Project results

Internet of Things: Skills and learning paths

Introduction

Over the last decade, the Internet of Things (IoT) has undergone rapid and extensive changes becoming a key enabler of digital transformation across many sectors. The IoT approach evolved into a paradigm that integrates a broad set of technologies, each of which is advancing at a rapid pace.

IoT combines different fields into one, like coding, computing, smart technology, artificial intelligence (AI) and wireless networks. Requirement to know each of these fields has been creating an IoT skills gap.

The Internet of Things offers a range of career opportunities in many industries including healthcare, manufacturing, utilities, transportation, agriculture, and consumer products. Jobs are expected to increase in the coming years across industries.

IoT skills are also important for most jobs and occupations of the future of work, which will be characterized by increased automation, transfer of labour-intensive tasks from humans to machines, as well as by increased human-machine collaboration.

For these reasons the problem of IoT skills gap needs solutions.

In the “EU-IoT Framework for Internet of Things Skills: Closing the Talent Gap” white paper, author John Soldatos summarizes the findings of various skills surveys regarding the shortage of IoT skills.

Addressing the IoT skills gap

Addressing the IoT skills gap is very important for adopting and leveraging cutting-edge technologies of the fourth industrial revolution in many economic sectors, but the development of solutions is challenging for several reasons, as reported by John Soldatos in the white paper:

• The multi-facet nature of IoT skills: IoT is not a single technology, but rather a computing paradigm that integrates multiple technology solutions. Therefore, most IoT roles are associated with multiple skills from different technological areas.

• The complexity of IoT solutions: IoT solutions comprise multiple technology infrastructures, which have diverse development and deployment requirements. Tacking this complexity asks for IoT professionals with multi-disciplinary profiles and different skillsets.

• The unprecedented technology acceleration: Digital technologies are evolving in a rapid pace. This creates a very dynamic IoT landscape, while makes it very difficult for skills development activities to keep up with the evolution of the state of the art.

• The skills shortage in related technologies: IoT projects require skills in cutting edge technological areas like ML (Machine Learning), AI (Artificial Intelligence), and cybersecurity. Each of these technology areas is experiencing its own skills shortage. This makes it very difficult to properly staff complex IoT projects.

• The need for collaboration in IoT projects: Successful IoT deployments are all about collaboration between different stakeholders and business actors. Hence, they bring together inter-disciplinary and multi-disciplinary expertise.

IoT skills profiles

Emerging of new technologies, as well as the applications that go along, requires all actors to up skill to successfully operate them.

In the “EU-IoT Framework for Internet of Things Skills: Closing the Talent Gap” white paper, the author presents how different IoT skills can be clustered in meaningful profiles, notably the profiles that are currently high in demand in the global job market.

The following guide proposes a possible classification of IoT skills profiles and the training required for each of them, that can be envisioned as learning paths towards IoT.

1. IoT Application Developer

An IoT application developer is a professional who can develop, manage and monitor IoT devices and systems by merging three essential elements – data, technology, and research. Having strong programming skills is a must for the daily activities of IoT developers. As personalities, IoT developers are encouraged to be very collaborative and communicative in a team environment, have an innovative mindset, and are willing to learn new trends and developments within the IoT field.

Individual skills: Python, JavaScript, IoT & Cloud Computing, DevOps, Docker, Kubernetes, Sensors, WSN, Arduino, MQTT.

Education and training: Aspiring IoT developers will benefit from a master’s degree  and extensive coding skills. Those with a background in engineering, software development, or computer science will be able to enter the IoT field most easily.

2. IoT Network Engineer

The IoT network engineer role is crucial for the maintenance of IoT infrastructure. The complexity of managing IoT hardware demands the need for IoT network engineers or architects. IoT network engineers can use their specialization in networking and network infrastructures to ensure proper functionality of all connections in the IoT network. In addition, career opportunities in IoT networking also demand specialization in uses of different sensor modules, protocols, integrators and transmitters.

Individual skills: Sensors & IoT Devices, LPWAN, 4G/5G/6G, WiFi, Bluetooth, MQTT.

Education and training: The design and management of wireless networking systems are essential functions of IoT network engineers. IoT networks can be complex because of the volume of connected devices, and each network design decision will be impacted by the various standards, protocols, and technologies available. In addition, IoT network professionals must know how to secure wireless networking systems.

3. IoT Data Analytics Expert

An IoT data analyst works on obtaining relevant insights from data collected through IoT devices. Within the IoT field, data science helps make decisions in response to data, identify patterns and anomalies, and filter or discard irrelevant data. Developers with a strong foundation in machine learning programming and analysis can help improve how IoT systems work.

Individual skills: Data Science, Machine Learning, TinyML, Sensors, WSN.

Education and training: The important skills required for IoT data analyst jobs include fluency in statistics and ability to identify patterns and correlations. At the same time, IoT data analysts also need skills in presenting IoT data insights in clear tabular or graphical form. On top of it, IoT data analysts also need skills in statistics-based languages.

4. Embedded Systems Engineer

Generally, systems engineers in IoT have the task to develop and implement software for embedded devices and systems, which includes sensors, microprocessors and software that helps run the systems. They use software design techniques to resolve a multitude of related tasks, such as investigation, design, developing, and testing.

Individual skills: Embedded Systems, FPGA, Printed Circuit Board (PCB) Design, Sensors, Actuators, WSN.

Education and training: An understanding of embedded systems, computer architecture, hardware security, and software will be helpful in this career path. Candidates can learn many of these skills with a master’s degree in a relevant field.

Conclusions

In perspective, education programs for IoT profiles may increasingly incorporate AI, machine learning, and cybersecurity aspects, recognizing their integral role in IoT development. There might be also a greater focus on practical, hands-on learning experiences, reflecting the dynamic and evolving nature of IoT technology.

Education for IoT must include also interdisciplinary training, combining technical knowledge with soft skills like problem-solving and creativity.

Additionally, continuous learning and up skilling will likely become essential, given the rapid technological advancements in the IoT field. Collaboration and teamwork skills could also be emphasized, considering the multi-faceted and collaborative nature of IoT projects.