Energy-efficient wireless sensor networks via scheduling algorithm and radio Wake-up technology

One of the most important requirements for wireless sensor networks (WSNs) is the energy efficiency, since sensors are usually fed by a battery that cannot be replaced or recharged. Radio wake-up - the technology that lets a sensor completely turn off and be reactivated by converting the electromagnetic field of radio waves into energy - is now one of the most emergent strategies in the design of wireless sensor networks. This work presents Scheduled on Demand Radio WakeUp (SORW), a flexible scheduler designed for a wireless sensor network where duty cycling strategy and radio wake-up technology are combined in order to optimize the network lifetime. In particular, it tries to keep sensors sleeping as much as possible, still guaranteeing a minimum number of detections per unit of time. Performances of SORW are provided through the use of OMNet++ simulator and compared to results obtained by other basic approaches. Results show that with SORW it is possible to reach a theoretical lifetime of several years, compared to simpler schedulers that only reach days of activity of the network

Managing Device and Platform Heterogeneity through the Web of Things

The chaotic growth of the IoT determined a fragmented landscape with a huge number of devices, technologies, and platforms available on the market, and consequential issues of interoperability on many system deployments. The Web of Things (WoT) architecture recently proposed by the W3C consortium constitutes a novel solution to enable interoperability across IoT Platforms and application domains. At the same time, in order to see an effective improvement, a wide adoption of the W3C WoT solutions from the academic and industrial communities is required; this translates into the need of accurate and complete support tools to ease the deployment of W3C WoT applications, as well as reference guidelines about how to enable the WoT on top of existing IoT scenarios and how to deploy WoT scenarios from scratch. In this thesis, we bring three main contributions for filling such gap: (1) we introduce the WoT Store, a novel platform for managing and easing the deployment of Things and applications on the W3C WoT, and additional strategies for bringing old legacy IoT systems into the WoT. The WoT Store allows the dynamic discovery of the resources available in the environment, i.e. the Things, and to interact with each of them through a dashboard by visualizing their properties, executing commands, or observing the notifications produced. (2) We map three different IoT scenarios to WoT scenarios: a generic heterogeneous environmental monitoring scenario, a structural health monitoring scenario and an Industry4.0 scenario. (3) We make proposals to improve both the W3C standard and the node-wot software stack design: in the first case, new vocabularies are needed in order to handle particular protocols employed in industrial scenarios, while in the second case we present some contributions required for the dynamic instantiation and the migration of Web Things and WoT services in a cloud-to-edge continuum environment

Indici di Integrazione Degli Immigrati in Italia, IX Rapporto

This report analyses how attractive Italian provinces and districts are for migrants and also how they are integrated in each area

Blockchain and Web of Things for Structural Health Monitoring Applications: A Proof of Concept

Interoperable and secure data management techniques are fundamental for most of large-scale Structural Health Monitoring (SHM) systems. Indeed, given the relevance of SHM critical measurements, data integrity must be protected against tampering or falsifications. In this paper, we propose a four-layer SHM architecture that allows to build an effective data pipeline from sensors to consumer applications, passing through the cloud. The architecture is built on top of the MODRON platform and exploits the recent advances of the W3C Web of Things (WoT) standard for interoperability. We then discuss how third-party services can take benefit of the W3C WoT architecture to retrieve the SHM critical data and to publish them on the Ethereum Blockchain through an SHM-specific Smart Contract, for data protection and traceability purposes. We test the effectiveness of the Smart Contract implementation in terms of latency and costs under simulated workload

