Assessment of Smart Cities Challenges and Future Consequences
スマートシティの課題と将来の影響の評価 (AI 翻訳)
K. A. Hossain
🤖 gxceed AI 要約
日本語
本論文は、スマートシティにおけるAI、IoT、ビッグデータなどの先端技術の導入がもたらす機会と課題を広範にレビューする。特に、データプライバシー、セキュリティ、法的・倫理的問題に焦点を当て、持続可能性と効率性の向上とのバランスを論じる。しかし、具体的な実証データや定量的な分析は乏しく、概念整理の段階にとどまる。
English
This paper broadly reviews the opportunities and challenges of deploying smart technologies (AI, IoT, big data) in smart cities, focusing on data privacy, security, legal, and ethical issues while linking to sustainability and urban efficiency. However, it lacks empirical evidence or quantitative analysis, remaining at a conceptual overview level with limited direct relevance to GX metrics or climate disclosure.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本論文は日本のGX文脈に特化した内容ではないが、スマートシティ政策（スーパーシティ構想など）の基礎的理解として参考になる可能性がある。ただし、SSBJや有報との直接的な接点はない。
In the global GX context
This paper provides a broad framework for understanding smart city sustainability challenges but does not engage with specific global climate disclosure frameworks (TCFD, ISSB) or carbon accounting methodologies.
👥 読者別の含意
🔬研究者:Broad conceptual review useful as introductory background but lacks novel findings.
🏢実務担当者:Provides a checklist of smart city challenges but no actionable GX guidance.
🏛政策担当者:Highlights need for balancing tech innovation with privacy/ethics regulations.
📄 Abstract（原文）
We may define high-tech era embodies the current period and may be explained by the rapid advancement and cutting-edge technologies such as mobile phone technology, digital/quantum computers, camera surveillance, robotics, Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), Big Data, Digital Twin, and many more into daily life, business, service, agriculture, finance, government and industry. It has revolutionized communication, transformed architectural design with exposed, functional structures, and shifted global economic power towards tech-driven innovation, creating both unprecedented connectivity and intense competition. Today the use of those smart technology presents many distinct prospects along with significant challenges. Those prospects include transforming industries, improving the agricultural and service sectors, enhancing daily life, and improving sustainability. These technologies, which include smart homes, cities, and healthcare, leverage connectivity to operate autonomously and improve efficiency. On the other hand, those challenges include technological, economic, legal, and ethical facets, primarily centered on data privacy, security, and accountability. The influence of current digital technologies on human activities, including politics, education, economy, service, business, and enterprises worldwide, is so disturbing. Those have changed radically of human culture, law, religion, work, etc., and that have greatly up-sated the normal order of things in the society. The deployment of these smart technologies in smart cities and corporate businesses has faced significant technical, financial, legal, and ethical ramifications. Smart cities in the in this century employ smart technologies and data analytics to promote sustainability, efficiency, and quality of life, addressing rising urbanization and climate issues to support peaceful and smart living. Important possibilities include intelligent traffic, smart grids, and citizen-centric services, while high implementation costs, critical legal aspect and cybersecurity threats remain substantial issues. This study will assess the challenges including ethical aspects, of the widespread use of smart technology to develop smart cities. Beyond many prospects, there are major challenges, including security, legal and ethical issues, that require balancing technological innovation with the protection of individual rights and security of society.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.14738/tmlai.1402.20174first seen 2026-07-01 05:54:41
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。