The dataset includes the coordinates of a 2980 antenna array. 

In this dataset, we conducted a spectrum monitoring experiment in an urban environment. The helikite flies up to an altitude of 400 feet throughout the day from noon to 9 p.m. during NC State’s Packapalooza festival in August, 2022. The spectrum is swept up to 6 GHz. Every sweep takes around 1 minute, while after every 4 measurements, the 5th measurement takes close to 5 minutes due to another data collection activity running in parallel. The photo of a flying Helikite at the experiment site is shown in the dataset image.

ImgFi converts wifi channel state information into images, improving feature extraction and achieving 99.5% accuracy in human activity recognition using only three layers of convolution. In addition to the self-test dataset, three publicly available high-quality datasets, WiAR, SAR and Widar3.0, are used. WiAR collects 16 activity-reflected WiFi signals; SAR collects WiFi signals in response to 6 actions performed by 9 volunteers over 6 days, while Widar3.0 collects 6 action signals from 5 volunteers at different locations and antenna orientations.

IoT has a significant role in smart campus. LoRaWAN is an emerging technology that enables serving hundreds of IoT devices. In this dataset, we present a the data results from the LoRa communication model between the devices and the gateway and between the gateway and the processing server. In addition, we present the physical readings sensed by the LoRa devices. This dataset is very rich and can be used in many applications, such as time-series forecasting, number of people prediction, and veryfing spatial correlation algorithms.