Di Martino B, C. C (2022). Machine Learning, Big Data Analytics and Natural Language Processing Techniques with Application to Social Media Analysis for Energy Communities. In.[More]
Di Martino B, D. S (2022). Semantic Based Knowledge Management in e-Government Document Workflows: A Case Study for Judiciary Domain in Road Accident Trials. In.[More]
Di Martino B, C. C (2022). A Semantic Representation for Public Calls Domain and Procedure: Housing Policies of Campania Region Case Study. In.[More]
Di Martino B, C. C (2022). Application of Business Process Semantic Annotation Techniques to Perform Pattern Recognition Activities Applied to the Generalized Civic Access.. In.[More]
Aversa, R., Branco, D., Di Martino, B., Iaiunese, L. & Venticinque, S (2022). Simulation and Evaluation of Charging Electric Vehicles in Smart Energy Neighborhoods. In Barolli, Leonard, Hussain, Farookh, Enokido & Tomoya (editors), Advanced Information Networking and Applications, pages 657-665. Cham : Springer International Publishing.[More]
Aversa, R., Branco, D., Di Martino, B. & Venticinque, S (2021). Container Based Simulation of Electric Vehicles Charge Optimization, pages 117-126. Springer Science and Business Media Deutschland GmbH.[More]
Branco, D., Di Martino, B. & Venticinque, S (2021). A Big Data Analysis and Visualization Pipeline for Green and Sustainable Mobility, pages 701-710. Springer Science and Business Media Deutschland GmbH.[More][Digital version]
Ambrisi, A., Aversa, R., Ficco, M., Cacace, D. & Venticinque, S (2021). Intelligent Cloud Agents in Multi-participant Conversations for Cyber-Physical Exploitation of Cultural Heritage, pages 97-106. Springer Science and Business Media Deutschland GmbH.[More]
Di Martino, B., Branco, D., Cante, L. C., Venticinque, S., Scholten, R. & Bosma, B. (2021). Semantic and knowledge based support to business model evaluation to stimulate green behaviour of electric vehicles’ drivers and energy prosumers. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, .[More]
Natvig, M. K., Jiang, S., Hallsteinsen, S., Venticinque, S. & Sard, R. E (2021). Evaluation Approach for Smart Charging Ecosystem – with Focus on Automated Data Collection and Indicator Calculations, pages 653-666. Springer Science and Business Media Deutschland GmbH.[More]
2020
Di Martino, B., Cante, L. C., Graziano, M. & Sard, R. E (2020). Tweets Analysis with Big Data Technology and Machine Learning to Evaluate Smart and Sustainable Urban Mobility Actions in Barcelona, pages 510-519. Springer, Cham.[More][Digital version]
Horn, G., Przezdiek, T., Buscher, M., Venticinque, S., Aversa, R., Di Martino, B. et al (2020). An Event-Driven Multi Agent System for Scalable Traffic Optimization. In Advances in Intelligent Systems and Computing, pages 1373-1382. Springer.[More]
Laudante, G., Musone, V., Rak, M., Venticinque, S. & Salzillo, G (2020). A cloud-edge smart infrastructures for road safety. In 20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020 - Proceedings, pages 147-152. Institute of Electrical and Electronics Engineers Inc..[More]
Development of an IoT System for the Generation of a Database of Residential Water End-Use Consumption Time Series. (2020)..[More][Digital version]
2019
Venticinque, S., Di Martino, B., Aversa, R., Natvig, M., Jiang, S. & Sard, R. E (2019). Evaluating Technology Innovation for E-Mobility. In 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pages 76-81. IEEE.[More][Digital version]
Venticinque, S (2019). Benchmarking physical and virtual IoT platforms. In 2019 IEEE International Conference on Cloud Engineering (IC2E), pages 247-252. IEEE.[More]
Venticinque, S. & Nacchia, S (2019). Learning and prediction of E-Car charging requirements for flexible loads shifting. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 284-293. Springer.[More]
Mauro, A. D., Nardo, A. D., Santonastaso, G. F. & Venticinque, S (2019). An IoT system for monitoring and data collection of residential water end-use consumption. In Proceedings - International Conference on Computer Communications and Networks, ICCCN, pages 1-6. Institute of Electrical and Electronics Engineers Inc..[More]
Savaglio, C., Venticinque, S., Leppänen, T. & Ozgovde, A. (2019). Message from the Workshop General Chairs..[More]
Ficco, M. (2019). Could emerging fraudulent energy consumption attacks make the cloud infrastructure costs unsustainable?. Information Sciences, 476, 474-490.[More][Digital version]
