Context-Aware, Real-Time Fleet Management: Next-Generation Platforms for Emergency Services
暫譯: 上下文感知即時車隊管理：應急服務的下一代平台
Gariuolo, Salvatore, Longo, Stefano
商品描述
In an emergency, every second counts, and even a small mistake can cost lives. Yet emergency fleets - ambulances, fire trucks, and police vehicles - still rely on platforms that are unable to integrate the diverse data needed to support accurate, reliable, and timely decisions. Selecting which vehicle to dispatch to an emergency is one such decision - a task that is complex, stressful, and prone to error with conventional dispatch systems.
This book examines how connected vehicle platforms - the technological backbone of modern fleet management - can be designed to meet the operational requirements of emergency services. By integrating vehicle and context data in real time - covering everything from vehicle status to staff availability, crew skills, shift schedules, traffic, and weather - these platforms enable faster and more consistent decision-making. Using the UK National Health Service ambulance fleet as a case study, the book presents a prototype system that automates ambulance dispatch, demonstrating how a thoughtfully designed platform can deliver performance and capabilities far beyond conventional fleet management systems.
Features:
- Presents a comprehensive overview of fleet management with core principles and provides essential knowledge for understanding and improving fleet management.
- Highlights the value of custom-built data platforms, which enable more efficient and effective fleet management than conventional, off-the-shelf systems.
- Explains how to design fleet management systems from system requirements, offering a unique engineering approach not found in other books.
- Includes an end-to-end development process and covers the full process from design through testing, providing a practical, hands-on guide for creating effective fleet management solutions.
- Demonstrates how real-time integration of vehicle data and context data transforms the management of the UK NHS ambulance fleet.
For fleet managers, emergency service professionals, researchers, and policymakers, this book provides a roadmap to improve fleet performance, reduce operational risk, and ultimately save lives - showing why every fleet needs a data platform tailored to its unique requirements.
商品描述(中文翻譯)
在緊急情況下，每一秒都至關重要，即使是小錯誤也可能造成生命損失。然而，緊急車隊——救護車、消防車和警車——仍然依賴於無法整合所需多樣數據的平台，以支持準確、可靠和及時的決策。選擇派遣哪輛車輛到緊急現場就是這樣一個決策——這是一項複雜、壓力大且容易出錯的任務，尤其是在傳統的調度系統中。
本書探討了如何設計連接車輛平台——現代車隊管理的技術支柱，以滿足緊急服務的操作需求。通過實時整合車輛和上下文數據——涵蓋從車輛狀態到人員可用性、船員技能、班次安排、交通和天氣等各方面——這些平台能夠實現更快且更一致的決策。以英國國民健康服務（NHS）救護車車隊為案例，本書展示了一個自動化救護車調度的原型系統，演示了精心設計的平台如何提供遠超傳統車隊管理系統的性能和能力。
特色：
- 提供車隊管理的全面概述，介紹核心原則，並提供理解和改善車隊管理所需的基本知識。
- 突出定制數據平台的價值，這些平台能夠比傳統的現成系統更有效率和更有效地進行車隊管理。
- 解釋如何從系統需求設計車隊管理系統，提供其他書籍中未見的獨特工程方法。
- 包含端到端的開發過程，涵蓋從設計到測試的完整過程，提供實用的、動手操作的指南，以創建有效的車隊管理解決方案。
- 演示如何實時整合車輛數據和上下文數據，改變英國NHS救護車車隊的管理方式。
對於車隊經理、緊急服務專業人員、研究人員和政策制定者，本書提供了一條改善車隊性能、降低操作風險並最終拯救生命的路線圖——顯示為什麼每個車隊都需要一個量身定制的數據平台，以滿足其獨特需求。
作者簡介
Salvatore Gariuolo is a leading expert in the future of mobility and the broader impact of emerging technologies. His work bridges academic insight with practical application, helping both industry and the public navigate a rapidly evolving technology landscape. He regularly presents his work at international conferences and shares insights through podcasts and interviews.
