IoT
Indoor intelligent perception systems have gained significant attention in recent years. However, accurately detecting human presence can be challenging in the presence of nonhuman subjects such as pets, robots, and electrical appliances, limiting the practicality of these systems for widespread use.
In this data port, we build the first comprehensive WiFi dataset of motion from various sources in real-world contexts. It includes WiFi data of humans, pets, cleaning robots, and fans.
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128 Views
The dataset is the experimental output of a 5G New Radio (NR) coverage expansion use case in the context of the NANCY project (https://nancy-project.eu/). Two experimental scenarios were carried out, namely a) a scenario where a user equipment (UE) is directly connected to a Base Station (BS) through a 5G NR link, and b) a scenario where an intermediate node is employed, which acts as a relay between the base station and the UE. To this end, two 5G BSs were deployed, using Ettus Research USRP B210 devices.
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722 Views
The Army Cyber Institute (ACI) Internet of Things (IoT) Network Traffic Dataset 2023 (ACI-IoT-2023) is a novel dataset tailored for machine learning (ML) applications in the realm of IoT network security. This effort focuses on delivering a distinctive and realistic dataset designed to train and evaluate ML models for IoT network environments. By addressing a gap in existing resources, this dataset aims to propel advancements in ML-based solutions, ultimately fortifying the security of IoT operations.
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5509 Views
We introduce a novel multi-modal dataset comprising point cloud data from a mmWave radar, RGB and depth images from an RGB-D camera, collected from 23 human subjects.
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396 Views
This dataset presents a comprehensive video collection of Internet of Things (IoT) products, encompassing both market successes and failures. Its primary focus is to explore the vision, technology, and capabilities of these IoT innovations, recognizing that products not viable today might inspire or become feasible in the future due to advancements in technology and reductions in manufacturing costs. The collection is particularly valuable for a wide array of stakeholders in IoT, including educators, researchers, product designers, and manufacturers.
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260 Views
This is a part of the data map of the distribution of base stations in China. This includes 54,718 entries about base stations. Data mainly contain the MCC, newsun focus, LAC, CELL, LNG, LAT, O_LNG, O_LAT, PRECISION, ADDRESS, DAY, REGION, CITY, COUNTRY this 14 items. LNG and LAT are the longitude and latitude data, respectively, and the location of each base station can be determined according to the data under these two categories. This is a part of the data map of the distribution of base stations in China. This includes 54,718 entries about base stations.
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148 Views
We define personal risk detection as the timely identification of when someone is in the midst of a dangerous situation, for example, a health crisis or a car accident, events that may jeopardize a person’s physical integrity. We work under the hypothesis that a risk-prone situation produces sudden and significant deviations in standard physiological and behavioural user patterns. These changes can be captured by a group of sensors, such as the accelerometer, gyroscope, and heart rate.
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841 Views
As the Internet of Things (IoT) continues to evolve, securing IoT networks and devices remains a continuing challenge.The deployment of IoT applications makes protection more challenging with the increased attack surfaces as well as the vulnerable and resource-constrained devices. Anomaly detection is a crucial procedure in protecting IoT. A promising way to perform anomaly detection on IoT is through the use of machine learning algorithms. There is a lack in the literature to identify the optimal (with regard to both effectiveness and efficiency) anomaly detection models for IoT.
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541 Views
The enhanced dataset is a sophisticated collection of simulated data points, meticulously designed to emulate real-world data as collected from wearable Internet of Things (IoT) devices. This dataset is tailored for applications in safety monitoring, particularly for women, and is ideal for developing machine learning models for distress or danger detection.
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1992 Views
The advent of the Internet of Things has increased the interest in automating mission-critical processes from domains such as smart cities. These applications' stringent Quality of Service (QoS) requirements motivate their deployment through the Cloud-IoT Continuum, which requires solving the NP-hard problem of placing the application's services onto the infrastructure's devices. Moreover, as the infrastructure and application change over time, the placement needs to continuously adapt to these changes to maintain an acceptable QoS.
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196 Views