10 papers
Machine Learning to Predict Slot Usage in TSCH Wireless Sensor Networks
Stefano Scanzio, Gabriele Formis, Tullio Facchinetti +1
Wireless sensor networks (WSNs) are employed across a wide range of industrial applications where ultra-low power consumption is a critical prerequisite. At the same time, these sy…
Improving Wi-Fi Network Performance Prediction with Deep Learning Models
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
The increasing need for robustness, reliability, and determinism in wireless networks for industrial and mission-critical applications is the driver for the growth of new innovativ…
Widening the Coverage of Reference Broadcast Infrastructure Synchronization in Wi-Fi Networks
Gianluca Cena, Pietro Chiavassa, Gabriele Formis +1
Precise clock synchronization protocols are increasingly used to ensure that all the nodes in a network share the very same time base. They enable several mechanisms aimed at impro…
On the Prediction of Wi-Fi Performance through Deep Learning
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
Ensuring reliable and predictable communications is one of the main goals in modern industrial systems that rely on Wi-Fi networks, especially in scenarios where continuity of oper…
Compression of executable QR codes or sQRy for Industry: an example for Wi-Fi access points
Stefano Scanzio, Gabriele Formis, Pietro Chiavassa +2
Executable QR codes, or sQRy, is a technology dated 2022 that permits to include a runnable program inside a QR code, enabling interaction with the user even in the absence of an I…
Accurate and Efficient Prediction of Wi-Fi Link Quality Based on Machine Learning
Gabriele Formis, Gianluca Cena, Lukasz Wisniewski +1
Wireless communications are characterized by their unpredictability, posing challenges for maintaining consistent communication quality. This paper presents a comprehensive analysi…