Internet of Things (IoT) Fundamentals Training Course

Module 1: Introduction to IoT and Core Concepts

• Definition and history of the Internet of Things
• Key components of an IoT ecosystem (Devices, Connectivity, Cloud, Applications)
• The market size and growth drivers for IoT
• Use cases and domains (Smart Home, Smart Cities, Industrial IoT)
• Challenges in deploying and managing IoT solutions
• Practical session: Analyzing three different industry scenarios and identifying the core IoT components required for each solution

Module 2: IoT Architecture and Layers

• The three-layer architecture (Perception, Network, Application)
• The five-layer architecture (Perception, Transport, Processing, Application, Business)
• Gateways and their role in translating protocols and data
• Data flow from device to cloud and back
• Designing scalable and maintainable IoT infrastructure
• Practical session: Sketching an end-to-end architecture diagram for a remote asset monitoring system, labeling all layers

Module 3: IoT Devices and Microcontrollers

• Understanding embedded systems and microcontrollers
• Introduction to popular platforms (Arduino, Raspberry Pi, ESP32)
• Comparing processing power, memory, and power consumption
• The role of Operating Systems (OS) in IoT devices (e.g., FreeRTOS)
• Selecting the right hardware for specific power constraints and environments
• Practical session: Setting up the environment and flashing a simple firmware onto an ESP32 or similar development board

Module 4: IoT Sensors and Actuators

• Classification of sensors (analog, digital, environmental, proximity)
• Interfacing with common sensors (temperature, humidity, light)
• Understanding actuators (motors, relays, LEDs) and control mechanisms
• Signal conditioning and noise reduction techniques
• Calibration and accuracy considerations for sensor data
• Practical session: Connecting a digital temperature sensor (e.g., DS18B20) to a microcontroller and reading/printing the data

Module 5: IoT Communication Protocols (Low Power)

• Understanding the need for low-power communication standards
• Detailed dive into Bluetooth Low Energy (BLE) and its profiles
• Overview of Zigbee and Z-Wave for home automation
• LoRaWAN and its capabilities for long-range communication
• Comparing range, bandwidth, and power usage of LPWAN technologies
• Practical session: Configuring a BLE device to advertise simple sensor data that can be read by a smartphone application

Module 6: IoT Communication Protocols (Network)

• TCP/IP stack relevance in IoT networking
• Message Queuing Telemetry Transport (MQTT) protocol in detail
• Constrained Application Protocol (CoAP) for resource-constrained devices
• HTTP/RESTful APIs for cloud communication
• Choosing the right protocol based on reliability, overhead, and constraints
• Practical session: Sending simulated sensor data from a device to a message broker using the MQTT protocol

Module 7: Data Acquisition and Processing at the Edge

• Defining Edge Computing and its benefits in IoT
• Reasons for processing data locally (latency, bandwidth, privacy)
• Basic data filtering, aggregation, and compression techniques at the device level
• Gateway-level data processing and middleware
• Software frameworks for edge computing (e.g., AWS IoT Greengrass, Azure IoT Edge)
• Practical session: Implementing a simple threshold-based alert system on the microcontroller to process data locally before sending it to the cloud

Module 8: Cloud Platforms for IoT

• Introduction to major cloud IoT services (AWS IoT, Azure IoT Hub, Google Cloud IoT)
• Device registration, provisioning, and lifecycle management
• Message routing rules and ingestion pipelines
• Shadow devices and state synchronization mechanisms
• Comparing platform capabilities for scalability and integration
• Practical session: Registering a virtual device on a cloud platform and using the platform's console to monitor its connectivity and status

Module 9: Data Storage and Analytics in IoT

• Selecting appropriate data stores for time-series data (e.g., InfluxDB, TimeStream)
• Big Data challenges in handling massive volumes of IoT data
• Stream processing and real-time analytics
• Batch processing for long-term data analysis
• Data governance and retention policies for IoT data
• Practical session: Designing a data pipeline that includes a time-series database and writing a simple query to calculate average sensor readings over time

