Sustainable AI Techniques for Real-Time Risk Monitoring
暫譯: 可持續的 AI 技術於即時風險監控
Zamani, Abu Sarwar, Hashim, Aisha Hassan Abdalla, Imran, Hazra
- 出版商: Springer
- 出版日期: 2026-07-15
- 售價: $8,950
- 貴賓價: 9.5 折 $8,502
- 語言: 英文
- 頁數: 341
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3032286719
- ISBN-13: 9783032286710
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相關分類:
DeepLearning、Maker、區塊鏈 Blockchain
海外代購書籍(需單獨結帳)
商品描述
Sustainable AI Techniques for Real-Time Risk Monitoring offers a comprehensive examination of energy-efficient artificial intelligence approaches for hazard detection in smart environments. The book begins by identifying the limitations of traditional AI models --particularly their high computational and energy demands -- and introduces the concept of Green AI as a sustainable alternative. It systematically presents key methodologies, including lightweight deep learning architectures, model optimization techniques, and the integration of edge and fog computing. In addition, it explores advanced paradigms such as federated learning and bio-inspired computing to enable scalable and resource-efficient real-time monitoring systems.
The book further elaborates on practical applications across diverse domains, including fire hazard detection, industrial safety, environmental monitoring, and smart healthcare systems. It also examines how secure and decentralized technologies--such as blockchain--enhance the reliability of IoT-based hazard detection frameworks. The concluding section outlines future research directions, emphasizing renewable-powered IoT infrastructures and the ethical, legal, and societal implications of Green AI.
Overall, this book serves as a valuable resource for academics, researchers, and practitioners striving to develop sustainable, reliable, and energy-conscious intelligent safety systems.
商品描述(中文翻譯)
《可持續人工智慧技術於即時風險監控》提供了對於智慧環境中危險檢測的能源效率人工智慧方法的全面探討。本書首先指出傳統人工智慧模型的限制,特別是其高計算和能源需求,並介紹了綠色人工智慧(Green AI)作為可持續的替代方案。它系統性地呈現了關鍵方法論,包括輕量級深度學習架構、模型優化技術,以及邊緣計算和霧計算的整合。此外,本書還探討了聯邦學習(federated learning)和生物啟發計算等先進範式,以實現可擴展且資源高效的即時監控系統。
本書進一步闡述了在多個領域的實際應用,包括火災危險檢測、工業安全、環境監測和智慧醫療系統。它還檢視了安全和去中心化技術(如區塊鏈)如何增強基於物聯網(IoT)的危險檢測框架的可靠性。結尾部分概述了未來的研究方向,強調可再生能源驅動的物聯網基礎設施以及綠色人工智慧的倫理、法律和社會影響。
總體而言,本書是學術界、研究人員和實務工作者在開發可持續、可靠且注重能源的智能安全系統方面的重要資源。
作者簡介
Dr. Abu Sarwar Zamani is an Assistant Professor at Prince Sattam bin Abdulaziz University, Al-Kharj, Kingdom of Saudi Arabia, and an Honorary Research Fellow at INTI International University, Malaysia. Previously, he worked as a Senior Lecturer at Shaqra University and King Saud University, Kingdom of Saudi Arabia. He received his Postdoctoral Fellowship from the Kulliyyah of Engineering, International Islamic University Malaysia, Gombak, Malaysia; his Ph.D. in Computer Science from the Pacific Academy of Higher Education and Research University, India; and his M.Sc. in Computer Science from Hamdard University, New Delhi, India, in 2007.
His research interests include Artificial Intelligence (AI), Machine Learning (ML), the Internet of Things (IoT), Health Informatics, and Big Data. With more than 15 years of experience in teaching, research, and industry, Dr. Zamani has published over 100 research papers. He also serves as an Academic Editor, Associate Editor, and Guest Editor for leading journals published by Springer, Elsevier, and MDPI.
Professor (Dr.) Aisha Hassan Abdalla Hashim is a Full Professor in the Department of Electrical and Computer Engineering at the International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia. She received her Ph.D. in Computer Engineering (2007), M.Sc. in Computer Science (1996), and B.Sc. in Electronics Engineering (1990).
Professor Aisha has served as an external examiner, visiting professor, and adjunct professor at several universities. She has published more than 200 journal and conference papers and supervised or co-supervised over 40 Ph.D. and Masters students. She was appointed the IIUM Internationalization Ambassador to Sudan in October 2014 and has played a key role in initiating several memoranda of understanding (MoUs) and promoting Ph.D. student mobility between IIUM and Sudanese universities. In addition to her academic work, she has served as a member of the Board of Studies at the International Islamic School, Malaysia.
