IoT
Our released weight dataset for fusion results in edge-cloud collaborative inference contains the corresponding weighted summation weights under 50,000 edge-cloud collaborative DNN inference tasks, listing the five heterogeneous NVIDIA edge devices they use (NVIDIA Jetson Nano, TX2, NX, Orin NX, and AGX Orin), computing power (1.9~275TOPS), DNN model type (EfficientNet-B0, ViT-B16), and network bandwidth (0.5~8Mbps).
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Recently, a novel method was proposed to estimate the distance between a couple of wireless transceivers and a reflecting obstacle by analyzing the frequency dependence of the RSS. Although the resolution of this method is rather coarse for typical 2.4 GHz systems, a traffic monitoring system based on that novel approach has been successfully evaluated
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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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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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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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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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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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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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Location awareness is vital in next generation (xG) wireless networks to enable different use cases, including location-based services (LBSs) and efficient network management. However, achieving the service level requirements specified by the 3rd Generation Partnership Project (3GPP) is challenging.
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