The increasing pervasiveness of software-intensive systems requires involving domain experts more directly in technological development. Visual models, expressed in semi-formal notations, can act as shared artefacts that support communication and collaboration between developers and domain experts. However, modelling with semi-formal notations can be challenging for novice modellers. This study presents an AI-infused, web-based modelling tool designed to support users in formalising domain knowledge without requiring advanced modelling skills. The tool features a block-based, domain-specific language that automatically transforms user-generated structures into semi-formal diagrams. AI-based functionalities include a diagram reader, contextual hints, natural-language instructions, and interaction logging. We evaluated the tool through a Wizard of Oz experiment with agronomists in digital agriculture, where participants completed an exploratory modelling task while interacting with AI assistance. Results reveal three key design implications: (i) adaptive AI support accommodating diverse modelling strategies, (ii) concise, actionable guidance delivered at moments of difficulty, and (iii) practice-oriented assistance that preserves user agency and supports learning-by-doing.

This work describes the ongoing design and development of the METRIQA platform, hosting the Italian agrifood data space.Both are key components that the Italian National Research Centre for Agricultural Technologies is putting forward in its activities.We present a high-level description of the platform, which is designed to provide web-like access to digital resources and services following an approach called Web of Agri-Food, to support the digital transformation of the sector in Italy.To show its potential, we also present a real case study demonstrating both the benefits and impacts of the proposed architecture, connecting stakeholders and authorities at different levels.

This contribution presents ModeLLer, a prototype of a web tool for system modelling based on a block-based visual editor. The aim of ModeLLer is to enable collaborative environments in requirements elicitation, allowing end-users to create UML class diagrams without any knowledge of the (semi-)formal UML notation.

The domain of rural areas, including rural communities, agriculture, and forestry, is going through a process of deep digital transformation. Digitalisation can have positive impacts on sustainability in terms of greater environmental control, and community prosperity. At the same time, it can also have disruptive effects, with the marginalisation of actors that cannot cope with the change. When developing a novel system for rural areas, requirements engineers should carefully consider the specific socio-economic characteristics of the domain, so that potential positive effects can be maximised, while mitigating negative impacts. The goal of this paper is to support requirements engineers with a reference catalogue of drivers, barriers and potential impacts associated to the introduction of novel ICT solutions in rural areas. To this end, we interview 30 cross-disciplinary experts in digitalisation of rural areas, and we analyse the transcripts to identify common themes. According to the experts, main drivers are economic, with the possibility of reducing costs, and regulatory, as institutions push for more precise tracing and monitoring of production; barriers are the limited connectivity, but also distrust towards technology and other socio-cultural aspects; positive impacts are socio-economic (e.g., reduction of manual labour, greater productivity), while negative ones include potential dependency from technology, with loss of hands-on expertise, and marginalisation of certain actors (e.g., small farms, subjects with limited education). This paper contributes to the literature with a domain-specific catalogue that characterises digitalisation in rural areas. The catalogue can be used as a reference baseline for requirements elicitation endeavours in rural areas, to support domain analysis prior to the development of novel solutions, as well as fit-gap analysis for the adaptation of existing technologies.

Providing reliable and efficient connectivity for maritime systems is a key objective to enable new services and to offer anytime-anywhere communication solutions to vessels operating in remote areas (e.g. oceans). Such a task has recently become quite compelling because of the increasing maritime traffic, which should be supported by an information distribution infrastructure in order to guarantee efficient data communication among vessels and control centres on land. To this end, satellites are the perfect candidates for achieving such an objective. This paper focuses on the case of messaging from moving vessels to fixed control centres on land by means of advanced channel random access schemes exploiting time diversity. In more detail, the paper extends an existing theoretical framework to evaluate the packet loss probability in Framed Slotted ALOHA systems by delving into the probability distribution of both colliding users within a frame and their replicas in time slots. The theoretical framework is validated through simulations campaigns, showing a good match between analytical and simulated results.

