IoT
This dataset presents a comprehensive collection of the indoor temperature data collection procedure, meticulously designed to develop a robust dataset. The primary purpose of this dataset is to train a sophisticated machine learning algorithm capable of dynamically controlling the climate within indoor environments. The data is gathered in the A-block hostel room block on the 13th floor of VIT University Chennai, from April 15th to April 22nd, 2024.
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409 Views
Bangladesh's aquaculture industry provides employment and food security. However, water quality management, disease control, and environmental monitoring continue to hinder aquaculture productivity and sustainability. This research uses IoT devices to create a comprehensive aqua fisheries dataset to solve these issues.The project uses IoT sensors and data collection methods to monitor water temperature, pH, dissolved oxygen, and turbidity in Bangladeshi aquaculture ponds.
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326 Views
The dataset consists of 4-channeled EOG data recorded in two environments. First category of data were recorded from 21 poeple using driving simulator (1976 samples). The second category of data were recorded from 30 people in real-road conditions (390 samples).
All the signals were acquired with JINS MEME ES_R smart glasses equipped with 3-point EOG sensor. Sampling frequency is 200 Hz.
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147 Views
<p>Mixed critical applications are real-time applications that have a combination of both high and low-critical tasks. Each task set has primary tasks and two backups of high-critical tasks. In the work carried out, different synthetic workloads and case studies are used for extracting the schedule and overhead data on a real-time operating system. The utilization of the task sets lies between 0.7 to 2.4.The Linux kernel is recompiled with Litmus-RT API to monitor the scheduling decisions and also measure the overheads incurred.
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167 Views
QuaN is a collection of specially designed datasets for exploring the impact of noise quantum machine learning and other applications. The presented work focuses on the transformation of clean datasets into noisy counterparts across diverse domains, including MNIST-handwritten digits datasets, Medical MNIST, IRIS datasets and Mobile Health datasets. The dataset is created using noise from classical and quantum domains.
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428 Views
We investigated the long term functionality of the designed PMCS in a practical use case where we monitored plant growth of classical horticulture Dianthus flowers (Dianthus carthusianorum) under the effect of plastic mulching over a period of 4 months. This use case represents a common phenological monitoring case that can be used in agricultural studies. For this, we integrated our PMCS in an embedded vision camera equipped with the openMV H7 Plus board in a waterproof housing [26]. The system shown in Fig.
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50 Views
These datasets are collected from the tests that were performed for decentralized synchronization among collaborative robots via 5G and Ethernet networks using with/without causal message ordering. These files have different names depending on the connection type and causality type. For example, 5G_with_causality.txt file stores the test results which were performed on a public 5G network using causal message ordering for different cobot groups like 5,10,20,30,40. The test results for each robot group are separated in each txt file.
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5 Views
Wi-Fi FTM RSSI Localization dataset
Wi-Fi Fine Time Measurement for positioning / Indoor Localization in 3 different locations and using 8 different APs
Custom APs using ESP32C3 and Raw FTM is measured in nanoseconds
Data is only measured at the Router Side
Data is not measured at client side
Has 4 datasets inside the zip folder with over 100,000 data points
Contains processed Wi-Fi FTM packets from various routers in:
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1143 Views
Wi-Fi BLE RSSI SQI Localization dataset
Wi-Fi BLE RSSI for positioning / Indoor Localization in 4 different locations and using 18 different APs
Data is only measured at the Router Side
Data is not measured at client side
Has 12 datasets inside the zip folder with over 1,000,000 data points
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809 Views
This dataset presents real-world IoT device traffic captured under a scenario termed "Active," reflecting typical usage patterns encountered by everyday users. Our methodology emphasizes the collection of authentic data, employing rigorous testing and system evaluations to ensure fidelity to real-world conditions while minimizing noise and irrelevant capture.
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595 Views