IoT Developer
Dive into the world of IoT coding and learn to build intelligent systems through hands-on projects! Gain essential skills in IoT architectures, communication protocols, and AI integration, preparing you for a future in smart technology development.
Course Program
What you'll learn
- Design and implement advanced IoT systems with secure, scalable, and energy-efficient architectures.
- Use AI and machine learning to enhance IoT data processing and automation.
Course Program
Requirements
- Basic knowledge of programming and electronics.
- Familiarity with cloud platforms and networking protocols.
- Beginner Class: For students new to programming or with no prior experience.
- Advance Class: For students with programming basics or who have completed the beginner level.
Course content
Beginner class
Advance class
Beginner class
- Introduction to IoT: Concepts and Applications
Overview of IoT, its components, architecture, and real-world applications. - Setting Up Your IoT Development Environment
Installing tools like Arduino IDE, setting up Raspberry Pi, and basic hardware requirements. - Basic Electronics for IoT
Understanding electronic components: resistors, capacitors, transistors, and basic circuits. - Introduction to Microcontrollers and Microprocessors
Overview of microcontrollers (Arduino) and microprocessors (Raspberry Pi) in IoT systems. - Programming Basics for IoT with Arduino
Writing basic programs for Arduino using C/C++, controlling LEDs, and reading sensor inputs. - Sensors and Actuators in IoT
Understanding sensors (temperature, humidity, motion) and actuators (motors, relays), their working principles, and interfacing with Arduino. - IoT Communication Protocols
Introduction to protocols like MQTT, HTTP, and CoAP for device communication. - Wireless Communication: Wi-Fi and Bluetooth
Working with Wi-Fi and Bluetooth modules for wireless IoT communication. - Introduction to Raspberry Pi and Python Programming
Setting up Raspberry Pi and using Python for basic IoT tasks. - Interfacing Sensors with Raspberry Pi
Reading sensor data and controlling outputs with Raspberry Pi using Python. - Cloud Platforms for IoT: Overview
Introduction to cloud platforms like AWS IoT, Google Cloud IoT, and ThingSpeak for IoT data storage and analysis. - Data Logging and Visualization
Collecting data from sensors and visualizing it using tools like Matplotlib or cloud dashboards. - IoT Security Basics
Overview of security challenges in IoT systems and basic protection mechanisms like encryption and secure communication. - Building a Simple IoT Project with Arduino
Hands-on project: Building a simple IoT system to collect and display sensor data over Wi-Fi. - Introduction to Edge Computing in IoT
Basics of edge computing and how it can enhance IoT systems by reducing latency and dependency on cloud services. - Deploying IoT Systems: Connecting Devices to the Cloud
Final project: Connecting an IoT device to the cloud, sending data, and visualizing it on a dashboard.
Advance class
- Advanced IoT Architecture: Edge, Fog, and Cloud Computing
Understanding edge, fog, and cloud computing and their roles in advanced IoT systems. - IoT Operating Systems: Introduction to Contiki and RIOT
Exploring operating systems built for IoT devices like Contiki and RIOT, their features, and when to use them. - Advanced IoT Communication Protocols: LoRaWAN and Zigbee
Implementing long-range communication protocols such as LoRaWAN and Zigbee for large-scale IoT networks. - Building Secure IoT Systems: Advanced IoT Security
Implementing advanced security features like authentication, encryption, and secure firmware updates. - Low Power IoT: Energy Management in IoT Devices
Techniques for reducing power consumption in IoT devices using sleep modes, low-power components, and energy harvesting. - IoT Networking: Mesh Networks
Setting up mesh networks using protocols like Zigbee or BLE Mesh for decentralized device communication. - IoT Data Processing and Storage
Handling large datasets from IoT devices, exploring storage solutions like InfluxDB and Cassandra for time-series data. - Machine Learning for IoT
Introduction to applying machine learning techniques on IoT data for predictive analytics and intelligent automation. - IoT with AI: Building Smart Systems
Combining AI and IoT to create smart systems that can learn and adapt based on data (e.g., smart homes, predictive maintenance). - Advanced Cloud Integration: IoT Analytics and Dashboards
Deep dive into cloud platforms for IoT, using AWS IoT, Azure IoT, and Google Cloud for real-time data analysis and building dashboards. - IoT for Industrial Applications (IIoT)
Implementing IoT in industrial settings, exploring use cases like predictive maintenance, smart factories, and robotics. - Edge AI in IoT
Building AI models that run on edge devices to process data locally and reduce reliance on cloud processing. - Blockchain in IoT: Securing IoT Networks
Understanding the role of blockchain in enhancing the security and transparency of IoT networks. - Interoperability in IoT: APIs and Web Services
Creating interoperable IoT systems using APIs and web services, integrating devices with third-party services. - IoT Project: Building a Full-Scale Smart Home System
Hands-on project: Developing a smart home system with sensors, actuators, cloud storage, and a mobile interface. - Scaling IoT Systems for Enterprise Applications
Strategies for scaling IoT networks, managing device fleets, and ensuring reliability in enterprise-level IoT application.
Course Program
Capstone Project
Smart Plant Monitor: Develop a system that uses sensors to monitor soil moisture and light levels, employing machine learning to predict when plants need watering or additional light.
AI-Powered Home Security System: Create a basic home security system using cameras and motion sensors that utilize AI for object detection to differentiate between pets, humans, and potential intruders.
Energy-Efficient Smart Thermostat: Design a smart thermostat that learns user preferences and optimizes heating and cooling schedules using machine learning to save energy.
Intelligent Waste Management System: Build a system that uses IoT sensors to monitor waste bin levels and employs AI to optimize collection routes based on real-time data.
Predictive Maintenance for IoT Devices: Develop a simple predictive maintenance system that monitors the performance of a small appliance (like a fan or pump) and uses machine learning to predict when maintenance is needed based on usage patterns.
Course Program
Outcomes
- Build IoT systems with AI, secure networks, and advanced communication protocols.
- Develop projects like smart homes and industrial IoT applications.