IoT
Dataset for An-ontology-integrating-the-open-standards-of-city-models-and-internet-of-things-for-smart-city-main research paper.
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For the innovation challenge for unmanned aerial vehicle (UAV) communications, we propose to demonstrate a two-tier Low Power Wide Area Network (LP-WAN) based on UAV base stations suitable for dynamic deployment and reconfiguration in deep rural areas. The proposed UAV-based LP-WAN network augments the existing macro-cellular NB-IoT network (Tier 1) with either an additional layer of mobile NB-IoT base stations or an additionaly layer of mobile LoRa base stations (Tier2).
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In recent years, drones have been used to transport payloads to remote and difficult access areas. A payload delivery with assisted relay system of two unmanned aerial vehicles (UAVs) is implemented. A local and web remote monitoring and control from a ground control station (GCS) for a pre-planned autonomous trajectory flight is developed in this work.
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This dataset contains the collection of temperature, humidity, heat index, thermal discomfort index and temperature and humidity index of five indoor environments in São Paulo, Brazil. Data were collected using the ESP32 microcontroller and the DHT11 temperature and humidity sensor.
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Data used for evaluation of the Chameleon system. We use it to evaluate capabilities of sensor fusion system that is able to adapot to multiple envrionemnts and monitor activity states within a room. The data set is divided by the two deployments and includes inforamtion for both of the sensors used to test the system. We include two weeks worth of data along with training and testing accuracy results.
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RSSI measurements collected by four anchors while receiving messages from a single mobile node transmitting advertisement and extended advertisement messages in all BLE channels (both primary and secondary advertisement channels). Tests conducted in 10x10 m office area (no large obstacles), with 4 anchors located in the corners of the area.
Cite https://ieeexplore.ieee.org/document/9661373 when using this dataset in your work.
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We have prepared a synthetic dataset to detect and add new devices in DynO-IoT ontology. This dataset consists of 1250 samples and has 35 features, such as feature-of-interest, device, sensor, sensor output, deployment, accuracy, unit, observation, actuator, actuation, actuating range, tag, reader, writer, etc.
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Inventory is an accounting term that refers to goods or products that are in various stages of being made ready for sale, purchase, and stock. The inventory management system is a software system that plays a critical role to track inventory levels, orders, and sales of a shop. Today, customers are more and more demanding, Companies can incur heavy losses when customers are not satisfied and do not return, therefore they need to have a better understanding of their customers’ behaviors in order to improve service and products.
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The dataset contains the path loss measurements obtained with a LoRa (868 MHz) transmitting radio and five receivers. The receivers move in a search area covering both outdoor and indoor areas wherein a double-slope path loss is experienced. The data can be used to test range-based localization algorithm through the received signal strength.
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It is important for network operators to carry out traffic and application characterization to gain insights into the activity of their networks. Several studies proposed methods that extract features from network traffic to characterize it, or to classify the application that produced it, based on a ?man in the middle? network interception point that can analyze the entire network traffic of an organization.
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