Rodrigo Da Rosa Righi

Universidade do Vale do Rio dos Sinos | UNISINOS · Computação Aplicada

A key characteristic of cloud computing is elasticity, automatically adjusting system resources to an application's workload. Both reactive and horizontal approaches represent traditional means to offer this capability, in which rule-condition-action statements and upper and lower thresholds occur to instantiate or consolidate compute nodes and vir...

Internet of Things, or IoT, is a new revolution of the Internet, supporting a connection between objects and humans yet more strong. This area is known by the huge quantity of data that can be generated from the RFID sensors at realtime. On managing this data, the IoT middleware introduces some time constrains regarding both accessing applications...

Process rescheduling is an useful mechanism to offer runtime load balancing, mainly in dynamic and heterogeneous environments. In this context, we developed a model called MigBSP which controls the process migration on BSP (Bulk Synchronous Parallel) applications. A BSP application is divided in one or more supersteps, each one containing both comp...

We live in a disruptive moment where technology plays a crucial role in capturing and analyzing citizens’ vital signs in real time. Although having a vast literature on providing health-based intelligent cities, the current articles are disappointing since explanations about scale, module interactions, and processing capabilities need to be detaile...

This paper presents a parallel modeling of a lossy image compression method based on the fractal theory and its evaluation over two versions of dual-core processors: with and without simultaneous multithreading (SMT) support. The idea is to observe the speedup on both configurations when changing application parameters and the number of threads at...

The manufacturers of IoT-based wearable devices present different ways to deliver the captured vital signs. Healthcare third-party systems need to adapt to the different approaches, rising complexity and acts against any idea of seamless integration. In addition to the interoperability problem, we observed that the state-of-the-art does not present...

Healthcare services and IoT, as highlighted by Hu et al. [9], generate enormous volumes of time series data. Using caching in serverless functions can significantly reduce latency and improve performance when storing frequently accessed data in memory. Although several approaches offer improvements, such as the use of in-memory caching, data predic...

This document introduces ADPS (Asynchronous Distributed Publish Subscribe), a PubSub-based communication model tailored for a hierarchical architecture distributed on Edge, Fog, and Cloud layers. The primary challenge addressed by this model is establishing runtime connections between subscribers and data providers, enabling communication across va...

The digitization of patient data by health services has marked a significant milestone in enhancing patient care. The next frontier in precision healthcare is seamlessly integrating this digitized data with real-time data streams from Internet of Things (IoT) devices. This integration is poised to foster the development of Personal Health Records,...

A otimização da utilização de recursos em cidades inteligentes tem o potencial de melhorar o bem-estar dos cidadãos. Através do monitoramento contínuo da saúde das pessoas, é possível a identificação precoce de problemas médicos. No entanto, o problema dos hospitais superlotados persiste, conduzindo a longos períodos de espera para os pacientes que...

Today, all computers have some degree of usable parallelism. Modern computers are explicitly equipped with hardware support for parallelism, such as multiple nodes, multicores, multiple CPUs, and accelerators. At the same time, the Cloud Continuum has become a viable platform for running parallel applications. Building software for these parallel a...

Smart cities can improve the quality of life of citizens by optimizing the utilization of resources. In an IoT-connected environment, people’s health can be constantly monitored, which can help identify medical problems before they become serious. However, overcrowded hospitals can lead to long waiting times for patients to receive treatment. The l...

Conversational systems like chatbots have emerged as powerful tools for automating interactive tasks traditionally confined to human involvement. Fundamental to chatbot functionality is their knowledge base, the foundation of their reasoning processes. A pivotal challenge resides in chatbots' innate incapacity to seamlessly integrate changes within...

As cidades inteligentes podem melhorar a qualidade de vida dos cidadãos, otimizando a utilização dos recursos. Em um ambiente conectado, a saúde das pessoas pode ser monitorada em tempo real para detectar situações que exijam suporte médico. No entanto, hospitais superlotados podem levar a longos tempos de espera para os pacientes receberem tratame...

