Context-Aware, Real-Time Fleet Management

Next-Generation Platforms for Emergency Services
1. Auflage 2026
ISBN: 978-1-041-17214-7
Verlag: Taylor & Francis

Buch, Englisch, 240 Seiten, Format (B × H): 156 mm x 234 mm

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.

- 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.

Zielgruppe

General

Autoren/Hrsg.

Gariuolo, Salvatore

Longo, Stefano

Fachgebiete

• Geisteswissenschaften Design Produktdesign, Industriedesign
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Feuerwehrtechnik

Inhaltsverzeichnis

1. Introduction 2. Overview of the State-of-the-Art 3. Case Study: Ambulance Fleet 4. Data Storage Infrastructure 5. Data Communication Infrastructure 6. Vehicle Interface 7. User Interfaces 8. Data Platform Testing 9. Conclusions

Über Autor(innen)

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 10 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 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 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, Chartered Engineer, and Fellow of the Higher Education Academy, regularly invited to speak at global conferences on autonomy, electrification, and intelligent mobility.