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  1. Proceedings of the Seventh International Conference on Future Energy Systems Poster Sessions (e-Energy '16)
  2. Observability: replacing sensors with inference engines
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In-situ sensor network for microclimate and urban energy modeling and validation
A framework for occupancy-aided energy disaggregation
Decentralized optimization of energy exchanges in an electricity microgrid
Inferring non-outage events using meter voltage data
Optimizing energy costs of commercial buildings in developing countries
Towards constraint-based aggregation of energy flexibilities
Combining data with physics to monitor solar panels
SunShade: software-defined solar systems
Observability: replacing sensors with inference engines
Harmoney: saving energy costs in buildings through harmonic current mitigation
Multiple time-scale model predictive control for thermal comfort in buildings
Collect, compare, and score: a generic data-driven anomaly detection method for buildings

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Observability: replacing sensors with inference engines

Content Provider ACM Digital Library
Author Ramamritham, Krithi Agarwal, Anshul Ajay Munigala, Vitobha
Abstract Sensor driven building management involves tasks like reducing and optimizing power consumption, monitoring the health of the building appliances, maintaining quality of the atmosphere in the building and tracking occupants in various parts of the building (useful for purposes such as building safety and emergency evacuation), to name a few. But, installing numerous sensors in different parts of the building can a) be tedious and expensive b) cause inconvenience to the users c) increase the payback period and, d) affect the aesthetics of the building. The fact that a sensor, suitable for observing a particular facet, may in turn help to infer other facets can be exploited to reduce the number of physical sensors deployed in a building. We have applied our approach to monitor various facets in our academic building and show that impressive reductions are possible, in the number of hard sensors needed, without compromising on observability.
Starting Page 1
Ending Page 2
Page Count 2
File Format PDF
ISBN 9781450344173
DOI 10.1145/2939912.2942356
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-06-21
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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