He currently serves as senior threat researcher at Trend Micro, where he investigates risks across a wide range of technologies, from connected vehicles to artificial intelligence (AI). His research examines how these complex technologies may evolve and create new threats, informing strategies to mitigate risks before they materialise.
Gariuolo holds a PhD from Cranfield University and a master's degree in computer science engineering from the University of Naples Federico II. With nearly a decade of research experience, he previously served as research fellow at Cranfield University, leading projects on connected and autonomous vehicle systems. He is also the founder of VEICOLNET, a company advising the automotive sector on strategy, innovation, and security, helping organisations navigate emerging technologies, regulatory compliance, and risk.
Stefano Longo is an internationally recognised leader in AI-driven mobility, specialising in intelligent decision-making algorithms that power everything from advanced battery systems to autonomous driving. With a career spanning academia, industry, and deep-tech innovation, he has delivered more than ten major R&D programmes
and contributed to shaping the next generation of automated and electrified transport.
He currently serves as head of Intellectual Property at Embotech AG in Switzerland, associate professor in Automated Vehicles at Cranfield University in the UK, and a strategic advisor for startups and incubation centres. His work blends cutting-edge research with real-world deployment, supported by a strong record of collaboration with OEMs, Tier-1s, and technology start-ups. Stefano is an inventor on a growing portfolio of patents and author of multiple books and over 90 publications that have influenced industrial practice and academic research in control, optimisation, and autonomous systems.
He has held senior academic and industrial roles, directed specialist postgraduate programmes, supervised extensive doctoral research, and contributed to national and international research councils. He is a senior member of IEEE, a chartered engineer, and a fellow of the Higher Education Academy and is regularly invited to speak at global conferences on autonomy, electrification, and intelligent mobility.
作者簡介(中文翻譯)
Salvatore Gariuolo 是未來移動性及新興技術廣泛影響的領先專家。他的工作將學術見解與實際應用相結合，幫助業界和公眾在快速變化的技術環境中導航。他定期在國際會議上發表研究成果，並通過播客和訪談分享見解。
他目前擔任趨勢科技的高級威脅研究員，研究範圍涵蓋從連接車輛到人工智慧 (AI) 的各種技術風險。他的研究探討這些複雜技術如何演變並創造新威脅，並為在威脅出現之前制定風險緩解策略提供資訊。
Gariuolo 擁有克蘭菲爾德大學的博士學位，以及那不勒斯費德里科二世大學的計算機科學工程碩士學位。擁有近十年的研究經驗，他曾擔任克蘭菲爾德大學的研究員，領導有關連接和自動駕駛車輛系統的項目。他也是 VEICOLNET 的創始人，該公司為汽車行業提供有關策略、創新和安全的建議，幫助組織應對新興技術、法規遵從和風險。
Stefano Longo 是國際公認的 AI 驅動移動性領導者，專注於智能決策算法，這些算法驅動從先進電池系統到自動駕駛的各種應用。他的職業生涯涵蓋學術界、工業界和深科技創新，已交付超過十個主要的研發計劃，並為塑造下一代自動化和電氣化交通做出了貢獻。
他目前擔任瑞士 Embotech AG 的知識產權主管、英國克蘭菲爾德大學自動駕駛車輛的副教授，以及初創企業和孵化中心的戰略顧問。他的工作將前沿研究與實際部署相結合，並擁有與原始設備製造商 (OEM)、一級供應商 (Tier-1) 和技術初創企業的強大合作記錄。Stefano 是一位擁有不斷增長的專利組合的發明人，也是多本書籍的作者，並發表了超過 90 篇影響控制、優化和自動系統的工業實踐和學術研究的出版物。
他曾擔任高級學術和工業職位，指導專業研究生課程，監督廣泛的博士研究，並為國家和國際研究委員會做出貢獻。他是 IEEE 的高級會員、特許工程師，以及高等教育學院的院士，並定期受邀在全球會議上發表有關自動化、電氣化和智能移動性的演講。