Module 10: IoT Security Fundamentals

• The attack surface of an IoT ecosystem (Device, Network, Cloud, Application)
• The CIA triad (Confidentiality, Integrity, Availability) in the IoT context
• Threat modeling for IoT solutions
• Secure boot and hardware security modules (HSM)
• Regulatory requirements and privacy considerations (e.g., GDPR)
• Practical session: Identifying the top five security vulnerabilities in a sample smart home system architecture

Module 11: Device and Data Security in IoT

• Secure provisioning and identity management for devices
• Using unique device identifiers and secure element technology
• Implementing encryption for sensor data transmission (TLS/DTLS)
• Over-the-Air (OTA) firmware updates and security
• Techniques for preventing physical tampering of devices
• Practical session: Implementing secure communication between a device and the cloud using SSL/TLS encryption with generated certificates

Module 12: Network and Cloud Security in IoT

• Securing IoT gateways and perimeter defense
• Network segmentation and micro-segmentation for isolating devices
• Using VPNs and secure tunnels for remote access
• Best practices for securing the cloud platform's IoT services
• Anomaly detection and threat intelligence for fleet monitoring
• Practical session: Configuring network access control lists (NACLs) to restrict device communication to only the necessary cloud endpoints

Module 13: IoT Connectivity and Network Management

• Understanding different cellular options (2G, 3G, 4G, 5G, NB-IoT)
• SIM card management and carrier switching strategies
• Wi-Fi provisioning challenges for large-scale deployments
• Remote device management and diagnostics
• Power management techniques to maximize battery life
• Practical session: Outlining a plan for onboarding 10,000 new Wi-Fi devices in a warehouse environment, focusing on scalability and security

Module 14: Introduction to Edge and Fog Computing

• Differentiating Edge, Fog, and Cloud computing models
• Architectural patterns for hybrid edge-cloud deployments
• Distributing compute workloads across the edge-to-cloud continuum
• Resource constraints and deployment challenges at the edge
• Use cases where Fog computing is superior to pure Edge or Cloud
• Practical session: Designing a workload distribution strategy for real-time video analytics where capture is at the edge and long-term storage is in the cloud

Module 15: IoT Application Development

• Designing user-facing applications (mobile/web) for IoT data
• Using cloud APIs and SDKs to interact with device data
• Event processing and rule engines for automated actions
• Creating command-and-control applications for actuators
• Testing and debugging strategies for end-to-end IoT solutions
• Practical session: Developing a basic web endpoint to receive device data from the cloud platform and log it to a simple interface

Module 16: Data Visualization and Dashboarding

• Principles of effective time-series data visualization
• Choosing the right chart types for different sensor data
• Introduction to dashboarding tools (e.g., Grafana, cloud dashboards)
• Creating real-time data feeds and updating dashboards
• Designing user interfaces for complex industrial IoT (IIoT) systems
• Practical session: Building a simple dashboard using a cloud service or open-source tool to display real-time sensor data from the previously connected virtual device

Module 17: IoT Project Lifecycle and Best Practices

• Requirements gathering specific to IoT projects
• Prototyping, Minimum Viable Product (MVP), and pilot deployment
• Total Cost of Ownership (TCO) calculation and business justification
• Scalability testing and stress testing device fleets
• Operational management (DevOps) in an IoT environment
• Practical session: Creating a project plan and checklist for moving an IoT prototype from a lab environment to a field pilot deployment

Module 18: IoT Case Studies and Future Trends

• In-depth analysis of successful IoT deployments (e.g., smart agriculture, predictive maintenance)
• The role of Artificial Intelligence (AI) and Machine Learning (ML) in IoT (AIoT)
• Future of sensing and energy harvesting technologies
• Impact of 6G and next-generation connectivity on IoT
• Ethical considerations and social impact of ubiquitous sensing
• Practical session: Analyzing the architectural decisions made in a real-world predictive maintenance case study and discussing alternative approaches

Requirements:

·       Participants should be reasonably proficient in English.

·       Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588