Kickstart IoT Systems Engineering - Build Intelligent IoT Systems from Embedded Devices to Cloud and Edge AI (English Edition) #964330

Use Sensors to Intelligence to Build Secure, Scalable IoT Systems

Book Description
Connected devices are reshaping every industry — from smart manufacturing and precision agriculture to healthcare monitoring and autonomous systems. Kickstart IoT Systems Engineering provides a comprehensive, hands-on path from core IoT concepts to production-grade, AI-enabled deployments, bridging the gap between academic foundations and real industry practice.

You begin with IoT architecture, sensors, microcontrollers, and communication protocols — including MQTT, REST APIs, LoRa, and BLE — then progressively build toward cloud-connected systems using Firebase, AWS IoT Core, and enterprise integration patterns.

What you will learn
● Program Arduino, NodeMCU, and ESP32 for real-world IoT applications.
● Connect devices to cloud platforms using MQTT, REST APIs, and Firebase.
● Implement encryption, authentication, and hardening for secure IoT systems.

Who is This Book For?
This book is tailored for students pursuing courses like BE, B.Tech, BCA, MCA, IoT developers, embedded engineers, and AI/ML practitioners who want to build practical, cloud-connected IoT systems. Beginners will also find a strong foundation in core concepts, and professionals will gain hands-on exposure to Edge AI, security, and enterprise-scale deployment.

Table of Contents
1. Introduction to IoT
2. IoT Architecture and Ecosystem
3. Sensor Technologies and Actuators
4. Networking and Communication Protocols (MQTT, HTTP, LoRa, BLE)
5. Getting Started with Arduino, NodeMCU, and ESP32
6. Interfacing Sensors and Modules
7. Real-Time Control with GPIO, PWM, and Interrupts
8. Serial Communication and Data Transmission between Devices
9. Firebase, Blynk, and Google Sheets
10. MQTT, REST APIs, and Webhooks for Device Communication
11. Encryption, Device Hardening, and Authentication
12. Data Logging, Alert Systems, and Notification Integration
13. Cloud-Backed End-to-End Projects and Enterprise IoT Integration
14. Introduction to ML with Sensor Data
15. Deployment, Testing, and Scaling
16. The Future of IoT
17. Applied IoT with Edge AI and Vision
       Index