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139 results for “iot”
An Exploratory Study on Code Quality, Testing, Data Accuracy, and Practical Use Cases of IoT Wearables
<p>Data used in IoT Wearable Study</p>
Implementation of a Multi-Channel DASH7 IoT Communication System for Packet Investigation and Validation
<p>This repository contains three cabled <a href="https://www.dash7-alliance.org/" target="_blank" rel="noopener">DASH7</a> data sets. All data sets are formatted as sigmf-data and sigmf-meta pairs, which can be investigated using <a href="https://iqengine.org/" target="_blank" rel="noopener">IQEngine</a>, <a href="https://www.gnuradio.org/" target="_blank" rel="noopener">GNU Radio</a>, or <a href="https://www.mathworks.com/products/matlab.html" target="_blank" rel="noopener">MATLAB</a>. Below you can find a more extended description of the data sets.</p> <p><strong>CH0.zip, CH93.zip, CH186.zip:</strong></p> <ul> <li>Cabled data sets of 3 channels</li> <li>10 recordings per channel</li> <li>1 DASH7 packet per file pair (SigMF)</li> <li>Fc: 866.5 MHz</li> <li>Sample rate: 7.68 MHz</li> <li>Data type: ci16_le</li> <li>Length: 1 second</li> <li>Channel class: Lo-Rate</li> <li>Sync word: 0x0B67</li> <li>3 Lo-Rate channel recordings <ul> <li>channel 0 (Fc: 863.0125 MHz), </li> <li>channel 93 (Fc: 865.3375 MHz), </li> <li>channel 186 (Fc: 867.6625 MHz)</li> </ul> </li> <li>Payload: 3 bytes [counter_byte 0xAB 0xCD] <ul> <li>counter byte is always [0x00]</li> </ul> </li> </ul> <p><strong>logs.zip:</strong></p> <ul> <li>Contains all the DASH7 gateway logs per measured channel.</li> </ul>
Development of Indoor Vegetable Plant Rack Design Based on IOTs to Prevent Stunts
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IoT bugs based on CVEs and Issues
<p>we created two datasets of IoT-related vulnerable clones.</p>
Distributed Sensing with Low-cost Mobile Sensors towards a Sustainable IoT
<p>This zip file contains the dataset used to produce Figure 4 of "Distributed Sensing with Low-cost Mobile Sensors towards a Sustainable IoT".</p> <p>It contains two folders, the first for the stationary sensors and the second for the mobile sensors.</p>
iot 3rd-party authorization
<p>Snapshot of acknowledgement email</p>
City scale particulate matter monitoring using LoRaWAN based air quality IoT devices
<p>Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that i) the physical device developed can operate at a city scale ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.</p>
Automated and Reproducible Application Traces Generation for IoT Applications Dataset Lighting Application
<p>This data represents an IoT smart city application. It results from an experiment that runs a firmware on a set of representative nodes that have to exchange packets in a broadcast mode using the IEEE 802.15.4-2006 MAC layer and RPL routing protocol. Each application produces data according to 1 of the 3 following modes: periodic (Tx nodes produce data every x milliseconds), event based (modeled with an exponential law with occurrence rate lambda) and hybrid (combination of the two previous modes).</p> <p>Each application has the following parameters :<br> - Surveillance has 10 sensors and 3 routers that exchange packets with a length of 127B. The generation type is exponential with a lambda of 196.74.<br> - Emergency Response has 40 sensors and 5 routers that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 0.03 and a period of 30 seconds.<br> - HVAC has 100 sensors and 5 routers that exchange packets with a length of 60B. The generation type is periodic with a period of 260 seconds.<br> - Lighting has 100 sensors and 5 routers that exchange packets with a length of 30B. The generation type is exponential with a lambda of 0.00208.<br> - VoIP has 10 sensors and 1 router that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 15.74 and a period of 0.063532 seconds.</p> <p>As a result, this dataset has files containing the following data :<br> - Received data : name of the receiving node (node_name); message reception time (timestamp); message unique identifier (message_id); reception delay in milliseconds (reception_delay)<br> - Transmitted data : name of the transmitting node (node_name); message transmission time (timestamp); message unique identifier (message_id); success (transmission success)</p> <p>Furthermore, datasets of 5 more IoT Applications are available at the following <a href="https://zenodo.org/record/7347970">link</a> <br> <br> For any questions, please contact Nina Santi (<a href="mailto:nina.santi@inria.fr">nina.santi@inria.fr</a>)</p>
Automated and Reproducible Application Traces Generation for IoT Applications Dataset
