes, providing a more interactive and personalized gaming experience. The study concludes that the integration of procedural generation in narrative design offers a promising avenue for improving educational game design, fostering deeper engagement and more effective learning.
MULTISCALE MODELING OF FLUID-STRUCTURE INTERACTION IN WIND TURBINE BLADES TO IMPROVE ENERGY CONVERSION EFFICIENCY IN RENEWABLE SYSTEMS Kaito Tanaka; Sulaiman Sulaiman; Lars Jensen
Research of Scientia Naturalis Vol. 3 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i3.4211

Abstract

The increasing demand for renewable electricity drives the need to improve wind turbine efficiency under complex aerodynamic and structural conditions. Numerical approaches often separate airflow analysis and structural response, thus reducing the accuracy of predicting aeroelastic behavior. This study aims to analyze the effectiveness of multiscale fluid-structure interaction (FSI) modeling in improving wind turbine blade performance through integrated aerodynamic, structural, and material analysis. Using a mixed-method sequential explanatory design, the study tested 2,800 simulation scenarios on 48 blade configurations under varying wind speeds, turbulence intensities, and composite material properties. Quantitative analysis included multivariate statistics and hierarchical regression, while qualitative thematic analysis was drawn from expert interviews and engineering workshops. Results show that a fully coupled multiscale FSI model consistently outperforms conventional approaches in improving aerodynamic efficiency, computational convergence, structural stability, vibration damping, and fatigue life prediction. Composite material optimization enhanced structural robustness under dynamic conditions. This framework provides practical guidance for designers and engineers to optimize renewable energy conversion through advanced multiphysics simulations.
Co-Authors Ismail Ismail Kaito Tanaka Lim Haeun Maria Nielsen Pieter Hendriks Sulaiman Sulaiman