Relativistic Digital Twin: Bringing the IoT to the Future

Complex IoT ecosystems often require the usage of Digital Twins (DTs) of their physical assets in order to perform predictive analytics and simulate what-if scenarios. DTs are able to replicate IoT devices and adapt over time to their behavioral changes. However, DTs in IoT are typically tailored to a specific use case, without the possibility to seamlessly adapt to different scenarios. Further, the fragmentation of IoT poses additional challenges on how to deploy DTs in heterogeneous scenarios characterized by the usage of multiple data formats and IoT network protocols. In this paper, we propose the Relativistic Digital Twin (RDT) framework, through which we automatically generate general-purpose DTs of IoT entities and tune their behavioral models over time by constantly observing their real counterparts. The framework relies on the object representation via the Web of Things (WoT), to offer a standardized interface to each of the IoT devices as well as to their DTs. To this purpose, we extended the W3C WoT standard in order to encompass the concept of behavioral model and define it in the Thing Description (TD) through a new vocabulary. Finally, we evaluated the RDT framework over two disjoint use cases to assess its correctness and learning performance, i.e., the DT of a simulated smart home scenario with the capability of forecasting the indoor temperature, and the DT of a real-world drone with the capability of forecasting its trajectory in an outdoor scenario.Comment: 17 pages, 10 figures, 4 tables, 6 listing

An IoT Toolchain Architecture for Planning, Running and Managing a Complete Condition Monitoring Scenario

Condition Monitoring (CM) is an extremely critical application of the Internet of Things (IoT) within Industry 4.0 and Smart City scenarios, especially following the recent energy crisis. CM aims to monitor the status of a physical appliance over time and in real time in order to react promptly when anomalies are detected, as well as perform predictive maintenance tasks. Current deployments suffer from both interoperability and management issues within their engineering process at all phases – from their design to their deployment, to their management –, often requiring human intervention. Furthermore, the fragmentation of the IoT landscape and the heterogeneity of IoT solutions hinder a seamless onboarding process of legacy devices and systems. In this paper, we tackle these problems by first proposing an architecture for CM based on both abstraction layers and toolchains, i.e., automated pipelines of engineering tools aimed at supporting the engineering process. In particular, we introduce four different toolchains, each of them dedicated to a well-defined task (e.g., energy monitoring). This orthogonal separation of concerns aims to simplify both the understanding of a complex ecosystem and the accomplishment of independent tasks. We then illustrate our implementation of a complete CM system that follows said architecture as a real Structural Health Monitoring (SHM) pilot of the Arrowhead Tools project, by describing in detail every single tool that we developed. We finally show how our pilot achieves the main objectives of the project: the reduction of engineering costs, the integration of legacy systems, and the interoperability with IoT frameworks

From Heterogeneous Sensor Networks to Integrated Software Services: Design and Implementation of a Semantic Architecture for the Internet of Things at ARCES@UNIBO

The Internet of Things (IoTs) is growing fast both in terms of number of devices connected and of complexity of deployments and applications. Several research studies an- alyzing the economical impact of the IoT worldwide identify the interoperability as one of the main boosting factor for its growth, thanks to the possibility to unlock novel commercial opportunities derived from the integration of heterogeneous systems which are currently not interconnected. However, at present, interoperability constitutes a relevant practical issue on any IoT deployments that is composed of sensor platforms mapped on different wireless technologies, network protocols or data formats. The paper addresses such issue, and investigates how to achieve effective data interoperability and data reuse on complex IoT deployments, where multiple users/applications need to consume sensor data produced by heterogeneous sensor networks. We propose a generic three-tier IoT architecture, which decouples the sensor data producers from the sensor data consumers, thanks to the intermediation of a semantic broker which is in charge of translating the sensor data into a shared ontology, and of providing publish-subscribe facilities to the producers/consumers. Then, we describe the real-world implementation of such architecture devised at the Advanced Research Center on Electronic System (ARCES) of the University of Bologna. The actual system collects the data produced by three different sensor networks, integrates them through a SPARQL Event Processing Architecture (SEPA), and supports two front- end applications for the data access, i.e. a web dashboard and an Amazon Alexa voice service

Midi networking: Metodologie di interconnessione di strumenti musicali tramite reti fisiche e virtuali

Il lavoro che si presenta ha la principale funzione di proporre un metodo di interconnessione di strumenti musicali digitali che utilizzi i più comuni protocolli e strumenti hardware di rete. Nell'ottica di Internet of Things, si vuole rendere MIDI un sotto-protocollo di rete