In this work, a solution for the distributed storage of data in Smart Cities is presented. An Edge-Fog-Cloud architecture that partitions the data through the Sharding technique proposes a hierarchical model that manipulates IoT data generated by Smart Cities. The problem is related to the approaches used to promote an integrated environment. Relat...

The growth of the world population forces a more outstanding and more efficient food production, forc-ing agribusiness into the race for greater productivity. Thus, agrochemicals as a tool for increasing and defending production have become more critical with each harvest. This work presents an ontology that describes the knowledge involved in the...

A pandemia de COVID-19 agravou a superlotação hospitalar. Em cidades inteligentes, a saúde das pessoas pode ser monitorada em tempo real para detectar situações que exijam suporte médico. Neste contexto, propomos o modelo CityHealth, baseado no conceito de elasticidade em Cloud Computing, onde é possível adicionar, migrar ou remover recursos de aco...

Este artigo apresenta SmartVSO - um modelo computacional de uma arquitetura hierárquica, escalável, fog-cloud, que processa sinais vitais com serviços de saúde implementados como funções serverless. Heurísticas favorecem sinais vitais de pessoas com problemas de saúde, a fim de obterem resultados com baixo tempo de resposta mesmo durante picos de u...

Purpose: Smart cities that support the execution of health services are more and more in evidence today. Here, it is mainstream to use IoT-based vital sign data to serve a multi-tier architecture. The state-of-the-art proposes the combination of edge, fog, and cloud computing to support critical health applications efficiently. However, to the bes...

Today, we no longer live in an era where cloud computing was addressed only for enterprise transaction-based applications like e-commerce and those centered on database usage. We are experiencing several cloud providers exploiting bottleneck performance bypass through optimized software and hardware infrastructures. With this in mind, each time mor...

Cloud, IoT, big data, and artificial intelligence are currently very present in the industrial and academic areas, being drivers of technological revolution. Such concepts are closely related to Industry 4.0, which can be defined as the idea of a flexible, technological, and connected factory, encompassing the shop floor itself and its relationship...

Infrastructures based on fog computing are gaining popularity as an alternative to provide low-latency communication on executing distributed services. With cloud resources, it is possible to assemble an architectub re with resources close to data providers and those with more processing capacity, achieved through internet links. In this context, t...

Pregnant women constantly need some information to support nutritional decisions during pregnancy, and many do not receive such assistance at all. This study aims to present a conversational agent to provide reliable information to pregnant women, focusing on nutritional education and evaluating the perception of pregnant women and health professio...

All over the world, there is a lot of patient health data in different locations such as hospitals, clinics, insurance companies, and other organizations. In this sense, global identification of the patient has emerged as an everyday healthcare challenge. Governments and institutions have to prioritize satisfactory, quick, and integrated decision-m...

The transmission network can enhance its economic advantages by adjusting the topology of the power system during operation. However, the constant change in demand requires the switching process to take place continuously during the day. Therefore, this requires the line switching must follow a certain strategy to ensure the stability of the system...

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for pro...

Inertial measurement units (IMU) are used diagnostically in the movement analysis of Parkinson’s disease (PD) patients, allowing an objective way to assess biomechanical motion and gait parameters. The Timed Up and Go (TUG) is a standardized clinical gait test widely used in the monitoring of patient fall risk and disease progression. Gait tests pe...

Glaucoma is the most significant cause of irreversible vision loss and the second biggest cause of blindness globally. The first signs of the disease will only appear in an advanced stage when there is no more recovery. Early diagnosis is of the utmost importance and is currently performed primarily through fundoscopy. This fundus image exam is a t...

The challenges of continuous authentication have resulted in a surge of recent studies. This article surveys the state of the art and rising trends in continuous and adaptive context-aware authentication. It employs a statistical approach to collect metrics on recent works exploring machine learning techniques for continuous learning.

This systematic review aims to study and classify machine learning models that predict pandemics' evolution within affected regions or countries. The advantage of this systematic review is that it allows the health authorities to decide what prediction model fits best depending upon the region's criticality and optimize hospitals' approaches to pre...

