Programming End-to-End Wireless IoT Systems & Applications
Master the full IoT stack — from embedded sensors and wireless protocols to cloud dashboards. Build real systems using MQTT, mioty, OPC-UA, and industry-grade toolchains.
120+ lab hours · ~12 weeks self-paced
Beginner to Advanced
Engineers, developers and graduates moving into IoT systems work.
Program Snapshot
6
MODULES
18+
HANDS-ON LABS
4
CAPSTONE SPRINTS
120+
LAB HOURS
IICT PEDAGOGY
Curriculum — From Basics to Project Ready
Self-paced modules designed in two structured phases. Each module bundles guided theory, hands-on labs and measurable learning outcomes.
01
Phase 01 — Basics
Learn the Technology
Introduction to Lab Tools
Get started with the IICT Virtual Lab — Linux, Git and Python essentials.
LEARNING OUTCOMES
Use the digital lab environment and toolchain
Apply Linux command-line and version control
Automate IoT workflows with Python
IoT Protocols & Interoperability
Practical understanding of MQTT, CoAP and REST and how data flows from devices to cloud.
LEARNING OUTCOMES
Compare IoT application-layer protocols
Analyze protocol performance and overhead
Design interoperable end-to-end IoT applications
02
Phase 02 — Experiments
Practice and Build
Programming Embedded Systems for Wireless IoT
Configure microcontrollers for IoT — register-level and HAL-based programming.
LEARNING OUTCOMES
Evaluate and select MCUs for IoT
Configure peripherals via register-level and HAL
Use modern IDEs for coding and debugging
Sensor Integration
Interface sensors with MCUs over UART, I²C and SPI; bridge to industrial OPC-UA.
LEARNING OUTCOMES
Understand sensor interfaces and signal characteristics
Program MCUs for I²C and SPI
Bridge embedded devices to industrial OPC-UA
Transmitting Data Wirelessly (mioty LPWAN)
Hands-on low-power wireless using mioty — KPI analysis, timing, and stack configuration.
LEARNING OUTCOMES
Understand LPWAN technologies and mioty
Compute network KPIs and timing budgets
Configure mioty stacks via serial
Performance Visualization & Persistence
Persist, monitor and visualize IoT data with InfluxDB, Grafana and Loki.
LEARNING OUTCOMES
Implement time-series data persistence
Build real-time Grafana dashboards
Set up complete logging and monitoring
HARDWARE & TOOLCHAIN
Real Equipment. Industry-Grade Tools.
Every lab runs on the same hardware and software stack used in industrial deployments — accessed remotely through the IICT Virtual Lab or shipped as a physical kit for institutional partners.
ESP32-S3 / STM32 MCU
mioty LPWAN Gateway
Industrial Sensor Array (I²C/SPI)
Mosquitto MQTT Broker
Grafana + InfluxDB Stack
What You'll Be Able to Do
Use the digital lab environment and toolchain
Compare IoT application-layer protocols
Evaluate and select MCUs for IoT
Understand sensor interfaces and signal characteristics
Self-paced
Certificate of Completion
Online Hosted
PHASE 03 — PROJECT READY
Capstone — IoT-Based Smart City
Develop a complete IoT prototype for real-time environmental monitoring — through structured agile sprints mirroring real-world development cycles.
S1
Network & System Setup
Establish IoT foundation — broker, simulated sensors, connectivity.
S2
Data Integration & Persistence
Build the backend with time-series storage and consistency.
S3
Visualization & Dashboard Creation
Turn sensor data into real-time, actionable dashboards.
S4
Scalability & Performance Evaluation
Stress test with many sensors; optimize bottlenecks.
Project Outcomes
Design and implement a functional IoT data pipeline
Apply performance analysis and visualization in a real scenario
Evaluate scalability and reliability through simulated load
Ready to start the IoT learning journey?
Enroll directly online, or request a bundled institutional / corporate license that covers cohorts, lab access and certification.