**Abstract**

This chapter describes a hands-on educational approach to teach Industrial Internet of Things (IIoT), including activities like problem analysis, programming, testing and debugging. Students are given autonomy to propose and evaluate different solutions, using adequate tools and following best practices. In parallel, key competencies like team management, project planning, costing and time scheduling, are imbibed in students to prepare them to become deployable automation engineers. To illustrate the proposed approach, we elaborate on the experience gained from teaching an elective course to undergraduate engineering students, in terms of learning outcomes, methodology, assessment and feedback. This course was centered on the Node Red platform (based on Node.js), using hardware devices like Arduino Uno, Nano and Raspberry Pi. Sensors commonly used and protocols like Modbus RTU/TCP, OPC UA, MQTT are discussed in the framework of common industrial applications.

**Keywords:** IIoT, experiential learning, Node Red, communication protocols, development boards

### **1. Introduction**

The skill gap for careers in a changing industrial sector has been identified by numerous authors [1], which has prompted educators to quickly adapt their courses, in order to prepare future engineers to excel in this new environment.

Typically, the following basic skills are in general required for engineers to succeed:


More formally, a document defining the skills and competencies needed in the automation field was proposed by The Automation Federation and International Society of Automation (ISA) [2]. It is made up of following tiers: personal effectiveness, academic, workplace, industry-wide technical, automation technical, occupation-specific knowledge, occupation-specific technical, occupation-specific requirements, and management (see **Figure 1**).

In this model, it is possible to observe that competencies related to Communication, Integration, Software and Cybersecurity are placed in tier 5.

#### **Figure 1.**

*Automation competency model [2].*

Therefore, this is the natural place for the training program that will be described in next sections.

The Internet of Things (IoT) can be defined as a global dynamic network where physical and virtual objects interact to enable a set of services. In this context, the Industrial Internet of Things (IIoT) is the extension of this network to industrial sectors like logistics, transportation, manufacturing, utilities, oil and gas, etc. This extension enables to gather real-time data, necessary to make better decisions across all business functions: procurement, production, shipping, maintenance, etc.

To prepare for this chapter, several reports of teaching experiences related to IIoT have been consulted. In [1], the author describes his personal experience, working with educators and practitioners. It is stated that the path toward creating the Industry 5.0 workforce should begin in elementary school, and a specific curriculum is proposed for each level.

In [3] an on-line learning infrastructure is proposed, that allows to engage in a range of programming of real-world sensing applications, using a board based on the Arduino microcontroller, with several onboard I/O devices, including a slider, a pushbutton switch, a bank of six LEDs, and analog inputs for additional sensors. In [4] a syllabus is proposed, which offers guidelines for the quality assurance and safeguarding of IoT solutions, suitable for advanced studies at postgraduate level.

This chapter describes a hands-on educational approach to teach IIoT. In Section 2, we discuss common educational challenges in this domain and how to overcome them. In Section 3, we elaborate on the experience gained from teaching an elective course to undergraduate engineering students, in terms of learning outcomes, methodology, assessment and feedback. Wherever possible, we provide the link to possible solutions of proposed problems, that we have developed in order to make it available for interested readers to test and adapt them for their own projects. Finally, we conclude this chapter.