The high volume of money involved in e-commerce transactions draws the attention of fraudsters, which makes fraud prevention and detection techniques of high importance. Current surveys and reviews on fraud systems focuses mainly on financial-specific domains or general areas, leaving e-commerce aside. In this context, this article presents a syste...

The evolution of parallel architectures points to dynamic environments where the number of available resources or configurations may vary during the execution of applications. This can be easily observed in grids and clouds, but can also be explored in clusters and multiprocessor architectures. Over more than two decades, several research initiativ...

Internet of Things (IoT) is a constantly growing paradigm that promises to revolutionize healthcare applications and could be associated with several other techniques. Data prediction is another widely used paradigm, where data captured over time is analyzed in order to identify and predict problematic situations that may happen in the future. Afte...

Background: the increasing adoption of smart and wearable sensors in the healthcare domain empowers the development of cutting-edge medical applications. Smart hospitals can employ sensors and applications for critical decision-making based on real-time monitoring of patients and equipment. In this context, quality of service (QoS) is essential to...

The Internet of Things (IoT) and its current IETF and IEEE dual stack model have been facing limitations, requiring applications to overcome tough constraints by their own, narrowing the full potential of this concept. For instance, the IoT dual stack model does not entirely address or support perennial naming, immutable data provenance, data accou...

Study objectives In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts, and...

Despite the advancements to improve patient safety, a significant number of errors still occur in Operating Suites (OS). To improve medical decision-making and the resulting quality of care, it is essential to monitor and understand medical activities’ workflow and interactions. Although some strategies employ different sensor devices, their focus...

Agrochemicals are products that, due to their hazardous nature and high cost, need to be monitored. The management of agrochemical packaging is generally precarious, and the supply chain needs more control due to its reverse characteristic. Traceability in the supply chain usually uses one sensor and not a combination of multiple sensors. The propo...

Glaucoma é a principal causa mundial de perda irreversível de visão. Afim de viabilizar a implantação de uma ferramenta de diagnóstico de glaucoma para a clínica médica, um trabalho base foi selecionado e otimizado. Ao unificar duas redes de segmentação reduzimos o tempo de processamento em 24,24%, e adicionando uma segunda rede de classificação di...

This paper presents a novel architecture to handle serverless functions with adaptive timeout, leveraging prediction to foresee how long the incoming request will take to finish based on historical data. This decision-making process aims to ensure that no request will be discarded, while maximizing execution throughput and offloading requests from...

Esse artigo apresenta uma nova arquitetura que integra computação em nuvem e neblina com compressão de dados para aquisição e processamento de informações em uma base heterogênea de dispositivos medical IoT (MIoT) que monitoram sinais vitais. O modelo permite processar uma grande base de dados distribuídos com baixa latência e baixo consumo de band...

A técnica de aprendizado federado é muito utilizada quando os dados a serem usados pelos modelos de aprendizado de máquina são sensíveis ou sigilosos. No entanto, aprendizado federado prevê o treinamento dos modelos por conta do usuário, que nem sempre está disponível para treinar o modelo ou não possui recursos computacionais eficientes. Esse trab...

Internet of Things (IoT) is currently present in several areas, including healthcare. IoT offers technology to track and monitor the state of patients remotely. In this context, this article presents MinhaHistoriaDigital, a scalable Fog-based solution for real-time monitoring and data processing from patients wearing wearable devices. Its main cont...

Sharding é uma estratégia de armazenamento de dados distribuídos em uma arquitetura horizontal. Dessa maneira, essa prática tem um enorme potencial de reduzir a latência no acesso de dados distribuídos em cidades inteligentes. Nessa pesquisa, trazemos uma implementação de Sharding para ser a base prática de uma arquitetura de armazenamento distribu...

Hospitais desempenham um papel importante para garantir o tratamento adequado da saúde humana. Em cidades inteligentes a saúde das pessoas pode ser monitorada a todo momento para que situações que requeiram suporte médico possam ser identificadas com antecedência. Nesse contexto, propomos um modelo adaptativo baseados em elasticidade para gerenciam...

