| 1. |
- de Freitas, Edison Pignaton, et al.
(author)
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Enhanced Wireless Sensor Network Setup Strategy Supported by Intelligent Software Agents
- 2010
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In: Sensors 2010 Hawaii. - Piscataway, N.J. : IEEE Press. - 9781424481682 ; , s. 813-816
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Conference paper (peer-reviewed)abstract
- A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the selection of appropriate nodes to perform the different tasks required to the missions' accomplishment and may be thus characterized as an instance of the task and resource allocation problem. Traditional approaches consider pre-planned strategies, which are not flexible to deal with changes in the network and environment operating conditions. This paper presents an enhanced agent-oriented strategy, which consists of a usage of mobile intelligent agents to disseminate missions and nodes' information over the network, as well as stationary software agents installed in the sensor nodes to provide advanced reasoning apparatus for decision making purposes. The proposed enhancement complements the original agent-based approach with robustness features required to overcome extreme adverse conditions in which an ordinary WSN presents poor results. Results from simulations provide evidences of the efficiency of the complete enhanced approach.
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| 2. |
- Emygdio de Melo, Carlos Felipe, et al.
(author)
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UAVouch : A Secure Identity and Location Validation Scheme for UAV-Networks
- 2021
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In: IEEE Access. - Piscataway : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 9, s. 82930-82946
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Journal article (peer-reviewed)abstract
- Emerging surveillance applications of UAV teams rely on secure communication to exchange information, coordinate their movements, and fulfill mission objectives. Protecting the network by identifying malicious nodes that are trying to disturb the system is an important task, particularly in the military domain. This paper presents the design and evaluation of UAVouch, an identity and location validation scheme that combines a public-key based authentication mechanism with a movement plausibility check for groups of UAVs. The key idea of UAVouch is to supplement the authentication mechanism by periodically checking the plausibility of the locations of neighboring UAVs, allowing the detection of intruders that are unable to follow expected trajectories. The proposed solution was evaluated in a simulated military surveillance scenario in which it detected malicious nodes’ position falsification attacks with an average accuracy of above 85%. © Copyright 2021 IEEE
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| 3. |
- Marinho, Marco A. M., et al.
(author)
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Array interpolation based on multivariate adaptive regression splines
- 2016
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In: 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal.
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| 4. |
- Oss Boll, Heloísa, et al.
(author)
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Graph neural networks for clinical risk prediction based on electronic health records : A survey
- 2024
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In: Journal of Biomedical Informatics. - Maryland Heights, MO : Academic Press. - 1532-0464 .- 1532-0480. ; 151
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Research review (peer-reviewed)abstract
- Objective: This study aims to comprehensively review the use of graph neural networks (GNNs) for clinical risk prediction based on electronic health records (EHRs). The primary goal is to provide an overview of the state-of-the-art of this subject, highlighting ongoing research efforts and identifying existing challenges in developing effective GNNs for improved prediction of clinical risks. Methods: A search was conducted in the Scopus, PubMed, ACM Digital Library, and Embase databases to identify relevant English-language papers that used GNNs for clinical risk prediction based on EHR data. The study includes original research papers published between January 2009 and May 2023. Results: Following the initial screening process, 50 articles were included in the data collection. A significant increase in publications from 2020 was observed, with most selected papers focusing on diagnosis prediction (n = 36). The study revealed that the graph attention network (GAT) (n = 19) was the most prevalent architecture, and MIMIC-III (n = 23) was the most common data resource. Conclusion: GNNs are relevant tools for predicting clinical risk by accounting for the relational aspects among medical events and entities and managing large volumes of EHR data. Future studies in this area may address challenges such as EHR data heterogeneity, multimodality, and model interpretability, aiming to develop more holistic GNN models that can produce more accurate predictions, be effectively implemented in clinical settings, and ultimately improve patient care. © 2024 The Authors
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| 5. |
- Pedrollo, Guilherme, et al.
(author)
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Using smart virtual-sensor nodes to improve the robustness of indoor localization systems
- 2021
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In: Sensors. - Basel : MDPI AG. - 1424-8220. ; 21:11
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Journal article (peer-reviewed)abstract
- Young, older, frail, and disabled individuals can require some form of monitoring or assistance, mainly when critical situations occur, such as falling and wandering. Healthcare facilities are increasingly interested in e-health systems that can detect and respond to emergencies on time. Indoor localization is an essential function in such e-health systems, and it typically relies on wireless sensor networks (WSN) composed of fixed and mobile nodes. Nodes in the network can become permanently or momentarily unavailable due to, for example, power failures, being out of range, and wrong placement. Consequently, unavailable sensors not providing data can compromise the system’s overall function. One approach to overcome the problem is to employ virtual sensors as replacements for unavailable sensors and generate synthetic but still realistic data. This paper investigated the viability of modelling and artificially reproducing the path of a monitored target tracked by a WSN with unavailable sensors. Particularly, the case with just a single sensor was explored. Based on the coordinates of the last measured positions by the unavailable node, a neural network was trained with 4 min of not very linear data to reproduce the behavior of a sensor that become unavailable for about 2 min. Such an approach provided reasonably successful results, especially for areas close to the room’s entrances and exits, which are critical for the security monitoring of patients in healthcare facilities. © 2021 by the authors.
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| 6. |
- Pignaton de Freitas, Edison, et al.
