| 1. |
- Almeida, N. C., et al.
(författare)
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Proposal of a Hybrid LoRa Mesh / LoRaWAN Network
- 2020
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728148922 ; , s. 702-707
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Konferensbidrag (refereegranskat)abstract
- There is a recent interest in the deployment of Low Power Wide Area Networks (LPWANs), such as LoRaWAN, to support Internet of Things (IoT) applications. Even though the main advantage of these LPWANs are the long rage communication, the challenge of providing seamless and shadow area coverage still remains. This paper presents a proposal of a hybrid LoRa Mesh/LoRaWAN network to cope with this challenge. In this proposal, a mesh network of LoRa nodes are connected to a Proxy node that works as a mesh coordinator and is also connected to the LoRaWAN network. The advantage of this topology is the improvement of the communication coverage in shadow areas where a regular LoRaWAN node cannot be reachable in cases of obstacles or topography. The development of the LoRa Mesh network as well as the routing mechanism are presented and verified with experimental results. Finally, the integration of the LoRa Mesh with the LoRaWAN networks is discussed and a proposal is presented. © 2020 IEEE.
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| 2. |
- Pasetti, M., et al.
(författare)
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On the Use of Synchronized LoRaWAN for the Coordination of Distributed Energy Resources in Smart Grids
- 2019
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9788887237450
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Konferensbidrag (refereegranskat)abstract
- The recent advances in Information and Communication Technology (ICT) are laying down the foundations of future energy systems. The growing availability of reliable and cost-effective ICT solutions are indeed offering the opportunity for the implementation of advanced monitoring and control functions over Distributed Energy Resources (DERs), thus fostering the transition towards decentralized and decarbonized energy systems. The integration of ICT in electrical equipment (such as power converters, metering devices, and protections) is essential for the monitoring and the coordinated control of heterogeneous energy resources, particularly in intermittent and distributed scenarios. Nevertheless, the implementation of such control approaches relies, in the end, on the availability of proper communication infrastructures. The adoption of wired infrastructures (such as field-bus, ethernet, or fiber optic systems) may however imply high installation costs, particularly for complex end-users' systems. To cope with this issue, in this study the use of a wireless network based on the LoRaWAntechnology is proposed to implement the monitoring and the coordinated control of dispersed DERs. A proper communication architecture is proposed and discussed in terms of the required coverage range and latency. Finally, a scalability analysis is also presented, which aims at evaluating the number of devices that can be supervised by a single LoRaWAngateway, by considering the expected data throughput, and the duty cycle limitations. © 2019 AEIT.
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| 3. |
- Alves, H. B. M., et al.
(författare)
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Introducing a survey methodology for assessing LoRaWAN coverage in Smart Campus scenarios
- 2020
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728148922 ; , s. 708-712
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Konferensbidrag (refereegranskat)abstract
- The LoRa is a Low Power Wide Area Network (LPWAN) technology. It has been proposed as a viable wireless connection method for the implementation of the Internet of Things (IoT), thanks to its wide coverage, low complexity and low energy consumption. Several studies ave been carried out about real coverage performance. In this article, a new test methodology for the experimental evaluation of LoRaWAN coverage within a smart campus is presented. The new approach consists in the definition of devices, method and procedures. The architecture of the mobile node is outlined. The survey procedure is based on a mapping phase, necessary to highlight the LoRaWAN coverage in the test area. Finally, a use case is described in the article: it is not intended for evaluating a specific implementation, but for assessing the suitability of the proposed methodology. The use case results demonstrate the effectiveness of the survey methodology in a real smart campus. © 2020 IEEE.
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| 4. |
- Barile, G., et al.
(författare)
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Automatic Differential Capacitive Sensing by Means of Linear Interface
- 2020
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Ingår i: Lect. Notes Electr. Eng.. - Cham : Springer. - 9783030375577 ; , s. 131-135
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Konferensbidrag (refereegranskat)abstract
- In this work we present the development of an integrated CMOS analog interface able to convert differential capacitive sensors variations into a DC voltage. The presented circuit is based on autobalancing bridge techniques improving its performances through the linearization of the input/output characteristic and the achievement of the full-range sensor variations capability. Comparison between theoretical and measured interface static behaviour results are reported. © 2020, Springer Nature Switzerland AG.
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| 5. |
- Bonafini, F., et al.
(författare)
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Cluster of IoT Sensors for Smart Cities : Impact of the Communication Infrastructure over Computational Performance
- 2019
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538677131
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Konferensbidrag (refereegranskat)abstract
- The Smart City (SC) paradigm is based on the integration of Information and Communication Technology (ICT) into the urban asset, for the optimal management of the energies and resources. The Internet of Thing (IoT) technology seems the proper solution to achieve this target, thanks to its capability to abstract the object in the real world. The deployment of IoT devices at different level in urban infrastructures is causing the presence of thousands of intelligent devices, large part of them with unused computational capabilities. Such devices could be integrated in a cluster in order to share the unused resources with other devices with limited computational resources. The use of a cluster of IoT Sensors has several benefits, including, but not limited to: high availability, sharing of computational resources, reduced response time with the respect of centralized cloud computing solution. The main bottleneck of this approach is represented by the communication infrastructure, typically based on wireless connection and, thus with a limited available bandwidth. The aim of the work related to this paper is to analyze the impact the communication infrastructure has on computational performance of a cluster of IoT sensors. An experimental set-up for the characterization of the performance of a cluster of low-cost off-the-shelf devices has been described. The experimental validation highlighted as the network infrastructure is loaded only during the data transfer and the maximum network load, with a cluster of ten IoT nodes is approximately 2 Mb/s with the considered benchmark. © 2019 IEEE.