IoT applications usually rely on cloud computing services to perform data analysis such as filtering, aggregation, classification, pattern detection, and prediction. When applied to specific domains, the IoT needs to deal with unique constraints. Besides the hostile environment such as vibration and electric-magnetic interference, resulting in malf...

The COVID-19 pandemic has rapidly spread around the world. The rapid transmission of the virus is a threat that hinders the ability to contain the disease propagation. The pandemic forced widespread conversion of in-person to virtual care delivery through telemedicine. Given this gap, this article aims at providing a literature review of machine le...

Healthcare 4.0 is a new concept that originates from the evolution of hospitals due to technological advances in medical activities. Nowadays, more and more doctors and healthcare administrators require real-time data analysis obtained from sensors and surgery monitoring. Using real-time information could make the difference between death and life...

In the field of agricultural research, Machine Learning (ML) has been used to increase agricultural productivity and minimize its environmental impact, proving to be an essential technique to support decision making. Accurate harvest time prediction is a challenge for fruit production in a sustainable manner, which could eventually reduce food wast...

IoT applications usually rely on cloud computing services to perform data analysis such as filtering, aggregation, classification, pattern detection, and prediction. When applied to specific domains, the IoT needs to deal with unique constraints. Besides the hostile environment such as vibration and electricmagnetic interference, resulting in malfu...

Nowadays, data has become an invaluable asset to entities and companies, and keeping it secure represents a major challenge. Data centers are responsible for storing data provided by software applications. Nevertheless, the number of vulnerabilities has been increasing every day. Managing such vulnerabilities is essential for building a reliable an...

The integration and exchange of information among health organizations and system providers are currently regarded as a challenge. Each organization usually has an internal ecosystem and a proprietary way to store electronic health records of the patient’s history. Recent research explores the advantages of an integrated ecosystem by exchanging inf...

Industry 4.0 (I4.0) provides connectivity, data volume, new devices, miniaturization, inventory reduction, personalization, and controlled production. In this new era, customization and data availability are essential to generate information that allows decision-making. The possibility of predicting the need for maintenance in the future and using...

Nowadays, there are many fragmented records of patient’s health data in different locations like hospitals, clinics, and organizations all around the world. With the arrival of the COVID-19 pandemic, several governments and institutions struggled to have satisfactory, fast, and accurate decision-making in a wide, dispersed, and global environment....

The fifth-generation mobile evolution introduces Next-Generation Radio Access Networks (NG-RAN), splitting the RAN protocol stack into the eight disaggregated options combined into three network units, i.e., Central, Distributed, and Radio. The disaggregated units reach full interoperability on Open RAN. Further advances allow the RAN software to b...

Background: Although the world has been facing the COVID-19 pandemic for over a year, we understand that there are still some challenges in using Internet of Things (IoT) devices as allies in this fight. Among the main difficulties, we can mention the selection of appropriate devices and the correct measurement and subsequent analysis of previously...

Industry 4.0 introduces several changes to the original approach of industrial automation. Internet of Things (IoT) and cyber-physical system (CPS) technologies play huge roles in this context introducing cognitive automation and consequently implementing the concept of intelligent production, leading to smart products and services. This approach l...

Through the Internet of Things (IoT), the generation of data, Cyber-Physical Systems (CPS) has shown a steady increase. The search for approaches in order to take advantage of generated data is a recurring theme on several managers’ agenda. To this end, data mining techniques, combined with asset health management, contribute to Industry 4.0 releva...

This article presents a dataset of insect-damaged soybean leaves. The capture of images was carried out on several soy farms, under realistic weather conditions, using two cell phones and a UAV. The dataset consists of 3 (three) folders with a total of 6,410 images. The dataset is divided into three categories: (I) healthy plants, (II) plants affec...

Early identification of patients with COVID-19 is essential to enable adequate treatment and to reduce the burden on the health system. The gold standard for COVID-19 detection is the use of RT-PCR tests. However, due to the high demand for tests, these can take days or even weeks in some regions of Brazil. Thus, an alternative for detecting COVID-...