(author)
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Adaptable middleware for heterogeneous wireless sensor networks
- 2008
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In: Proceedings of the 10th European Agent Systems Summer School. ; , s. 17-24
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Conference paper (other academic/artistic)abstract
- The use of sensor networks in different kinds of sophisticated applications is emerging due to several advances in sensor technologies and embedded systems. However, the integration and coordination of heterogeneous sensors is still a challenge, especially when the target application environment is susceptible to changes that the system must track and adapt itself to in order to fulfil the users’ requirements. These changing scenarios require services being provided in different places during the system runtime, and to fulfil this, a support for adaptability is needed. In this paper we present some initial ideas to use multi-agents in a middleware that aims to provide the necessary support to sophisticated sensor network applications.
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| 7. |
- Saar de Moraes, Rodrigo, et al.
(author)
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Multi-UAV Based Crowd Monitoring System
- 2020
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In: IEEE Transactions on Aerospace and Electronic Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9251 .- 1557-9603. ; 56:2, s. 1332-1345
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Journal article (peer-reviewed)abstract
- This article presents the development of a multi-unmanned aerial vehicle (UAV) based crowd monitoring system, demonstrating a system that uses UAVs to periodically monitor a group of moving walking individuals. Using auction paradigms to distribute targets among UAVs and genetic algorithms to calculate the best order to visit the targets, the system has shown capabilities to efficiently perform the surveillance, visiting all the targets during a surveillance period and minimizing the time between the visits made to each target. Moreover, the system showed robustness keeping the good performance under a variety of situations.
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| 8. |
- Schwarzrock, Janaína, et al.
(author)
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Solving task allocation problem in multi Unmanned Aerial Vehicles systems using Swarm intelligence
- 2018
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In: Engineering applications of artificial intelligence. - Oxford : Elsevier. - 0952-1976 .- 1873-6769. ; 72, s. 10-20
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Journal article (peer-reviewed)abstract
- The envisaged usage of multiple Unmanned Aerial Vehicles (UAVs) to perform cooperative tasks is a promising concept for future autonomous military systems. An important aspect to make this usage a reality is the solution of the task allocation problem in these cooperative systems. This paper addresses the problem of tasks allocation among agents representing UAVs, considering that the tasks are created by a central entity, in which the decision of which task will be performed by each agent is not decided by this central entity, but by the agents themselves. The assumption that tasks are created by a central entity is a reasonable one, given the way strategic planning is carried up in military operations. To enable the UAVs to have the ability to decide which tasks to perform, concepts from swarm intelligence and multi-agent system approach are used. Heuristic methods are commonly used to solve this problem, but they present drawbacks. For example, many tasks end up not begin performed even if the UAVs have enough resources to execute them. To cope with this problem, this paper proposes three algorithm variants that complement each other to form a new method aiming to increase the amount of performed tasks, so that a better task allocation is achieved. Through experiments in a simulated environment, the proposed method was evaluated, yielding enhanced results for the addressed problem compared to existing methods reported in the literature. © 2018 Elsevier Ltd
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| 9. |
- Vicenzi, Julio Costella, et al.
(author)
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Dynamic Offloading for Improved Performance and Energy Efficiency in Heterogeneous IoT-Edge-Cloud Continuum
- 2023
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In: 2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). - : IEEE. - 9798350327694 - 9798350327700
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Conference paper (peer-reviewed)abstract
- While machine learning applications in IoT devices are getting more widespread, the computational and power limitations of these devices pose a great challenge. To handle this increasing computational burden, edge, and cloud solutions emerge as a means to offload computation to more powerful devices. However, the unstable nature of network connections constantly changes the communication costs, making the offload process (i.e., when and where to transfer data) a dynamic trade-off. In this work, we propose DECOS: a framework to automatically select at run-time the best offloading solution with minimum latency based on the computational capabilities of devices and network status at a given moment. We use heterogeneous devices for edge and Cloud nodes to evaluate the framework's performance using MobileNetV1 CNN and network traffic data from a real-world 4G bandwidth dataset. DECOS effectively selects the best processing node to maintain the minimum possible latency, reducing it up to 29% compared to Cloud-exclusive processing while reducing the energy consumption by 1.9times compared to IoT-exclusive execution. © 2023 IEEE.
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| 10. |
- Agnoletto, Daniel, et al.
(author)
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Time slot transmission scheme with packet prioritization for Bluetooth low energy devices used in real-time applications
- 2020
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In: International Journal of Wireless Information Networks. - New York, NY : Springer Science+Business Media B.V.. - 1068-9605 .- 1572-8129. ; 27:4, s. 518-534
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Journal article (peer-reviewed)abstract
- Bluetooth Low Energy (BLE) is one of the most important technologies that feed the growing field of Internet of Things and Wireless Sensor Networks. Due to its flexibility and unique low power-consumption, an increasing number of industrial devices, household appliances and wearables are being designed using it. However, the real-time demands of these networks such as timing and Quality of Service are not fully covered by the protocol itself. To help improve and offer some control over these characteristics, this paper presents a time slot transmission scheme with packet prioritization. It is based on the division and allocation of the connection interval to two types of messages: real-time and ordinary. The goal is to offer the lowest packet loss and time guarantees for real-time messages, while providing acceptable throughput for ordinary ones. Since the probability of a BLE connection to close increases with the number of packets sent through it, the position where a real-time packet is being sent as well as the number of ordinary messages in a connection represent key factors. The use of the first and last slot for real-time packets with ordinary flow restricted to the space between them decreases the transmission delay uncertainty and allows probability tuning based on the number of ordinary messages. Simulations were performed using the proposed scheme and a reduction of more than 100 times in the delay variance was observed for real-time transmissions. Regarding reliability, around 5% of the packets were lost for a bit error rate of 10−3. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
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