- 1st ACM Workshop on Privacy in Smart Buildings and Environments (PSBE'23)
- 1st IEA EBC Annex 81 'Data-Driven Smart Buildings' Workshop on Smart Building-to-Grid Services and Applications (B2G'23)
- 1st Int'l Workshop on Cyber-Physical-Social Infrastructure Systems (CPSIS'23)
- 2nd ACM Workshop on Advancements in Building Energy Benchmarking Systems (BenchSys'23)
- 3rd ACM International Workshop on Big Data and Machine Learning for Smart Buildings and Cities (BALANCES'23)
- 4th ACM SIGEnergy Workshop on Reinforcement Learning for Energy Management in Buildings & Cities (RLEM'23)
- 6th International SenSys+BuildSys Workshop on Data: Acquisition to Analysis (DATA'23)
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1st ACM Workshop on Privacy in Smart Buildings and Environments (PSBE'23)Website | CFP | Important Dates | Submission Link
Our built environments increasingly collect sensitive information about their human occupants using sensors such as smart electricity, gas and water meters, building occupancy temperature and vibration sensors, and many types of image-based sensing. As the number of sensors and monitoring systems in smart buildings and smart cities grows, so too does the risk to privacy for the people that inhabit those spaces. This triggers some important questions, such as:
- What are our rights to privacy as citizens and how might those be compromised by smart buildings and smart cities?
- What specific challenges do sensor systems in built environments pose for protecting human privacy?
- As designers of sensor systems, what are our responsibilities for protecting privacy?
- What privacy-enhancing technologies are most effective to mitigate risks to privacy whilst preserving the utility of the data?
- How can we measure privacy and utility for data and applications for the built environment?
- How can we track whether sensor systems and data analytics adhere to privacy standards?
- How can fairness, transparency, accuracy, integrity, confidentiality, and data minimisation be built-in to sensing systems?
The First Workshop on Privacy in Smart Buildings and Environments (PSBE) aims to bring together researchers with multiple perspectives on these questions to explore current best practices and discuss promising directions for future research.
- Rachel Cardell-Oliver (University of Western Australia, Australia)
- Isabel Wagner (University of Basel, Switzerland)
- Jin B. Hong (University of Western Australia, Australia)
1st IEA EBC Annex 81 'Data-Driven Smart Buildings' Workshop on Smart Building-to-Grid Services and Applications (B2G'23)Website | CFP | Important Dates | Submission Link
The BuildSys B2G'23 Workshop brings together researchers and industry practitioners to explore the development and advancement of data-driven methods for providing building-to-grid services that ensure the efficiency, sustainability, stability and reliability of energy grids with large shares of intermittent renewable energy sources.
This workshop will allow participants to discuss pathways for increased adoption of building-to-grid controls through panel Q&A with international experts and round table brainstorming discussions for a proposed new Mission Innovation 'Grid Integrated Control of Buildings' initiative.
- Hicham Johra (Aalborg University, Denmark)
- Stephen White (CSIRO, Australia)
1st Int'l Workshop on Cyber-Physical-Social Infrastructure Systems (CPSIS'23)Website | CFP | Important Dates | Submission Link
Cyber-physical systems (CPSs) have radically transformed engineering solutions over the last decade. CPSs have even expanded to include human-in-the-loop control, where humans serve as operators or supervisors. While these paradigms have been wildly successful for the design and operation of physical systems decoupled from—or weakly coupled to—human social contexts, it is limiting to study physical systems in a vacuum, that is, without accounting for their interactions with the social systems they are designed to serve. This traditional approach has left many promising applications of CPSs to human-oriented systems—or cyber-physical-social infrastructure systems (CPSISs)—untouched.
The ACM BuildSys CPSIS'23 Workshop brings together researchers and industry practitioners to explore the development and advancement of CPSISs capable of explicitly enhancing social (i.e., human-centered) benefits of the built environment. The workshop will showcase advances in the theory and tools used to support CPSISs, which promise the design, management, and control of physical spaces and the built environment in ways that explicitly and measurably contribute to social objectives (e.g., productivity, sociability, co-design and collaboration, well-being, accessibility) and determine whether social capital develops.
The workshop is soliciting notes and papers for proceedings publication and presentation (3-8 pages).
