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- IoT system to monitor the well-being of senior citizens who self-isolate during the pandemicPublication . Gonçalves, Fábio; Jesus, Cassandra Sofia dos Santos; Fernandes, Francisco; Rosa, Rafaela; Dionísio, Rogério PaisThe COVID-19 pandemic and the need for selfisolation has decreased the frequency of visits to senior citizens by family members or caregivers. Because of this, many health concerns of the elderly remained unresolved. We created a IoT system, called Zelar@CB, that monitors the daily activities of isolated elderly people who do not have access to at-home care. The proposed project detects unusual activity by monitoring the person’s usage of electrical appliances to track if the user left the stove on or if there is a change in usage. It can also detect when the user falls, and sends an alert to family members or caregivers.
- Proceedings of the 5th International Conference on Production Economics and Project EvaluationPublication . Farinha, Luís; Araújo, Madalena; Rigueiro, Constança; Raposo, Daniel; Neves, João Vasco; Anjos, O.; Dionísio, Rogério PaisInternational Conference on Production Economics and Project Evaluation.
- Satellite IoT System Simulation with SEAMCAT: overview, modeling and analysisPublication . Dionísio, Rogério PaisSatellite IoT System Simulation with SEAMCAT: overview, modeling and analysis.
- Nyon-data : a fall detection dataset from a hinged board apparatusPublication . Dionísio, Rogério Pais; Rosa, Ana Rafaela; Jesus, Cassandra Sofia dos SantosNyon-data : a fall detection dataset from a hinged board apparatus.
- Nyon-data, a fall detection dataset from a hinged board apparatusPublication . Dionísio, Rogério Pais; Rosa, Ana Rafaela; Jesus, Cassandra Sofia dos SantosFalls are one of the causes of severe hilliness among elders, and the COVID-19 pandemic increased the number of unattended cases because of the social distancing measures. This study aims to create a dataset that collects the data from a 3-axis acceleration sensor fixed on a hinged board apparatus that mimics a human fall event. The datalogging system uses off-the-shelf devices to measure, collect and store the data. The resulting dataset includes data from different angle positions and heights, corresponding to joints of the lower limbs of the human body (ankle, knee, and hip). We use the dataset with a threshold-based fall detection algorithm. The result from the Receiver Operating Characteristic curve shows a good behavior with a mean Area Under the Curve of 0.77 and allow to compute a best threshold value with False Positive Rate of 14.8% and True Positive rate of 89.1%. The optimal threshold value may vary depending on the specific population, activity patterns, and environmental conditions, which may require further customization and validation in real-world settings.
- The extended information systems success measurement model : e-learning perspectivePublication . Lolić, Teodora; Stefanovic, Darko; Lalic, Danijela Ciric; Dionísio, Rogério Pais; Oliveira, Ângela; Pržulj, ĐorđeThis study investigated the crucial factors for measuring the success of the information system used in the e-learning process, considering the transformations in the work environment. This study was motivated by the changes caused by COVID-19 witnessed after the shift to fully online learning environments supported by e-learning systems, i.e., learning emphasized with information systems. Empirical research was conducted on a sample comprising teaching staff from two European universities: the University of Novi Sad, Faculty of Technical Sciences in Serbia and the Polytechnic Institute of Castelo Branco in Portugal. By synthesizing knowledge from review of the prior literature, supported by the findings of this study, the authors propose an Extended Information System Success Measurement Model—EISSMM. EISSMM underlines the importance of workforce agility, which includes the factors of proactivity, adaptability, and resistance to change, in the information system performance measurement model. The results of our research provide more extensive evidence and findings for scholars and practitioners that could support measuring information system success primarily in e-learning and other various contextual settings, highlighting the importance of people’s responses to work environment changes.
- PoPu-Data: a multilayered, simultaneously collected lying position datasetPublication . Fonseca, Luís Filipe Rodrigues; Ribeiro, Fernando Reinaldo; Metrôlho, J.C.M.M.; Santos, Adriana; Dionísio, Rogério Pais; Amini, Mohammad; Silva, Arlindo F.; Heravi, Ahmad Reza; Sheikholeslami, Davood Fanaei; Fidalgo, Filipe; Rodrigues, Francisco; Santos, Osvaldo; Coelho, Patrícia; Aemmi, Seyyed SajjadThis study presents a dataset containing three layers of data that are useful for body position classification and all uses related to it. The PoPu dataset contains simultaneously collected data from two different sensor sheets—one placed over and one placed under a mattress; furthermore, a segmentation data layer was added where different body parts are identified using the pressure data from the sensors over the mattress. The data included were gathered from 60 healthy volunteers distributed among the different gathered characteristics: namely sex, weight, and height. This dataset can be used for position classification, assessing the viability of sensors placed under a mattress, and in applications regarding bedded or lying people or sleep related disorders.
- Magnetoresistive sensors and piezoresistive accelerometers for vibration measurements: a comparative studyPublication . Dionísio, Rogério Pais; Torres, Pedro; Ramalho, Armando; Ferreira, Ricardohis experimental study focuses on the comparison between two different sensors for vibration signals: a magnetoresistive sensor and an accelerometer as a calibrated reference. The vibrations are collected from a variable speed inductor motor setup, coupled to a ball bearing load with adjustable misalignments. To evaluate the performance of the magnetoresistive sensor against the accelerometer, several vibration measurements are performed in three different axes: axial, horizontal and vertical. Vibration velocity measurements from both sensors were collected and analyzed based on spectral decomposition of the signals. The high cross-correlation coefficient between spectrum vibration signatures in all experimental measurements shows good agreement between the proposed magnetoresistive sensor and the reference accelerometer performances. The results demonstrate the potential of this type of innovative and non-contact approach to vibration data collection and a prospective use of magnetoresistive sensors for predictive maintenance models for inductive motors in Industry 4.0 applications.
- Nyon : a ubiquitous fall detection device for eldersPublication . Jesus, Cassandra Sofia dos Santos; Rosa, Ana Rafaela; Dionísio, Rogério PaisFalls are one of the main causes of mortality and morbidity in the elderly worldwide. This had let to the research and development of electronic fall-detection systems. We propose a complete fall-detection system, that combines a wearable device (called Nyon) and a message microservice (for email and SMS) to alert caregiver every time a fall occurs. The wearable uses a simple threshold method and has the capability of search and switch between Wi-Fi and Bluetooth, using the available communication technology when a fall occurs. The results have shown that the wearable autonomy is adequate for a daily use and the server microservices are reliable and deliver a message to the caregiver every time a fall alert occurs. Several improvements are planned to increase the autonomy and range of the wearable device.
- Using smart traffic lights to reduce CO2 emissions and improve traffic flow at intersections: simulation of an intersection in a small Portuguese cityPublication . Santos, Osvaldo; Ribeiro, Fernando Reinaldo; Metrôlho, J.C.M.M.; Dionísio, Rogério PaisReducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.