Alessandra Flammini

Bio: Alessandra Flammini is an academic researcher from University of Brescia. The author has contributed to research in topics: Wireless sensor network & Synchronization. The author has an hindex of 36, co-authored 331 publications receiving 4896 citations. Previous affiliations of Alessandra Flammini include Brescia University.

Wired and wireless sensor networks for industrial applications

Abstract: Distributed architectures for industrial applications are a new opportunity to realize cost-effective, flexible, scalable and reliable systems. Direct interfacing of sensors and actuators to the industrial communication network improves the system performance, because process data and diagnostics can be simultaneously available to many systems and also shared on the Web. However, sensors, especially low-cost ones, cannot use standard communication protocols suitable for computers and PLCs. In fact, sensors typically require a cyclic, isochronous and hard real-time exchange of few data, whereas PCs and PLCs exchange a large amount of data with soft real-time constrains. Looking at the industrial communication systems, this separation is clearly visible: several fieldbuses have been designed for specific sensor application areas, whereas high-level industrial equipments use wired/wireless Ethernet and Internet technologies. Recently, traditional fieldbuses were replaced by Real-Time Ethernet protocols, which are ''extended'' versions of Ethernet that meet real-time operation requirements. Besides, real-time wireless sensor networking seems promising, as demonstrated by the growing research activities. In this paper, an overview of the state-of-art of real-time sensor networks for industrial applications is presented. Particular attention has been paid to the description of methods and instrumentation for performance measurement in this kind of architectures.

Evaluation of the IoT LoRaWAN Solution for Distributed Measurement Applications

Abstract: Internet of Things (IoT) is based on data collection, where billions of sensors sample the real world; in other words, the IoT includes a giant distributed measurement system (DMS). A question still requiring an answer is: Are the IoT technologies usable to enhance traditional measurement systems, since they have been developed for a very similar objective? In this paper, the use of a long-range (LoRa) technology, originally developed for IoT, is investigated with the aim of implementing DMSs. After the conclusion that LoRa and LoRa wide area network architectures show a good match with measurement systems, this paper focuses on the characterization of time-related performance indicators that are important for distributed systems. The experimental results show the capability of low-cost transceiver to schedule the transmission of frames with a standard uncertainty less than $3~\mu \text{s}$ ; and an acceptable long-term clock stability (Allan Deviation) of commercial available devices (nodes and packet forwarders) for application such as smart metering, smart building, and process industry.

A low-cost interface to high-value resistive sensors varying over a wide range

Abstract: This paper presents a low-cost interface for high-value resistive sensors varying over a wide range, from k/spl Omega/ to G/spl Omega/. The proposed circuit that acts as a "resistance to period converter" is suitable to be interfaced to a microcontroller or a counting device. The behavior of real electronic components that produce estimation errors, is taken into account. Experimental results obtained by the realized prototype show a good resolution and repeatability.

Using LoRa for industrial wireless networks

Abstract: The new concept of Industry 4.0 has been developed: it includes both Internet of Things (IoT) structure and the local networks that are still needed to carry out real-time tasks. However, forecasts of mass application of consumer IoT system have stimulated the development of new wireless technologies that may also be interesting for industry. In this paper, the LoRa technology is investigated for the implementation of industrial wireless networks suitable for sensors and actuators of the Industry 4.0 era. After a brief overview of LoRa and LoRaWAN, the paper deals with the discussion about using LoRa for industrial applications compared to traditional industrial wireless systems. With only very light modifications to the upper layer of LoRaWAN communication stack, a time slot channel hopping schema is possible. The experimental results show the feasibility of the proposed approach, which is compatible with requirements of soft real-time applications in process industry. In particular, proper time, frequency, and spreading factor planning may allow 6000 nodes accessed up to one minute cycle time.

Delay Estimation of Industrial IoT Applications Based on Messaging Protocols

Abstract: Information and operational technologies merge into the so-called industrial Internet of Things, which is one of the basic pillars of the Industry 4.0 paradigm. Roughly speaking, yet-to-come services will be offered in the automation scenario by industrial devices having an internet connection for sharing data in the cloud. Currently, most efforts are in the development of protocols able to ensure horizontal interoperability among heterogeneous applications. Consequently, poor attention is devoted to time-related performance. In this paper, a new, full software, platform-independent approach is proposed for experimentally evaluating the delay in transferring information across local and intercontinental routes by applications leveraging on messaging middleware. The application is realized using the node-RED web-based framework, due to its availability on different platforms; the widely accepted message queue telemetry transport protocol has been chosen thanks to its low overhead and complexity. For sake of completeness, five different, private and public, brokers are used. The adopted industrial-grade hardware, complemented by global positioning system time reference, permits an overall synchronization and timestamping accuracy of a few milliseconds. The vast measurement campaign highlighted that, generally, quality of service (QoS) type 1 offers low end-to-end delay (average value less than 0.5 s) with reduced variability (0.1 s). However, the maximum end-to-end one-way delay ranges from 1 s for QoS 0 to less than 1.5 s for fully acknowledged QoS 2.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Wearable biosensors for healthcare monitoring.

Abstract: Wearable biosensors are garnering substantial interest due to their potential to provide continuous, real-time physiological information via dynamic, noninvasive measurements of biochemical markers in biofluids, such as sweat, tears, saliva and interstitial fluid. Recent developments have focused on electrochemical and optical biosensors, together with advances in the noninvasive monitoring of biomarkers including metabolites, bacteria and hormones. A combination of multiplexed biosensing, microfluidic sampling and transport systems have been integrated, miniaturized and combined with flexible materials for improved wearability and ease of operation. Although wearable biosensors hold promise, a better understanding of the correlations between analyte concentrations in the blood and noninvasive biofluids is needed to improve reliability. An expanded set of on-body bioaffinity assays and more sensing strategies are needed to make more biomarkers accessible to monitoring. Large-cohort validation studies of wearable biosensor performance will be needed to underpin clinical acceptance. Accurate and reliable real-time sensing of physiological information using wearable biosensor technologies would have a broad impact on our daily lives.

Industrial Internet of Things: Challenges, Opportunities, and Directions

Abstract: Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.