<p>This data represents an IoT smart city application. It results from an experiment that runs a firmware on a set of representative nodes that have to exchange packets in a broadcast mode using the IEEE 802.15.4-2006 MAC layer and RPL routing protocol. Each application produces data according to 1 of the 3 following modes: periodic (Tx nodes produce data every x millisecond), event based (modeled with an exponential law with occurrence rate lambda), and hybrid (combination of the two previous modes).</p> <p>Each application has the following parameters :<br> - Surveillance has 10 sensors and 3 routers that exchange packets with a length of 127B. The generation type is exponential with a lambda of 196.74.<br> - Emergency Response has 40 sensors and 5 routers that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 0.03 and a period of 30 seconds.<br> - HVAC has 100 sensors and 5 routers that exchange packets with a length of 60B. The generation type is periodic with a period of 260 seconds.<br> - Lighting has 100 sensors and 5 routers that exchange packets with a length of 30B. The generation type is exponential with a lambda of 0.00208.<br> - VoIP has 10 sensors and 1 router that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 15.74 and a period of 0.063532 seconds.</p> <p>As a result, this dataset has files containing the following data :<br> - Received data : name of the receiving node (node_name); message reception time (timestamp); message unique identifier (message_id); reception delay in milliseconds (reception_delay)<br> - Transmitted data : name of the transmitting node (node_name); message transmission time (timestamp); message unique identifier (message_id); success (transmission success)</p> <p>Furthermore, a dataset of an IoT Lighting Application is available at the following <a href="https://zenodo.org/record/7348232#.Y4D9VdJBxhE">link</a><br> For any questions, please contact Nina Santi (<a href="mailto:nina.santi@inria.fr">nina.santi@inria.fr</a>)</p>
Literature Review - IoT for SmartCities
<p>As the world becomes increasingly urbanized, there is a growing need to address the challenges of urbanization. Smart cities offer a way to address these challenges by using technology to make cities more efficient, sustainable, and livable. However, since it is a recent field of development, there is a lack of understanding of some concepts. Therefore, we performed a structured literature review of secondary studies to characterize Smart Cities regarding their features, applications, technologies, and challenges. The findings indicate the research opportunities in the field, focusing on designing Smart Cities solutions. This work provides a characterization of Smart Cities and outlines the issues that need to be addressed for them to be established.</p>
IoT Emulated Dataset for ICMP/Ping Normal and Malicious Traffic
<p>These datasets are related to Intrusion Detection System, Computer Network Traffic and IoT.</p> <p>These datasets are generated for the purpose of differentiating <strong>ICMP/Ping normal and malicious traffic </strong>that are generated from an embedded device (IoT). The differentiation analysis is done using machine learning.</p> <p>There are three types of files that depend on each module of our research framework. The data generation sequence is as follows:</p> <p>The <strong>pcap files </strong>(network traffic) are generated first, the device used to generate the data is an ESP-01s. Afterwards, the pcap files are transformed into <strong>log files </strong>using the Zeek tool, the log files are then extracted and placed into <strong>CSV files</strong>.</p> <p>The CSV files are labeled and ready for the Machine Learning process.</p> <p> </p> <p>The publication reference for this work is here : https://doi.org/10.1109/ACCESS.2023.3327061</p> <p>The code link: <a href="../badge/latestdoi/619245496">https://zenodo.org/badge/latestdoi/619245496</a></p> <p><strong>This version of the release (0.2.0) is for ping flood with spoofed IPs, however, the previous version (</strong>0.1.0)<strong> is for static IP</strong></p> <p> </p> <p> </p> <p> </p>
QoS data set for IoT services
<p>This is a dataset on Quality of Service (QoS) for IoT services related to experiments. It consists of data on four QoS attributes for services generated within specified ranges, denoted as Execution time, Service cost, Credibility, and Reliability. The data has been normalized.There are some different IoTS scales in this dataset, including 6×25,6×50,6×75,6×100;10×25,10×50,10×75,10×100;20×25,20×50,20×75,20×100.<br> </p>
The Effect of IoT-based Smart Exercises System in the Senior Adults
ClinicalTrials.gov study NCT04137939. IPD Sharing: Not stated. Countries: 1. Publications: 1.
UNSW IoT traffic data with packets, flows, and protocols
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Supplementary Material - SPL and IoT Studies
<p>Supplementary Material - SPL and IoT Studies</p>
IoT device identification - Same room
<p>Same room measurements of the 868 MHz ISM band. The transmitter device and receiver are placed in the same room.</p> <p>Frequency: 863-870 MHz (center 866,5 MHz)</p> <p>Sample Frequency: 10 MSPS</p> <p>Date of measurement: 15 November 2018</p> <p>Location: Connectivity Lab, Fredrik Bajers Vej 7C, Aalborg University, Denmark</p>
Dataset for: Trust Trackers for Computation Offloading in Edge-Based IoT Networks
<p>The dataset used to generate graphs for: Matthew Bradbury, Arshad Jhumka and Tim Watson.<br> Trust Trackers for Computation Offloading in Edge-Based IoT Networks. In IEEE INFOCOM, 1–10. IEEE, 10–13 May 2021.</p> <p>Also includes instructions for experiment setup.</p> <p>Scripts from https://github.com/MBradbury/iot-trust-task-alloc are required to analyse and graph these results.</p>
Light Power Resource Variability for Energy Harvesting Photovoltaics for Self-Powered IoT
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Multi-faceted Study on Microservices-Based IoT Systems Deployment: Challenges, Practices, and Performance Analysis
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An Approach to Assess Robustness of MQTT-based IoT Systems - Supplementary Material
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.