Dr. Hazra Imran is an Associate Teaching Professor in the Khoury College of Computer Sciences at Northeastern University, based in Vancouver, Canada. With more than 18 years of experience in academia, Dr. Imran teaches courses in database systems, capstone projects, web development, and the Align program. Beyond teaching, she engages in research collaborations and technological innovations in education, regularly presenting her work at international conferences.
Dr. Imran has served on numerous university and journal committees and maintains an active record of scholarly publications. She holds a Ph.D. in Computer Science and completed a Postdoctoral Fellowship at Athabasca University, Canada, where her research focused on advanced adaptivity and personalization in learning systems.
Dr. Padmaja Savaram is an Assistant Professor in the Department of Computer Science at the College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia. Previously, she served as an Associate Professor in the Department of Computer Science and Engineering at Keshav Memorial Institute of Technology (KMIT) beginning in 2017 and as Head of the Department from 2019 to 2023.
With over 22 years of teaching and research experience, her research expertise lies in Sentiment Analysis, which has resulted in patents, books, research articles, and a monograph on embedded systems. She serves on the editorial board of Data Science and Big Data Analytics and reviews manuscripts for several international journals. Her professional contributions include delivering invited lectures, conducting workshops, and presenting research at leading institutions such as defense laboratories and educational organizations.
作者簡介(中文翻譯)
阿布·薩瓦爾·扎馬尼博士是沙烏地阿拉伯阿爾哈吉的王子薩塔姆·賓·阿卜杜拉齊茲大學的助理教授,以及馬來西亞INTI國際大學的榮譽研究員。之前,他曾擔任沙克拉大學和沙烏地阿拉伯國王沙烏德大學的高級講師。他於2007年獲得馬來西亞國際伊斯蘭大學工程學院的博士後研究獎學金,並在印度太平洋高等教育與研究大學獲得計算機科學博士學位,在印度新德里的哈姆達爾大學獲得計算機科學碩士學位。
他的研究興趣包括人工智慧(AI)、機器學習(ML)、物聯網(IoT)、健康資訊學和大數據。扎馬尼博士在教學、研究和產業方面擁有超過15年的經驗,已發表超過100篇研究論文。他還擔任Springer、Elsevier和MDPI出版的領先期刊的學術編輯、助理編輯和客座編輯。
艾莎·哈桑·阿卜杜拉·哈希姆教授(博士)是馬來西亞國際伊斯蘭大學(IIUM)電機與計算機工程系的正教授。她於2007年獲得計算機工程博士學位(Ph.D.)、1996年獲得計算機科學碩士學位(M.Sc.)和1990年獲得電子工程學士學位(B.Sc.)。
艾莎教授曾擔任多所大學的外部考官、訪問教授和兼任教授。她已發表超過200篇期刊和會議論文,並指導或共同指導超過40名博士和碩士生。她於2014年10月被任命為IIUM前往蘇丹的國際化大使,並在促進IIUM與蘇丹大學之間的博士生流動和啟動多項諒解備忘錄(MoUs)方面發揮了關鍵作用。除了學術工作外,她還擔任馬來西亞國際伊斯蘭學校的學術委員會成員。
哈茲拉·伊姆蘭博士是加拿大溫哥華東北大學Khoury計算機科學學院的副教學教授。擁有超過18年的學術經驗,伊姆蘭博士教授數據庫系統、畢業專案、網頁開發和Align計畫的課程。除了教學外,她還參與教育領域的研究合作和技術創新,並定期在國際會議上展示她的研究成果。
伊姆蘭博士曾在多個大學和期刊委員會任職,並保持活躍的學術出版紀錄。她擁有計算機科學博士學位,並在加拿大阿薩巴斯卡大學完成博士後研究,研究重點是學習系統中的高級適應性和個性化。
帕德馬雅·薩瓦拉姆博士是沙烏地阿拉伯王子薩塔姆·賓·阿卜杜拉齊茲大學計算機工程與科學學院計算機科學系的助理教授。之前,她自2017年起擔任Keshav Memorial Institute of Technology(KMIT)計算機科學與工程系的副教授,並於2019年至2023年擔任系主任。
擁有超過22年的教學和研究經驗,她的研究專長在於情感分析,並已獲得專利、出版書籍、研究文章以及關於嵌入式系統的專著。她擔任《數據科學與大數據分析》的編輯委員會成員,並為多個國際期刊審稿。她的專業貢獻包括發表邀請講座、舉辦工作坊,以及在國防實驗室和教育機構等領先機構展示研究成果。