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.

Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, call for Quality of Service (QoS) management to guarantee/control performance indicators, even in presence of many sources of “stochastic noise” in real deployment environments, from scarcely available bandwidth in a time window to concurrent usage of virtualized processing resources. This paper proposes a novel IoT-oriented middleware that i) considers and coordinates together different aspects of QoS monitoring, control, and management for different kinds of virtualized resources (from networking to processing) in a holistic way, and ii) specifically targets deployment environments where edge cloud resources are employed to enable the Serverless paradigm in the cloud continuum. The reported experimental results show how it is possible to achieve the desired QoS differentiation by coordinating heterogeneous mechanisms and technologies already available in the market. This demonstrates the feasibility of effective QoS-aware management of virtualized resources in the cloud-to-things continuum when considering a Serverless provisioning scenario, which is completely original in the related literature to the best of our knowledge.

The continuous evolution of IT (information technology) technologies is radically transforming many technical areas and social aspects, also reshaping the way we behave and looking for entertainment and leisure services. In that context, tourism experiences request to enhance the level of user involvement and integration and to create an ever more personalized and connected experience, by leveraging on the differentiated tourist services and information locally present in the territory, by pushing active participation of customers, and by taking advantage of the ever-increasing presence of sensors and IoT (Internet of Things) devices deployed in many realities. However, the deep fragmentation of services and technologies adopted in tourism context characterizes the whole information provided also by customer sensing and IoTs (Internet of Things) heterogeneity and deep clashes with an effective organization of smart tourism. This article presents APERTO5.0 (an Architecture for Personalization and Elaboration of services and data to Reshape Tourism Offers 5.0), an innovative architecture aiming at a whole integration and deep facilitation of tourism service and information organization and blending, to enable the re-provisioning of novel services as advanced aggregates or re-elaborated ones. The proposed solution will demonstrate its effectiveness in the context of Smart Tourism by choosing the real use case of the “Francigena way” (a pilgrim historical path), the Italian part.

Long-range and low-power networks play a crucial role in the development of smart cities. However, the centralized and vertically integrated Internet of Things (IoT) model, where municipalities or private entities deploy and manage devices effectively retaining ownership of the data, presents significant technological and operational barriers that have so far hindered the capillary deployment of the technology. To overcome these limitations, we propose an original bottom-up deployment model that decentralizes data and network ownership and reduces management and operational barriers. Community-driven LoRa networks Urban sensing Empowered by Smart homes (CLUES) advocates for a participatory and decentralized sensor network through the integration of a smart gateway into citizen’s smart homes. Crowd-sensed data captured by Smart Home Gateways (SHG) allows us to power local-scoped digital representations of sensors, augmenting their capabilities with data and services from edge devices. Gateways can participate in municipal networks and share sensed data with institutions and companies, fostering a cost-effective approach to the construction of city ecosystems. In particular, our proposal opens up new deployment and management models for low-power networks, providing better coverage and enabling more dense, scalable, and energy-efficient deployments. We showcase the effectiveness of our approach through a large-scale evaluation of a simulated deployment of the proposal and provide the community with an open-source implementation of the SHG.

The urban environment is a complex ecosystem that undergoes constant change, and Digital Twin (DT) technology can help to reliably track and map the dynamics through the use of real-time data, constantly evolving its representation along with the physical counterpart. To this end, Urban Digital Twins (UDTs) must be capable of ingesting a wide range of heterogeneous data, sourced by different (un)trusted actors, embodying different semantic and syntactic representations. This translates into having dedicated and tailored data processing pipelines, making up for a complex and difficult-to-maintain back-end logic. In addition, issues of interoperability, reliability, and trust arise when data need to be accessed and shared between digital twins operated by different providers. In this work, we advocate for a multifaceted interoperability model using Minimum Interoperability Models (MIMs) as an abstraction for standardized and secure data access and serverless technology as a processing layer interfacing with the various components and systems. Using a serverless architecture and cloud-based services, the proposal aims to offer scalability, flexibility, and cost effectiveness, enabling UDT developers to quickly build and deploy applications that can take advantage of the vast amounts of data generated in these environments. To validate our approach, we conduct a preliminary evaluation of our proposal through a series of experiments conducted in a real deployment environment.

Distributed ledger technologies (DLT) can enhance trust and auditability in the Internet of Things (IoT). Among them, IOTA has been specifically designed to support machine-to-machine interactions and IoT data anchoring through scalable DLT architectures. However, their integration with Low-Power Wide-Area Networks (LPWANs) remains limited due to device constraints, strict timing requirements, and the operational costs of on-chain transactions. The transition from the fee-less Stardust to the fee-based IOTA Rebased model introduces explicit transaction costs, questioning the viability of continuous IoT data anchoring. IOTA provides a suitable platform to examine the challenges of integrating distributed ledger technologies with LPWAN-based IoT systems. Its transition to a fee-based execution model raises important questions regarding cost predictability and performance in continuous data anchoring scenarios, particularly under the constraints of resource-limited and latency-sensitive environments. This article investigates the practicality of the execution and payment model introduced by IOTA Rebased for IoT scenarios requiring continuous data notarization. We provide an empirical evaluation of continuous IoT data notarization on the public IOTA Rebased Mainnet and characterize the performance implications on edge-oriented deployments, including resource-constrained and resource-rich devices. We implement a notarization oracle that ingests LoRaWAN uplinks from The Things Network (TTN), canonicalizes payloads, generates SHA-256 commitments, and records them on-chain through reusable notarization objects. The oracle enables continuous anchoring of IoT telemetry while minimizing transaction overhead through object reuse. Two 24-h experimental campaigns compare a notarization oracle on resource-constrained and resource-rich hardware under periodic workloads. Results show consistent steady-state gas consumption for UPDATE operations, indicating that object reuse enables stable on-chain cost behavior in IOTA Rebased regardless of the deployment platform. From a performance perspective, both environments achieve stable execution; however, the resource-constrained edge deployment exhibits higher median and tail latency, alongside tighter memory margins compared to the resource-rich centralized baseline. These findings confirm the feasibility of deploying notarization services on constrained edge infrastructure under the new fee-based model.