IoT
With the modern day technological advancements and the evolution of Industry 4.0, it is very important to make sure that the problem of Intrusion detection in Cloud , IoT and other modern networking environments is addressed as an immediate concern. It is a fact that Cloud and Cyber Physical Systems are the basis for Industry 4.0. Thus, intrusion detection in cyber physical systems plays a crucial role in Industry 4.0. Here, we provide the an intrusion detection dataset for performance evaluation of machine learning and deep learning based intrusion detection systems.
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data of fishing operations from beidou, AIS and policy.
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307 Views
Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).
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1945 Views
README.txt for simulation files IEEE_Collaboration_N_entities_2021.mdl and IEEE_2_Platforms_federation_SF_2021.mdl
This is a README.txt for the model published on the paper titled:
Improving IoT Federation Resiliency with Distributed Ledger Technology, 2021, Elo T, et al.
This readme describes how to replicate the main simulation results from the paper using a Vensim
model file. The model file has been generated using the Vensim DSS Macintosh Version
8.0.7 Double Precision x64.
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186 Views
Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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Abstract—In the 2021 and later we know that the technology
will have key participation of to help us in all kind of tasks
mainly using internet connection, due the new normality.
Industry 4.0 has been one of the most relevant field. IoT as part
of it. This Systematic Literature Review (SLR) we will cover
the South America countries and their development status,
addressing the development categories and the Hardware that
has been cited on papers on the last 5 years.
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271 Views
We elaborate on the dataset collected from our testbed developed at Washington University in St. Louis, to perform real-world IIoT operations, carrying out attacks that are more prelevant against IIoT systems. This dataset is to be utilized in the research of AI/ML based security solutions to tackle the intrusion problem.
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2790 Views
Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems
Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems is called ERT-CORE. It defines specific input parameters, i.e., system's workload, average request processing time and availability. Defined parameters reflect system's state and react on its changes. Based on these parameters system reliability evaluation is performed.
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232 Views
Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).
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1514 Views
The Bluetooth 5.1 Core Specification brought Angle of Arrival (AoA) based Indoor Localization to the Bluetooth Standard. This dataset is the result of one of the first comprehensive studies of static Bluetooth AoA-based Indoor Localization in a real-world testbed using commercial off-the-shelf Bluetooth chipsets.
The positioning experiments were carried out on a 100 m² test area using four stationary Bluetooth sensor devices each equipped with eight antennas. With this setup, a median localization accuracy of up to 18 cm was achieved.
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1219 Views