Nowadays, we are observing a rapid development of UAV-based monitoring systems, which are faced with more and more new tasks, such as high temporal resolution and high spatial resolution of measurements, or Artificial Intelligence on board. This paper presents the open universal framework intended for fast prototyping or building a short series of specialized flying monitoring systems able to work in urban and industrial areas. The proposed framework combines mobility of UAV with IoT measurements and full-stack WebRTC communications. WebRTC offers simultaneous transmission of both a real-time video stream and the flow of data coming from sensors, and ensures a kind of protection of data flow, which leads to preserving its near-real-time character and enables contextual communication. Addition of the AI accelerator hardware makes this system AI-ready, i.e., the IoT communication hub, which is the air component of our system, is able to perform tasks of AI-supported computing. The exemplary prototype of this system was evaluated in terms of the ability to work with fast-response sensors, the ability to work with high temporal and high spatial resolutions, video information in poor visibility conditions and AI-readiness. Results show that prototypes based on the proposed framework are able to meet the challenges of monitoring systems in smart cities and industrial areas.

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In this paper we propose an extension to RSVP protocol, based on dynamic resource reservations, which allows for better coexistence of HD video transmission and elastic traffic (e.g. bulk data transfer). These extensions have been evaluated in two different domains, both in the Quality of Experience (QoE) domain and in the Quality of Service (QoS) domain. Experiments carried out in an emulated multi-node heterogeneous network show that the proposed extensions are profitable, especially in the network domain. They are able to assure a better quality of service for elastic traffic than typical RSVP reservations and offer the same QoS for HD video transmission as well-dimensioned typical RSVP. Analysis in QoE domain confirms that proposed extensions assure a video transmission quality unnoticeably worse than the one possible with RSVP (with no extensions).

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Thanks to IoT, Internet access, and low-cost sensors, it has become possible to increase the number of weather measuring points; hence, the density of the deployment of sources that provide weather data for the needs of large recipients, for example, weather web services or smart city management systems, has also increased. This paper presents a flying weather station that carries out measurements of two weather factors that are typically included in weather stations (ambient temperature and relative humidity), an often included weather factor (atmospheric pressure), and a rarely included one (ultraviolet index). In our solution, the measurements are supplemented with a visual observation of present weather phenomena. The flying weather station is built on a UAV and WebRTC-based universal platform proposed in our previous paper. The complete, fully operational flying weather station was evaluated in field studies. Experiments were conducted during a 6-month period on days having noticeably different weather conditions. Results show that weather data coming from the flying weather station were equal (with a good approximation) to weather data obtained from the reference weather station. When compared to the weather stations described in the literature (both stationary weather stations and mobile ones), the proposed solution achieved better accuracy than the other weather stations based on low-cost sensors.