UAV
Ground-to-air (GA) communication using unmanned aerial vehicles (UAVs) has gained popularity in recent years and is expected to be part of 5G networks and beyond. However, the GA links are susceptible to frequent blockages at millimeter wave (mmWave) frequencies. During a link blockage, the channel information cannot be obtained reliably. In this work, we provide a novel method of channel prediction during the GA link blockage at 28 GHz.
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There are two data files, named 'Data1.mdb' and 'Data2.mdb'. A total of 87,272 pieces of data, including 43,607 pieces of data in file 'Data1.mdb' and 43,665 pieces of data in file 'Data2.mdb'. Please open them with ACCESS software.
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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 paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names
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GPS spoofing and jamming are common attacks against the UAV, however, conducting these experiments for research can be difficult in many areas. This dataset consists of a logs from simulation and live fights. Logs include data from a benign flight as well as one where the UAV experiences an attack.
Simulated Attacks
Note: This is not the most accurate of the data. We recommend using the live GPS Spoofing and Jamming data if possible.
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This dataset is in support of my 3 research papers - 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part I', ' Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part II' , and 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part III'.
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This dataset is in support of my 2 research papers - 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part I' and 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part II'.
Faults and datasets can be copied to submit in fire cause investigation reports or thesis.
This dataset is a collection of data of battery and BMC faults.
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