This work describes a real testbed for enabling Unmanned Aerial Vehicles (UAVs)-to-ground real-time video streaming. The aim is in providing a video feed to the pilot on the ground for Beyond Visual Line of Sight (BVLoS) operations exploiting cellular networks in urban/suburban areas. Towards this aim, multipath communications are used in a multi-operator setup to counteract the intermittent network coverage in urban and suburban areas. The main requirements are low latency and a continuous video stream of reasonable quality. We rely on both upper-layer Forward Error Correction (FEC) techniques and link diversity, so to increase the probability of fluid video playback with acceptable quality. We report per-link statistics, collected during field trials, of three different cellular operators, to analyse the impact of using a set of physical links as a single logical one on an RTP-based video streaming. In our tests, such a setup has provided a good level of performance.

This work analyses the use of the WebRTC framework on resource-constrained platforms. WebRTC is a consolidated solution for real-time video streaming, and it is an appealing solution in a wide range of application scenarios. We focus our attention on those in which power consumption, size and weight are of paramount importance because of size, weight and power requirements, such as the use case of unmanned aerial vehicles delivering real-time video streams over WebRTC to peers on the ground. The testbed described in this work shows that the power consumption can be reduced by changing WebRTC default settings while maintaining comparable video quality.

Nowadays, Machine-to-Machine and Internet of Things traffic sources puts the terrestrial networks under great pressure. While 5G is still on its way, satellites are used to deliver a fraction of such an enormous traffic rate. In this work, we investigate the use of the Constrained Application Protocol (CoAP) to reliably deliver Machine-to-Machine and Internet of Things traffic in a push fashion, which also implements a Selective Repeat Automatic Repeat reQuest and a sender-based variant of the TCP Friendly Rate Control protocol. We aim at providing an analytical model to evaluate the working point of the system in non-saturated conditions as a function of the MAC parameters in use, when such a closed-loop congestion control mechanism is in use over a random access satellite channel. The proposed analytical model is then validated against simulation results, showing a good precision.

Nowadays, Machine-to-Machine (M2M) and Internet of Things (IoT) traffic rate is increasing at a fast pace. The use of satellites is expected to play a large role in delivering such a traffic. In this work, we investigate the use of two of the most common M2M/IoT protocols stacks on a satellite Random Access (RA) channel, based on DVB-RCS2 standard. The metric under consideration is the completion time, in order to identify the protocol stack that can provide the best performance level.

Application of random access schemes in the return link of satellite systems shows appealing advantages over demand assignment multiple access (DAMA) especially in case of bursty traffic (e.g., M2M). The interactions of TCP with random access has been however only marginally explored by the scientific community, thus limiting the appeal of random access. This paper attempts to bridge this gap, by providing insights into the performance of TCP-based services running on top of DVB-S2/RCS2 satellite networks implementing Contention Resolution Diversity Slotted Aloha (CRDSA) as random access scheme. A special attention has been also dedicated to TCP modeling, since classical TCP throughput formulations fail in the proposed scenario, whereby a simple but effective enhancement is proposed in this paper.

In this work, we discuss the two-ray radio propagation model when an UAV acts as a mobile node belonging to a ground wireless sensor network. Currently, UAVs are attracting attention in the market and in the research field, thus more accurate radio propagation models are needed to properly estimate

A Selective Dropping Congestion Control (SDCC) algorithm is proposed in this work, for wireless multimedia sensor networks based on scalable multimedia encoding. SDCC, which has been designed by means of linear discrete time control theory arguments, can be applied in a fully distributed way. It periodically evaluates at each node the amount of data to drop, in order to control the level of the transmission queue, and then selects the packets to discard based on their relevance to the image quality. SDCC effectiveness has been evaluated with reference to a video-surveillance problem in several scenarios, using the Castalia simulator. Results have shown that SDCC is able to significantly improve the network performance in terms of image delivery ratio and delay.