João Carlos Amaro Ferreira (ISCTE-IUL, 16/07/2021), showcasing the research group's work in IoT, edge/fog computing, and data science. The group has expertise in edge/fog architectures (open-source and commercial platforms), IoT communications (short and long range, lightweight protocols such as MQTT/CoAP, V2X), and distributed AI models (edge-to-cloud deployment, federated learning), applied to Industry 4.0, transportation, and energy. Highlighted case studies include: building energy efficiency using IoT ("Social IoT Project," IoT data visualization in 3D BIM models); waste management data analytics; a hospital data project (predicting patient waiting times, appointment overbooking, and extracting clinical knowledge via NLP/NER, using the DataSense framework for GDPR-compliant sensitive data detection); analysis of Lisbon's public transport data (Carris) to identify factors influencing fuel consumption, with estimated savings of 20–40€/day per bus; mobile accelerometer data for pothole detection and driving-style identification; analytics on Lisbon traffic accidents and fire incidents; air quality (NO2) monitoring during the pandemic; and sentiment/topic analysis of social media (Twitter, Reddit, Público) around COVID-19 in Portugal. Overall, it's a portfolio of applied projects combining IoT, big data, and AI to tackle real-world problems in smart cities, healthcare, transportation, buildings, and social media.
João C. Ferreira· Zenodo (CERN European Organi...· 0 citations
João Carlos Amaro Ferreira (ISCTE-IUL, 16/07/2021), showcasing the research group's work in IoT, edge/fog computing, and data science. The group has expertise in edge/fog architectures (open-source and commercial platforms), IoT communications (short and long range, lightweight protocols such as MQTT/CoAP, V2X), and distributed AI models (edge-to-cloud deployment, federated learning), applied to Industry 4.0, transportation, and energy. Highlighted case studies include: building energy efficiency using IoT ("Social IoT Project," IoT data visualization in 3D BIM models); waste management data analytics; a hospital data project (predicting patient waiting times, appointment overbooking, and extracting clinical knowledge via NLP/NER, using the DataSense framework for GDPR-compliant sensitive data detection); analysis of Lisbon's public transport data (Carris) to identify factors influencing fuel consumption, with estimated savings of 20–40€/day per bus; mobile accelerometer data for pothole detection and driving-style identification; analytics on Lisbon traffic accidents and fire incidents; air quality (NO2) monitoring during the pandemic; and sentiment/topic analysis of social media (Twitter, Reddit, Público) around COVID-19 in Portugal. Overall, it's a portfolio of applied projects combining IoT, big data, and AI to tackle real-world problems in smart cities, healthcare, transportation, buildings, and social media.
João C. Ferreira· Zenodo (CERN European Organi...· 0 citations
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