WorkshopsWorkshops are in Hamilton Hall!
- The 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization (UrbSys)
- The 1st ACM International Workshop on Device-Free Human Sensing (DFHS)
- The 1st ACM International Workshop on Technology Enablers and Innovative Applications for Smart Cities and Communities (TESCA)
- The 2nd ACM International Workshop on Data: Acquisition To Analysis (DATA)
Please see if your paper fits the co-located workshops in Sensys 2019.
Location: Hamilton 304
The advancements and availability of low-cost, low-energy sensors has improved energy and environmental sensing exponentially. Besides the millions of sensors used for monitoring, the improved accuracy of these sensors offer greater resolution for modeling ‘what-if’ scenarios in near real-time using high-performance computing. Similarly, big data analysis has enabled city-scale modeling of energy and environmental impact using, among others, energy-efficient ‘smaller’ machine learning algorithms and/or physics-based modeling approaches. Coupled with interactive data visualization including Virtual Reality (VR), urban-scale energy and environmental systems modeling has become an exciting niche at the intersection of computer science and urban / architecture / mechanical engineering. The UrbSys workshop intends to capture the recent work by research experts at this nexus that supports sustainable urban systems’ design and engineering through state-of-the-art sensing, controls, modeling, and visualization.
Submission deadline: June 22, 2019, AOE
Location: Hamilton 602
The advent of human sensing has enabled many applications in smart buildings and cities, including healthcare, energy management, and marketing. Considerable work has been done in the recent past to sense the human using devices which they carry or wear, such as smartphones and wearables. These approaches, although potentially accurate, have high installation and maintenance requirement which limits their application in some real-life applications. For example, in eldercare monitoring, requiring the elderly to wear or carry a device at all times is an important limitation. This workshop aims to attract novel research papers which enhance device-free human sensing via either developing device-free sensing hardware or designing data-driven, physics-based, or physics-guided data-driven algorithms to extract meaningful information about human status, activities, and behavioral patterns.
Submission deadline: August 8, 2019, 11:59:59pm AOE
Location: Hamilton 703
By 2050, it is envisaged that more than half of the worldwide population will live in urban areas. Owing to this trend, solutions and policies need to set forth in order to manage resource consumption, wastage and overall costs in urban spaces. Smart Cities offer huge potential to revolutionize a range of utilities and services in urban spaces including areas such as healthcare, energy management, transportation, security and smart buildings. Smart city integrates the modern digital technologies such as sensing, IoT, networking, cloud computing, big data, machine learning and artificial intelligence to ensure economic and environmental sustainability. The goal of the workshop, Technology Enabler for Smart Cities (TESC-2019), is to provide a forum where diverse group of researchers can share the latest research insights, present key and novel results on both theoretical and application perspectives of smart cities.
Submission deadline: August 9, 2019
- Venkat P. Rangan (Amrita Vishwa Vidyapeetham, India)
- Maneesha V. Ramesh (Amrita Vishwa Vidyapeetham, India)
- Nalini Venkatasubramanian (University of California at Irvine, USA)
- Serge Miranda (University of Nice Sophia Antipolis, France)
Location: Hamilton 516, 517
As the enthusiasm for and sucess of the Internet of Things (IoT), Cyber-Physical Systems (CPS), and Smart Buildings grows, so too does the volume and variety of data collected by these systems. How do we ensure that this data is of high quality, and how do we maximize the utility of collected data such that many projects can benefit from the time, cost, and effort of deployments?
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 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.
Workshop paper submission link: https://data19.hotcrp.com
- Shijia Pan (Carnegie Mellon University, USA)
- Pat Pannuto (University of California at Berkeley, USA)
- Flora Salim (RMIT University, Australia)
- Mikkel Baun Kjærgaard (University of Southern Denmark, Denmark)
Building Metadata Normalization with Plaster
Building metadata is one of the foundations of deploying applications and conducting research on buildings. Over the last four years at BuildSys, we have presented a series of effort in tackling the building metadata challenge --- from Brick [5, 6, 7], a unified metadata schema, to various algorithms (Scrabble , Zodiac , and BuildingAdapter ) for normalizing building metadata. While these works have promised to facilitate the conversion of metadata in existing buildings into Brick, actual users with not much programming experience, such as building managers, are still lacking a practical tool that provides these algorithms in their work life.
To this end, we have designed and developed Plaster  and Plaster Web Service . In particular, Plaster is a Python library including recent metadata normalization algorithms and provides a unified interface to them, which enables benchmarking and integration of different algorithms as well as development of new ones with regard to the standardized programming model. Using Plaster’s Python interfaces, Plaster Web Service provides a user-friendly web interface for non-programmer users to easily explore the state-of-art metadata normalization algorithms.
In this tutorial, we present an overview of the metadata normalization workflow and a couple of algorithms in Plaster. We will also go over Plaster Web Service to help users understand the underlying mechanisms and workflow. Plaster WebService is freely available at https://plaster.ucsd.edu.
- Plaster: An integration, benchmark, and development framework for metadata normalization methods (BulidSys 2018)
- Scrabble: transferrable semi-automated semantic metadata normalization using intermediate representation (BuildSys 2018)
- Zodiac: Organizing large deployment of sensors to create reusable applications for buildings (BuildSys 2015)
- The Building Adapter: Towards quickly applying building analytics at scale (BuildSys 2015)
- Brick: Towards a unified metadata schema for buildings (BuildSys 2016)
- Brick: Metadata schema for portable smart building applications (Applied Energy 2018)
- Beyond a House of Sticks: Formalizing Metadata Tags with Brick (BuildSys 2019)
- Demo Abstract: Interactive Building Metadata Normalization with Plaster (BuildSys 2019)
- Jason Koh (University of California, San Diego)
- Dezhi Hong (University of California, San Diego)
- Rajesh Gupta (University of California, San Diego)
- Yuvraj Agarwal (Carnegie Mellon University)