Special Issues
Table of Content

Software, Algorithms and Automation for Industrial, Societal and Technological Sustainable Development

Submission Deadline: 31 May 2026 View: 1082 Submit to Special Issue

Guest Editors

Assoc. Prof. Dr. Ari Happonen

Email: ari.happonen@lut.fi

Affiliation: Software Engineering, LUT University, Lappeenranta, 53850, Finland

Homepage:

Research Interests: software, algorithms, electrification, automation, robotics and LLMs for industrial, societal and technologies sustainable development

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Summary

Modern-day robotization, LLM, Createch and related technologies and algorithms offer change for an improved and more sustainable society, where software solutions thrive and make life better for us all.

We appreciate studies that take into account both the academic and practical insights. The special looks for front-line Robtization, Automation, Algorithm, related Createch, Software and technology solutions, in modern digitalized societies for better, sustainable and more economically feasible pathways to reduce unnecessary suffering, to find new development directions and to push forward societal and technologies sustainable development.

We particularly welcome articles with the following themes:
• Software and automation development for industrial and societal sustainable development benefits.
• Automation, LLM and robotization algorithms and solutions development, case studies and novel solutions on ongoing research streams.
• Interdisciplinary work connecting multiple sectors of research and/or industry applications together.
• Applied case studies, showcasing how Software, Algorithms, Createch or related tools/solutions are used in practice.
• Investigations into (end)user motivation and the design solutions for engaging with digital environments and solutions in connection with automation or robotics.
• Innovations in data visualization, storytelling, simulation, and interaction design that enhance social and sustainable outcomes.


Keywords

software, algorithm, automation, robotics, large language model, societal sustainability, technologies development.

Published Papers


  • Open Access

    ARTICLE

    Intelligent Ridge Path Planning for Agriculture Robot Using Modified Q-Learning Algorithm

    A. Sivasangari, V. J. K. Kishor Sonti, J. Cruz Antony, E. Murali, D. Deepa, A. Happonen
    CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074429
    (This article belongs to the Special Issue: Software, Algorithms and Automation for Industrial, Societal and Technological Sustainable Development)
    Abstract In the past two decades, Precision Agriculture has received research attention since the development of robotics. Agricultural robotic equipment and drones, which can be operated by farmers, are appearing more frequently and being used to make the process of farming easier and more productive. This paper attempts to develop a modified Q-learning algorithm. A reinforcement learning algorithm called Q-learning has Q-values that are updated in order to find the best routes for the robotic devices to follow while avoiding any obstacles. Different types of terrain and other factors that influence the development of good routes… More >

  • Open Access

    ARTICLE

    Computational Assessment of Information System Reliability Using Hybrid MCDM Models

    Nurbek Sissenov, Gulden Ulyukova, Dina Satybaldina, Nikolaj Goranin
    CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075504
    (This article belongs to the Special Issue: Software, Algorithms and Automation for Industrial, Societal and Technological Sustainable Development)
    Abstract The reliability of information systems (IS) is a key factor in the sustainable operation of modern digital services. However, existing assessment methods remain fragmented and are often limited to individual indicators or expert judgments. This paper proposes a hybrid methodology for a comprehensive assessment of IS reliability based on the integration of the international standard ISO/IEC 25010:2023, multicriteria analysis methods (ARAS, CoCoSo, and TOPSIS), and the XGBoost machine learning algorithm for missing data imputation. The structure of the ISO/IEC 25010 standard is used to formalize reliability criteria and subcriteria, while the AHP method allows for… More >

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