2022

  • Richard, R., Cao, H., & Wachowicz, M. (2022). EVStationSIM: An end-to-end platform to identify and interpret similar clustering patterns of EV charging stations across multiple time slices. In Applied Energy, 322, 119491.
        [DOI]

  • McCully, L., Cao, H., Wachowicz, M., Champion, S. & Williams, P.A.H. (2022). Discovering self-quantified patterns using multi-time window models. In Applied Computing and Informatics.
        [DOI]

  • Richard, R., Cao, H., & Wachowicz, M. (2022). A Spatial-temporal Comparison of EV Charging Station Clusters Leveraging Multiple Validity Indices. In Communications in Computer and Information Science book series.
        [DOI]

2021

  • Cao, H., Wachowicz, M. & Craig, J. (2021). Edge-Cloud Intelligence in Self-Diagnostic of Land Mobile Radio Systems. In Internet of Things (WF-IoT), 2021 IEEE 7rd World Forum on. IEEE. New Orleans, Louisiana, USA.
          [DOI]

  • Parise A., Callejo, M. A. M., Cao, H., & Wachowicz, M. (2021). Prophet model for forecasting occupancy presence in indoor spaces using non-intrusive sensors. In AGILE: GIScience Series 2, 1-13.
          [DOI]

  • Richard, R., Cao, H., & Wachowicz, M. (2021). An Automated Clustering Process for Helping Practitioners to Identify Similar EV Charging Patterns Across Multiple Temporal Granularities. In Proceedings of the 10th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS (pp. 67-77). ISBN 978-989-758-512-8. Virtual Conference. (Acceptance Rate: 19%)
        [DOI] (  Best Student Paper Award)

2020

  • Richard, R., Cao, H., & Wachowicz, M. (2020). Discovering EV Recharging Patterns through an Automated Analytical Workflow. In 2020 IEEE International Smart Cities Conference (ISC2) (pp. 1-8). IEEE. Virtual Conference.
        [DOI]

  • Cao, H., & Wachowicz, M. (2020). A Holistic Overview of Anticipatory Learning for the Internet of Moving Things: Research Challenges and Opportunities. Special Issue State-of-the-Art in Spatial Information Science. In International Journal of Geo-Information 9(4), 272.
        [DOI]

2019

  • Cao, H., & Wachowicz, M. (2019). An Edge-Fog-Cloud Architecture of Streaming Analytics for Internet of Things Applications. Special Issue Edge/Fog/Cloud Computing in the Internet of Things. In Sensors 19(16), 3594.
        [DOI]

  • Cao, H., Wachowicz, M., Renso, C., & Carlini, E. (2019). Analytics Everywhere: generating insights from the Internet of Things. In IEEE Access, 7, 71749-71769.
        [DOI]

  • Cao, H., & Wachowicz, M. (2019). The design of an IoT-GIS platform for performing automated analytical tasks. In Computers, Environment and Urban Systems, 74, 23-40.
        [DOI]

  • Cao, H., & Wachowicz, M. (2019). Analytics Everywhere for streaming IoT data. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 18-25). IEEE. Granada, Spain.
          [DOI]

  • Cao, H., Brown M., Chen L., Smith R., & Wachowicz, M. (2019). Lessons learned from integrating batch and stream processing using IoT data. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 32-34). IEEE. Granada, Spain.
          [DOI]

  • Parise A., Callejo, M. A. M., Cao, H., Mendonca M., Kohli H., & Wachowicz, M. (2019). Indoor Occupancy Prediction using an IoT Platform. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 26-31). IEEE. Granada, Spain.
          [DOI]

2018

  • Cao, H., Wachowicz, M., Renso, C., & Carlini, E. (2018). An edge-fog-cloud platform for anticipatory learning process designed for internet of mobile things In arXiv: 1711.09745
        [arXiv]

2017

  • Cao, H., Wachowicz, M., & Cha, S. (2017, December). Developing an edge computing platform for real-time descriptive analytics. In Big Data (Big Data), 2017 IEEE International Conference on (pp. 4546-4554). IEEE. Boston, MA, USA.
          [DOI]

  • Maduako, I., Cao, H., Hernandez, L., & Wachowicz, M. (2017, October). Combining edge and cloud computing for mobility analytics. In Proceedings of the Second ACM/IEEE Symposium on Edge Computing (p. 22). ACM. San Jose, CA, USA.
        [DOI]

  • Hernandez, L., Cao, H., & Wachowicz, M. (2017, October). Implementing an Edge-Fog-Cloud architecture for stream data management. In Fog World Congress (FWC), 2017 IEEE (pp. 1-6). IEEE. Santa Clara, CA, USA.
          [DOI]

  • Cao, H., & Wachowicz, M. (2017, August). The design of a streaming analytical workflow for processing massive transit feeds. In 2nd International Symposium on Spatiotemporal Computing. Harvard University, Cambridge, MA, USA.
       

  • Cao, H. (2017). What is the next innovation after the internet of things?. arXiv preprint arXiv:1708.07160. (Technical Report)
     

2016

  • Cha, S., Ruiz, M. P., Wachowicz, M., Tran, L. H., Cao, H., & Maduako, I. (2016, December). The role of an IoT platform in the design of real-time recommender systems. In Internet of Things (WF-IoT), 2016 IEEE 3rd World Forum on (pp. 448-453). IEEE. Reston, Virginia, USA
        [DOI]

  • Cao, H., Maduako, I., Cavalheri, E., Brideau, E., & Wachowicz, M. (2016, September). The Role of Graph Databases in Geomatics. In Geomatics Atlantics 2016, Fredericton, NB, Canada.
          [DOI]

  • Cao, H., Maduako, I., Cavalheri, E., Brideau, E., & Wachowicz, M. (2016, September). How can graph databases improve transit systems? In UNB Research Showcase, University of New Brunswick, Fredericton, NB, Canada.
      [DOI]

2015

  • Cao, V. H., Chu, K. X., Le-Khac, N. A., Kechadi, M. T., Laefer, D., & Truong-Hong, L. (2015, July). Toward a new approach for massive LiDAR data processing. In Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2015 2nd IEEE International Conference on (pp. 135-140). IEEE.
          [DOI]

2012

  • Lung, V. D., Van Hung, C., Loc, N. P., & Quoc, N. V. (2012, December). Analysis of Vietnamese tones to optimize database in speech synthesis using unit selection method. In Signal Processing and Information Technology (ISSPIT), 2012 IEEE International Symposium on (pp. 000043-000048). IEEE.
        [DOI]

2011

  • C Hung, L La, P Duy, & V Lung. (2011) Musical fountain modeling, controlled by audio frequency analysis using FFT algorithm. In Vietnam National Conference on Information Technology. (in Vietnamese)
     

Contact us

Analytics Everywhere Lab

University of New Brunswick
Computer Science Faculty
Room GC107,
550 Windsor St, Fredericton,
Canada, E3B 5A3

Email: hcao3[at]unb[dot]ca

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