IoT
The dataset reflects a single household (home) power profile related to the grid. Households include typical appliances, two air-to-air heat pumps, a 3-phase 18 kW through-flow water heater, 6 kW solar panels and a 2,5 kW charger for the electric car.
For five-month (April_August) in 2022, every 0.2 sec took each 3-phase voltage and current measurement, calculate power and harmonics (up to 15th) for power profile registration.
Positive value reflects energy flow from the grid to a household, and negative values are energy flow to the grid.
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1243 Views
This dataset has 2 different RFID manufacturer tags (2 of each) with different EPC content. Signal Strength data of all 4 tags were taken in the frequency spectrum in the US UHF (900-910 MHz) range. There are 100 data readings per tag, so 400 files total.
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268 Views
Information Collected by Green Care
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388 Views
This article presents the details of the Cardinal RF (CardRF) dataset. CardRF is acquired to foster research in RF- based UAV detection and identification or RF fingerprinting. RF signals were collected from UAV controllers, UAV, Bluetooth, and Wi-Fi devices. Signals are collected at both visual line-of-sight and beyond-line-of-sight. The assumptions and procedure for the data acquisition are presented. A detailed explanation of how the data can be utilized is discussed. CardRF is over 65 GB in storage memory.
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8122 Views
Solar Insecticidal Lamp, as a professional device for smart phytoprotection, can kill the insects to calculate the insect density, further guiding the famers to spray pesticide accurately. Various experiments were performed by a testbed, combined Solar Insecticidal Lamp with two cameras, to get the dataset including time, Pulse Number of Insecticidal Sounds, Pulse Number of Insecticidal Discharges, insecticidal status, abnormal value, and insecticidal quantity. The dataset can be used for a variety of methods related to the research of insecticidal counting.
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349 Views
In this dataset, 57 DoT are seleted from three website: StateoftheDApps, DAppradar and DApp.com. The websites are search engine sites for variety of DApps. These selected DoT are all based on Ethereum, achieving applications on renting cars, finding chargers and sharing route. We download the data including basic information of these DoT and the transaction data from Etherscan. This dataset can be used to analyze the abnormal transactions of DoT.
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23 Views
Please cite the following paper when using this dataset:
N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049
Abstract
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1671 Views
This dataset supports a review and an in-depth analysis on the environmental impacts of integrated circuits (ICs). The paper is currently under review.
We gathered data from foundry reports, industry roadmaps, scientific literature, and commercial state-of-the-art LCA databases. All assumptions are detailed.
More information can be found on the GitHub repository : https://github.com/ThibaultPirson/environmental-footprint-IC.
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547 Views
This dataset contains Wi-Fi sensing data using Channel State Information (CSI) for respiration rate measurements in a standard 3m x 3m room. The Wi-Fi CSI data was collected using the Wi-Fi module on the ESP32 Microcontroller units using the esp32-csi-tool. The Wi-Fi CSI data is accompanied by respiration belt data taken with the Wi-Fi measurements simultaneously using the Neulog NUL-236 respiration belt logger as ground truth.
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80 Views
In this paper, we develop an internet of medical things (IoMT)-based electrocardiogram(ECG) recorder for monitoring heart conditions in practical cases. To remove noise from signals recorded by these non-clinical devices, we propose a cloud-based denoising approach that utilizes deep neural network techniques in the time-frequency domain through the two stages. Accordingly, we exploit the fractional Stockwell transform (FrST) to transfer the ECG signal into the time-frequency domain and apply the deep robust two-stage network (DeepRTSNet) for the noise cancellation.
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354 Views