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Axel Sikora

Researcher at University of Applied Sciences Offenburg

Publications -  153
Citations -  1342

Axel Sikora is an academic researcher from University of Applied Sciences Offenburg. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 12, co-authored 133 publications receiving 1004 citations. Previous affiliations of Axel Sikora include Baden-Wuerttemberg Cooperative State University Loerrach & Information Technology University.

Papers
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Proceedings ArticleDOI

Coexistence of IEEE802.15.4 with other Systems in the 2.4 GHz-ISM-Band

TL;DR: In this article, the mutual effects of IEEE 802.15.4 and 802.11 in the 2.4 GHz ISM band are examined with real-life equipment, in order to quantify coexistence issues.
Proceedings ArticleDOI

Free space range measurements with Semtech Lora™ technology

TL;DR: This contribution gives a short overview into the technologies to support Long Range (LoRa ™), describes the outdoor setup at the Laboratory Embedded Systems and Communication Electronics of Offenburg University of Applied Sciences, shows detailed measurement results and discusses the strengths and weaknesses of this technology.
Proceedings ArticleDOI

A localization system using inertial measurement units from wireless commercial hand-held devices

TL;DR: A newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets, and a novel step length estimator is proposed.
Proceedings ArticleDOI

Low Latency V2X Applications and Network Requirements: Performance Evaluation

TL;DR: This paper classify V2X use-cases and their requirements in order to identify cellular network technologies able to support them, and a starting point to migrate to Narrowband IoT (NB-IoT) or 5G - solutions is given.
Journal ArticleDOI

A survey of machine-learning techniques for condition monitoring and predictive maintenance of bearings in grinding machines

TL;DR: In this article, the authors present an overview of the most important approaches for bearing-fault analysis in grinding machines, which includes the classification of bearing faults, the detection of unhealthy conditions, the position of the error (e.g., at the inner or at the outer ring of the bearing) and the severity, which detects the size of the fault.