Informatyka
William Pretty
One of the best kept secrets of the security industry is just how simple the monitoring hardware actually is - BeagleBone has all the computing power you need to build yourself an extremely sophisticated access control, alarm panel, and home automation and network intrusion-detection system. Security companies make a fortune each year by charging exorbitant fees to their customers. You will learn how easy it is to make an alarm system with Beaglebone.A company-maintained-and-monitored alarm system has its place - your dear old mum is probably not going to be creating her own system any time soon. But if you are reading this book, you are probably a builder or a hobbyist with all the skills required to do it yourself. With Building a Home Security System with BeagleBone, you will learn everything you need to know to develop your own state-of-the-art security system, all for less than a year's worth of monitoring charges from your local alarm company!You will start by building and testing your hardware and open source software on an experimenter's prototype board before progressing to more complex systems. You will then learn how to test your new creations in a modular fashion and begin to utilize BeagleBone. Once your system is built and tested, you will install some of the professional-grade sensors used in modern alarm systems and learn how to use them. You will also discover how to extend your alarm system in a variety of different ways. The only limit will be your imagination.
Matthew Poole
The Raspberry Pi is a powerful low-cost credit-card-sized computer, which lends itself perfectly as the controller for a sophisticated home security system. Using the on-board interfaces available, the Raspberry Pi can be expanded to allow the connection of a virtually infinite number of security sensors and devices. The Raspberry Pi has the processing power and interfaces available to build a sophisticated home security system but at a fraction of the cost of commercially available systems.Building a Home Security System with Raspberry Pi starts off by showing you the Raspberry Pi and how to set up the Linux-based operating system. It then guides you through connecting switch sensors and LEDs to the native GPIO connector safely, and how to access them using simple Bash scripts. As you dive further in, you’ll learn how to build an input/output expansion board using the I2C interface and power supply, allowing the connection of the large number of sensors needed for a typical home security setup. In the later chapters of the book, we'll look at more sophisticated topics such as adding cameras, remotely accessing the system using your mobile phone, receiving intrusion alerts and images by e-mail, and more.By the end of the book, you will be well-versed with the use of Raspberry Pi to power a home-based security system that sends message alerts whenever it is triggered and will be able to build a truly sophisticated and modular home security system. You will also gain a good understanding of Raspberry Pi's ecosystem and be able to write the functions required for a security system.
Ashish Kothekar
This comprehensive guide to QRadar will help you build an efficient security operations center (SOC) for threat hunting and need-to-know software updates, as well as understand compliance and reporting and how IBM QRadar stores network data in real time.The book begins with a quick introduction to QRadar components and architecture, teaching you the different ways of deploying QRadar. You’ll grasp the importance of being aware of the major and minor upgrades in software and learn how to scale, upgrade, and maintain QRadar. Once you gain a detailed understanding of QRadar and how its environment is built, the chapters will take you through the features and how they can be tailored to meet specifi c business requirements. You’ll also explore events, flows, and searches with the help of examples. As you advance, you’ll familiarize yourself with predefined QRadar applications and extensions that successfully mine data and find out how to integrate AI in threat management with confidence. Toward the end of this book, you’ll create different types of apps in QRadar, troubleshoot and maintain them, and recognize the current security challenges and address them through QRadar XDR.By the end of this book, you’ll be able to apply IBM QRadar SOC’s prescriptive practices and leverage its capabilities to build a very efficient SOC in your enterprise.
Anjanava Biswas, Wrick Talukdar, Matthew R. Scott,...
Gain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks.Starting with the foundations of GenAI and agentic architectures, you’ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents.Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention.
Henry Habib
Everyone’s talking about AI agents, but how do you build one that works in the real world? Not a toy demo, but an agent that solves real problems, saves time, and integrates into workflows. With vague frameworks, fragmented tooling, and endless hype, most developers are left without a clear path. The hardest part isn’t technical; it is knowing where to start.This book gives you that starting point. It’s a complete guide to building intelligent AI agents and agentic systems using the official OpenAI Agents SDK. It begins by grounding you in the core concepts, design principles, and architecture of AI agents, how they differ from other traditional systems, their advantages, and why that matters.Through practical step-by-step projects, you’ll master every feature of the SDK—tools, memory, RAG, multi-agent orchestration, tracing, handoffs, and more—while contributing to an end-to-end agent system that grows in complexity. Projects include a custom support agent, invoice and inventory assistant, health advisor, sales trainer, and data analyst, giving you production-ready skills.By the end, you’ll know how to design, build, and deploy agentic systems that interact with APIs, query databases, hand off to external systems, and drive meaningful outcomes. You won’t just understand AI agents; you’ll be ready to ship them.
Salvatore Raieli, Gabriele Iuculano
This book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving.Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples and real-world case studies reinforce each concept and show how the techniques fit together.By the end of this book, you’ll be able to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.*Email sign-up and proof of purchase required
Salvatore Raieli, Gabriele Iuculano
This book addresses the challenge of building AI that not only generates text but also grounds its responses in real data and takes action. Authored by AI specialists with expertise in drug discovery and systems optimization, this guide empowers you to leverage retrieval-augmented generation (RAG), knowledge graphs, and agent-based architectures to engineer truly intelligent behavior. By combining large language models (LLMs) with up-to-date information retrieval and structured knowledge, you'll create AI agents capable of deeper reasoning and more reliable problem-solving.Inside, you'll find a practical roadmap from concept to implementation. You’ll discover how to connect language models with external data via RAG pipelines for increasing factual accuracy and incorporate knowledge graphs for context-rich reasoning. The chapters will help you build and orchestrate autonomous agents that combine planning, tool use, and knowledge retrieval to achieve complex goals. Concrete Python examples and real-world case studies reinforce each concept and show how the techniques fit together.By the end of this book, you’ll be able to build intelligent AI agents that reason, retrieve, and interact dynamically, empowering you to deploy powerful AI solutions across industries.*Email sign-up and proof of purchase required