The proliferation of urban sensing, IoT, and big data in buildings, cities, and urban areas provides unprecedented opportunities for a deeper understanding of occupant behavior, transportation, and energy and water usage patterns. However, utilizing the existing data sources and modeling methods in building science to model urban scale occupant behaviors can be pretty challenging. Therefore, technological progress is needed to unlock its full potential. In order to fulfill the latter task, this workshop focuses on the methodologies for big urban and building data collection, analytics, modeling, and real-world technology deployment. Additionally, it also places a spotlight on two different IEA EBC Annexes: the IEA EBC Annex 79 Subtask 2 on data-driven occupant modeling strategies and digital tools, and the IEA EBC Annex 82 Subtask A2.3 on data-driven modelling of energy flexibility on building- and urban-scale.
The workshop aims to open up discussions on 1. Big data modeling paradigms that could be applicable in building and urban science; 2. Requirements on the data collection infrastructure needed for these modeling paradigms; 3. Challenges faced by current modeling approaches; and 4. Future research directions to fully utilize building and urban big data. An important part of the workshop will be dedicated to accelerating the open-world deployment of developed technologies, and highlighting challenges encountered in real-world large-scale pilots. For instance, how can existing and upcoming guidelines on model benchmarking and standardization unlock the potential of big data, help us better understand occupant behavior, and optimize energy consumption on building- and urban-scale.
BALANCES'22 will be held in conjunction with ACM BuildSys'22
The workshop will accept the submissions of original work or work in progress. Submitted papers must be unpublished and must not be currently under review for any other publication. Submissions must be full papers, at most 4 single-spaced US Letter (8.5” x 11”) pages, including figures, tables, references and appendices. Submissions for All submissions must use the LaTeX (preferred) or Word styles found here. All submissions must be submitted using the submission website. Authors must make a good faith effort to anonymize their submissions by: (1) using the "anonymous" option for the class and (2) using "anonsuppress" section where appropriate. Papers that do not meet the size, formatting, and anonymization requirements will not be reviewed. Please note that ACM uses 9-pt fonts in all conference proceedings, and the style (both LaTeX and Word) implicitly define the font size to be 9-pt.
The tentative presentation formats are regular oral presentation (15 minutes) and a spotlight presentation (2 minutes).
Register through ACM BuildSys 2022
Marios M. Polycarpou
Marios M. Polycarpou
Marios M. Polycarpou
Professor, IEEE Fellow, IFAC Fellow
Director, KIOS Research and Innovation Center of Excellence
Professor of Electrical and Computer Engineering, University of Cyprus
Visiting Professor, Imperial College London, U.K.
Distributed Fault Diagnosis of Interconnected Cyber-Physical Systems
The emergence of interconnected cyber-physical systems and sensor/actuator networks has given rise to advanced automation applications, where a large amount of sensor data is collected and processed in order to make suitable real-time decisions and to achieve the desired control objectives. However, in situations where some components behave abnormally or become faulty, this may lead to serious degradation in performance or even to catastrophic system failures, especially due to cascaded effects of the interconnected subsystems. Distributed fault diagnosis refers to monitoring architectures where the overall system is viewed as an interconnection of various subsystems, each of which is monitored by a dedicated fault diagnosis agent that communicates and exchanges information with other “neighboring” agents. The goal of this presentation is to provide insight into various aspects of the design and analysis of intelligent monitoring and control schemes and to discuss directions for future research.
The Cyprus Institute