A contribution to industrial and educational IoT
ein Beitrag zum Einsatz von IoT-Technologien in Industrie und Bildung
Seiten
2025
RPTU Rheinland-Pfälzische Technische Universität Kaiserslautern Landau (Verlag)
978-3-95974-228-3 (ISBN)
RPTU Rheinland-Pfälzische Technische Universität Kaiserslautern Landau (Verlag)
978-3-95974-228-3 (ISBN)
Abstract
The constantly expanding Internet of Things (IoT) poses significant challenges for
the devices and systems involved. When transporting the enormous amounts of data
that are collected every day by IoT devices, the security of the data transmission is a
crucial factor, especially in areas like the Industrial IoT. While state-of-the-art security
algorithms can achieve a high level of trust, the necessary underlying computations
pose a major challenge for small embedded systems with very restricted energy bud-
gets like small sensor nodes. The common approach of optimizing individual compu-
tational steps using special cryptographic hardware accelerators, however, still does
not fully exploit the available potential in terms of energy e!iciency and computation
time. Therefore, in addition to the impact of the utilization of hardware accelerators,
a holistic analysis approach is presented and evaluated in this thesis. The resulting
optimized IoT system demonstrates that even with a small amount of energy, which
can be collected, e.g., by an energy harvesting module, a wireless data transmission
that meets today’s security requirements can be realized.
In addition to the transmission of data, capturing the environment is an essential
element of the IoT. New challenging multi-sensor systems are needed to answer many
research questions, especially in the emerging field of Educational IoT and the asso-
ciated digitalization of learning environments. In cooperation with colleagues from
didactics research, a learning environment for augmented electrical experiments and
a learning platform for the field of photometry were developed. This work focuses on
the technical implementation, the required sensor systems, and the evaluation of the
learning platforms.
The contributions of this work o!er a clear added value for the related research
projects and future research projects due to their project-oriented implementation.
Furthermore, the modular and generic structure of the projects o!ers elementary
adaptability to other domains and systems.
The constantly expanding Internet of Things (IoT) poses significant challenges for
the devices and systems involved. When transporting the enormous amounts of data
that are collected every day by IoT devices, the security of the data transmission is a
crucial factor, especially in areas like the Industrial IoT. While state-of-the-art security
algorithms can achieve a high level of trust, the necessary underlying computations
pose a major challenge for small embedded systems with very restricted energy bud-
gets like small sensor nodes. The common approach of optimizing individual compu-
tational steps using special cryptographic hardware accelerators, however, still does
not fully exploit the available potential in terms of energy e!iciency and computation
time. Therefore, in addition to the impact of the utilization of hardware accelerators,
a holistic analysis approach is presented and evaluated in this thesis. The resulting
optimized IoT system demonstrates that even with a small amount of energy, which
can be collected, e.g., by an energy harvesting module, a wireless data transmission
that meets today’s security requirements can be realized.
In addition to the transmission of data, capturing the environment is an essential
element of the IoT. New challenging multi-sensor systems are needed to answer many
research questions, especially in the emerging field of Educational IoT and the asso-
ciated digitalization of learning environments. In cooperation with colleagues from
didactics research, a learning environment for augmented electrical experiments and
a learning platform for the field of photometry were developed. This work focuses on
the technical implementation, the required sensor systems, and the evaluation of the
learning platforms.
The contributions of this work o!er a clear added value for the related research
projects and future research projects due to their project-oriented implementation.
Furthermore, the modular and generic structure of the projects o!ers elementary
adaptability to other domains and systems.
| Erscheinungsdatum | 29.03.2025 |
|---|---|
| Reihe/Serie | Forschungsberichte Mikroelektronik ; 35 |
| Sprache | englisch |
| Maße | 145 x 210 mm |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Schlagworte | Educational IoT • Industrial IoT • IOT • Low Power • security • smart learning environment |
| ISBN-10 | 3-95974-228-2 / 3959742282 |
| ISBN-13 | 978-3-95974-228-3 / 9783959742283 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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Buch | Softcover (2025)
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