- Katherine Flanigan (Carnegie Mellon University, USA)
2nd ACM Workshop on Advancements in Building Energy Benchmarking Systems (BenchSys'23)Website | CFP | Important Dates | Submission Link
The second ACM international workshop on “Advances in Building Energy Benchmarking” invites papers on the current developments in building energy benchmarking. Researchers and practitioners working on data acquisition technology and processes, data sharing protocols and policies, benchmarking modeling methodologies, standardization and widespread adoption, strategy and collaboration, case studies, open source platforms and crowdsourcing are invited to participate. The workshop also aims to explore the existing challenges in data acquisition techniques in emerging economies. It will foster a discussion on the widespread adoption of energy benchmarking methods while bringing together researchers and practitioners from diverse backgrounds to discuss related challenges and breakthroughs. This year's workshop has expanded the scope of submission formats to attract participants from across spectrum and stimulate rich interaction and engagement.
- Prashant Anand (IIT Kharagpur, India)
- Balaji Kalluri (FLAME University, India)
- Chirag Deb (The University of Sydney, Australia)
- Priya Vishnu (Massey University, New Zealand)
- Pandarasamy Arjunan (Indian Institute of Science, India)
3rd ACM International Workshop on Big Data and Machine Learning for Smart Buildings and Cities (BALANCES'23)Website | CFP | Important Dates | Submission Link
The proliferation of urban sensing, IoT, and big data in buildings, cities, and urban areas provides unprecedented opportunities to better understand and optimize transportation, energy and water networks, and how human behavior affects them (and is, in turn, affected by them). However, historically due to poor-quality data, limitations in algorithms, and computational bottlenecks, modeling urban-scale occupant behavior and its interactions with energy and transportation demand has proven to be quite challenging. Therefore, progress in developing data-driven techniques, which can work with enormous amounts of data that is increasingly available today, is needed to unlock its full potential.In order to realize this potential, BALANCES focuses on innovative data-driven methodologies that can be applied to model and optimize buildings and cities. Additionally, it also places a spotlight on two different IEA EBC Annexes: the Annex 81 - Data-Driven Smart Buildings. Annex 82 - Energy Flexible Buildings Towards Resilient Low Carbon Energy Systems. In doing so, the workshop aims to open up discussions on:
- Big data modeling paradigms that could be applicable in building and urban science
- Requirements on the data collection infrastructure needed for these modeling paradigms
- Challenges faced by current modeling approaches, and
- Future research directions to fully utilize building and urban big data.
- Bing Dong (Syracuse University, USA)
- Ankush Chakrabarty (Mitsubishi Electric Research Laboratories, USA)
- Xu Han (University of Kansas, USA)
- Sicheng Zhan (National University of Singapore, Singapore)
- Zhipeng Deng (Syracuse University, USA)
4th ACM SIGEnergy Workshop on Reinforcement Learning for Energy Management in Buildings & Cities (RLEM'23)Website | CFP | Important Dates | Submission Link
RLEM brings together researchers and industry practitioners for the advancement of (deep) reinforcement learning (RL) in the built environment as it is applied for managing energy in civil infrastructure systems (energy, water, transportation).
Optimal decarbonization requires electrification of end-uses and concomitant decarbonization of electricity supply. The integration must be done carefully to unlock their full potential. Artificial intelligence is regarded as a possible pathway to orchestrate these complexities of Smart Cities. In particular, (deep) reinforcement learning algorithms have seen an increased interest and have demonstrated human expert level performance in other domains, e.g., computer games. Research in the building and cities domain has been fragmented and with focus on different problems and using a variety of frameworks.
The purpose of this Workshop is to build a growing community around this exciting topic, provide a platform for discussion for future research direction, and share common frameworks.
- Zoltan Nagy (The University of Texas at Austin, USA)
6th International SenSys+BuildSys Workshop on Data: Acquisition to Analysis (DATA'23)Website | CFP | Important Dates | Submission Link
The Data: Acquisition To Analysis (DATA) workshop aims to look broadly at interesting data from interesting sensing systems. The workshop considers problems, solutions, and results from all across the real-world data pipeline. We solicit submissions on unexpected challenges and solutions in the collection of datasets, on new and novel datasets of interest to the community, and on experiences and results - explicitly including negative results - in using prior datasets to develop new insights.
The workshop aims to bring together a community of application researchers and algorithm researchers in the sensing systems and building domains to promote breakthroughs from integration of the generators and users of datasets. The workshop will foster cross-domain understanding by enabling both the understanding of application needs and data collection limitations.
- Gabe Fierro (Colorado School of Mines, USA)
- Shiwei Fang (University of Massachusetts Amherst, USA)