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The ever increasing pace of IoT deployment is opening the door to concrete implementations of smart city applications, enabling the large-scale sensing and modeling of (near-)real-time digital replicas of physical processes and environments. This digital replica could serve as the basis of a decision support system, providing insights into possible optimizations of resources in a smart city scenario. In this article, we discuss an extension of a prior work, presenting a detailed proof-of-concept implementation of a Digital Twin solution for the Urban Facility Management (UFM) process. The Interactive Planning Platform for City District Adaptive Maintenance Operations (IPPODAMO) is a distributed geographical system, fed with and ingesting heterogeneous data sources originating from different urban data providers. The data are subject to continuous refinements and algorithmic processes, used to quantify and build synthetic indexes measuring the activity level inside an area of interest. IPPODAMO takes into account potential interference from other stakeholders in the urban environment, enabling the informed scheduling of operations, aimed at minimizing interference and the costs of operations.

We are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0 (I5.0) era goes a step beyond, aiming to build cross-border, sustainable, and circular value chains benefiting society as a whole. An enabler of this vision is the integration of data and AI in the industrial decision-making process, which does not exhibit yet a coordination between the Operation and Information Technology domains (OT/IT). This work proposes an architectural approach and an accompanying software prototype addressing the OT/IT convergence problem. The approach is based on a two-layered middleware solution, where each layer aims to better serve the specific differentiated requirements of the OT and IT layers. The proposal is validated in a real testbed, employing actual machine data, showing the capacity of the components to gracefully scale and serve increasing data volumes.

Joining a private Wi-Fi network is an intricate operation for end users, especially when they must type a long and complicated password in order to gain access. Moreover, it is often the case where users connect to multiple such hotspots, placed in public places visited in their daily routine, further exacerbating the issue. In this paper we present WPA-Totem: a small device that emits Wi-Fi configuration tokens, which can be received by any NFC-enabled smartphones and tablets. Moreover, our proposal is able to automatically change the WPA passphrase after a specified period of time, keeping away the freeloaders from the network. WPA-Totem is aordable, easy to deploy and compatible with all the existing WPA2-Personal protected Wi-Fi networks. A new client can connect to the access point by simply tapping the totem and this, as we measured, leads to a dramatic improvement of the user experience.

Flying ad-hoc networks are becoming a promising solution for different application scenarios involving unmanned aerial vehicles, like urban surveillance or search and rescue missions. However, such networks present various and very specific communication issues. As a consequence, there are several research studies focused on analyzing their performance via simulation. Correctly modeling mobility is crucial in this context and although many mobility models are already available to reproduce the behavior of mobile nodes in an ad-hoc network, most of these models cannot be used to reliably simulate the motion of unmanned aerial vehicles. In this article, we list the existing mobility models and provide guidance to understand whether they could be actually adopted depending on the specific flying ad-hoc network application scenarios, while discussing their advantages and disadvantages.

In this paper, we propose GeoSaW, a delay-tolerant routing protocol for Airborne Networks in Search and Rescue scenarios. The protocol exploits the geographical information of UAVs to make appropriate message forwarding decisions. More precisely, the information about the future UAV’s motion path is exploited to select the best UAV carrying the message towards the destination. Simulation results show that the proposed solution outperforms the classic DTN routing protocols in terms of several performance metrics.