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Design and development of an Industry 5.0 IoT gateway with Edge Processing capability
keywords ARTIFICIAL INTELLIGENCE, EDGE COMPUTING, EMBEDDED CYBERSECURITY, INDUSTRY 5.0, INTERNET-OF-THINGS (IOT)
Reference persons LUCA BARBIERATO, LORENZO BOTTACCIOLI, EDOARDO PATTI
Research Groups Electronic Design Automation(EDA)
Thesis type EXPERIMENTAL APPLIED
Description Edge Computing requires scalable software and hardware platforms capable of accelerating many field operations to automate procedures and provide real-time decision support in various application sectors, ranging from smart factories to autonomous driving to simple household applications. Thanks to Artificial Intelligence and the capabilities of Edge Computing, it is now possible to use machine learning processes to process data in real-time, ensuring the best possible automation and decision support experience for the service or end-user.
The thesis project focuses on the development of an IoT gateway for Industry 5.0 to promote Edge Computing with the potential to host, execute, and manage sensor analytic algorithms, artificial intelligence, and encryption. These algorithms traditionally require high computational capabilities that are not available on edge devices, which are designed to be highly pervasive, installed outside data centers, with limited access to energy sources and high-bandwidth digital communication networks. The evolution of hardware technologies (e.g. Coral.ai), the proliferation of Internet of Things systems, and the progressive improvement of low-power, high-bandwidth connectivity has made it possible to integrate computationally intensive algorithms at the peripheral level. The gateway will develop flexible and scalable technology to create an edge processing chain that can provide support and relieve the cloud from post-processing operations on field-collected data.
The objectives of the thesis to reach are the following:
- Conduct a comprehensive literature review on Edge Computing, focusing on its applications, benefits, challenges, and existing research and developments in the field.
- Analyze the current state of IoT gateways for Industry 5.0 and their limitations in supporting Edge Computing, specifically in terms of hosting, executing, and managing sensor analytic algorithms, artificial intelligence, and encryption.
- Identify the computational requirements of these algorithms and assess their compatibility with edge devices, which are designed to be highly pervasive and have limited access to energy sources and high-bandwidth digital communication networks.
- Investigate advancements in hardware technologies, such as Coral.ai, and their potential for integrating computationally intensive algorithms at the edge.
- Evaluate the impact of the proliferation of Internet of Things systems and the progressive improvement of low-power, high-bandwidth connectivity on the feasibility of implementing Edge Computing in various application sectors.
- Develop flexible and scalable technology for creating an edge processing chain that can effectively support and offload post-processing operations from the cloud for field-collected data.
- Test and validate the developed IoT gateway prototype, assessing its performance in terms of computational capabilities, data processing speed, and reliability.
- Analyze the results and provide recommendations for further improvements and future research in the field of Edge Computing for Industry 5.0.
This project is carried out within the objectives of the project “Circular Tracing per l’Industria 5.0” funded by Ministero delle Imprese e del Made in Italy within the program “Accordi per l’Innovazione”.
Required skills - Experience in Python Object Oriented Programming (OOP)
- Experience in Internet protocols (e.g. HTTP, MQTT)
- Experience in Internet-of-Things (e.g. publish/subscribe approach, request/response approach)
- Experience in data format (e.g. JSON)
- Basic experience in Linux Operative System
- Basic experience in cybersecurity suite (e.g. OpenSSL)
- Problem-solving and proactivity soft-skill
Deadline 13/06/2025
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