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| 6. |
- Bonafini, F., et al.
(författare)
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Evaluating indoor and outdoor localization services for LoRaWAN in Smart City applications
- 2019
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728104294 ; , s. 300-305
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Konferensbidrag (refereegranskat)abstract
- Nowadays, wireless technologies penetrate all aspects of our lives. 'Internet of Things' (IoT) and 'Location- Based Services' are the pillars of Smart City concept. The IoT smart objects surrounding us are an integral part of the Internet, thanks to their computational and communication capabilities. In such applications, location information can be exploited in all the layers of the stack, from the application level (e.g., to correctly interpret measurements from sensor nodes deployed on the field), down to the physical level (e.g., for sensing coverage). One of the most viable solutions for Smart City wireless connectivity seems to be the use of long-range, low-power and low-throughput low-power wide area networks (LPWANs). In this work, the authors devise the jointly use of LPWANs with widely-diffused and well-accepted localization techniques, as the Global Positioning Systems (GPS, outdoor) and real-time location systems (RTLS, indoor), for Smart Campus applications. In particular, a LoRaWAN node equipped with both GPS and Ultra Wide Bandbased UWB-RTLS has been developed and tested in real-world scenarios. Experimental results demonstrate the feasibility of the proposed approach; in particular, location errors are in the order of few tens of meters for GPS and in the order of few tens of centimeters for UWB. © 2019 IEEE.
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| 7. |
- Carvalho, D. F., et al.
(författare)
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Architecture for the interconnection of prototypical medical instrument via cloud services
- 2019
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Ingår i: Proceedings. - 9781538634608
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Konferensbidrag (refereegranskat)abstract
- Medical cyber-physical systems (MCPS) have been appeared as a possible approach for detecting and mitigating human errors. In this context, a MCPS in which medical and non-medical devices are connected could promptly detect potential risky or wrong procedures that deviate from standardized approaches. In this work, such a paradigm has been expanded to prototypical diagnostic devices. A distributed platform of such instruments is proposed in order to avoid misdiagnosis: diagnostic instrument send data to a message-oriented middleware, thus allowing technicians and doctors to remotely access test-related information for further processing and for creating an historical database. A Broker has been used for collecting data and distribute them to cloud database and to users. Two of the most diffused protocols, i.e., MQTT and AMQP, have been considered. An experimental setup has been developed to verify performance; time-related metrics confirm that the proposed approach has an end-to-end delay on few hundreds of milliseconds even for geographical scale networks. © 2019 IEEE.
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| 8. |
- Crema, C., et al.
(författare)
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Characterization of a wearable system for automatic supervision of fitness exercises
- 2019
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Ingår i: Measurement: Journal of the International Measurement Confederation. - : Elsevier BV. - 0263-2241. ; 147
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Tidskriftsartikel (refereegranskat)abstract
- It is widely known that physical activity is an effective tool for preventing several diseases. However, unsupervised training may lead to poor execution quality, resulting in ineffective training, or even injuries in worst cases. Automatic tracking and quantification of exercise efforts by means of wearables could be a way to monitor the execution correctness. As a positive side effect, these devices help in motivating people, increasing the quantity of physical exercises of users and thus improving health conditions as well. Unfortunately, despite the availability of some commercial devices, their performance and effectiveness are not documented. This work proposes a new solution that exploits machine learning (ML) techniques (in particular Linear Discriminant Analysis, LDA) for analyzing data coming from wearable Inertial Measurement Units (IMUs). Efforts have been done in reducing the computational requirements, in order to be compatible with constraints in perspective of embedded implementation. The experimental campaign carried out to measure the performance showed an average accuracy, recall and precision on the order of 97%, 93% and 90%, respectively. © 2019 Elsevier Ltd
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| 9. |
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| 10. |
- Depari, A., et al.
(författare)
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Lightweight Machine Learning-Based Approach for Supervision of Fitness Workout
- 2019
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538677131
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Konferensbidrag (refereegranskat)abstract
- It is widely known that physical activity helps preventing several diseases. However, unsupervised training often results in low exercise quality, ineffective training, and, in worst cases, injuries. Automatic tracking and quantification of exercises by means of wearable devices could be an effective mean for the monitoring of exercise correctness. As a consequence, such devices could help motivating people, thus improving the quantity of performed physical exercise, with positive effects on users' health conditions. However, despite the availability of several commercial devices, the performance and effectiveness are not well documented. This work proposes a new solution for fitness workout supervision exploiting machine learning techniques, in particular Linear Discriminant Analysis for analyzing data coming from wearable Inertial Measurement Units. Efforts have been done in order to reduce the computational requirements, thus assuring compatibility in perspective of embedded implementation. The experimental tests carried out to assess the proposed approach performance showed an accuracy in exercise detection over 93% and error in exercise counting less than 6%. © 2019 IEEE.
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