Occupancy Detection via Environmental Sensing

@article{Jin2018OccupancyDV,
  title={Occupancy Detection via Environmental Sensing},
  author={Ming Jin and Nikolaos Bekiaris-Liberis and Kevin Weekly and Costas J. Spanos and Alexandre M. Bayen},
  journal={IEEE Transactions on Automation Science and Engineering},
  year={2018},
  volume={15},
  pages={443-455},
  url={https://api.semanticscholar.org/CorpusID:4600376}
}
Sensing by proxy (SbP) is proposed in this paper as a sensing paradigm for occupancy detection, where the inference is based on “proxy” measurements such as temperature and CO2 concentrations, which holds considerable potential for energy saving and improvement of HVAC operations.
View on IEEE
bayen.eecs.berkeley.edu
121 Citations
Highly Influential Citations
1
Background Citations
41
Methods Citations
14

Figures and Tables from this paper

121 Citations

Indoor environmental quality monitoring by autonomous mobile sensing

The study develops spatio-temporal interpolation methods based on ST binning, global trend extraction, and local variation estimation, which efficiently use the data to construct accurate depiction of the indoor environment evolution.

Cognitive validation map for early occupancy detection in environmental sensing

Opportunistic occupancy-count estimation using sensor fusion: A case study

Light Sensor Based Occupancy Estimation via Bayes Filter With Neural Networks

Results indicate that the proposed Bayes filter outperforms all the benchmark approaches, and the number of sensing units should be chosen based on the required performance and the SLFN is sufficient for this application.

Incorporating SLAM and mobile sensing for indoor CO2 monitoring and source position estimation

Virtual Occupancy Sensing: Using Smart Meters to Indicate Your Presence

It is shown that power usage contains valuable and sensitive user information, demonstrating a virtual occupancy sensing approach with minimal system calibration and setup, as motivated by difficulties in ground truth collection.

Measuring Indoor Occupancy through Environmental Sensors: A Systematic Review on Sensor Deployment

This systematic review provides an overview of the type of environmental sensors used to detect/estimate occupancy, the places that have been selected to carry out experiments, details about the placement of the sensors, characteristics of datasets, and models/algorithms developed.

Building occupant sensing : occupancy prediction and behavior recognition

This thesis proposes four frameworks based on feature learning to perform occupancy level prediction and occupant behavior recognition and demonstrates that when the time-domain data is combined with frequency-domain ones, it could provide much valuable information during the feature extraction process to improve the performance of the classification of occupancy levels.

MODES: Multi-sensor occupancy data-driven estimation system for smart buildings

MODES, a Multi-sensor Occupancy Data-driven Estimation System for Smart Buildings shows that MODES can save up to 77% of energy use in a building while improving the quality of comfort by 10%.

Real-time occupancy detection with physics-informed pattern-recognition machines based on limited CO2 and temperature sensors

...

41 References

Sensing by Proxy : Occupancy Detection Based on Indoor CO 2 Concentration

Sensing by proxy, as described in this study, is a sensing paradigm which infers latent factors by “proxy” measurements based on constitutive models that exploit the spatial and physical features in…

Estimation of building occupancy levels through environmental signals deconvolution

This work addresses the problem of estimating the occupancy levels in rooms using the information available in standard HVAC systems with both online and offline estimators; the latter is shown to perform favorably compared to other data-based building occupancy estimators.

An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

Occupancy detection through an extensive environmental sensor network in an open-plan office building

A study to develop algorithms for occupancy number detection based on the analysis of environmental data captured from existing sensors and ambient sensing networks in the Robert L. Preger Intelligent Workplace at Carnegie Mellon University.

Building occupancy detection through sensor belief networks

A sensor-utility-network method for estimation of occupancy in buildings

It is found that the average estimation error at the building level is reduced from 70% to 11% using the SUN estimator, when compared to the naive approach that relies solely on flow measurements.

Regularized Deconvolution-Based Approaches for Estimating Room Occupancies

The object of this study is the reconstruction of occupancy patterns in a room using measurements of concentration, temperature, fresh air inflow, and door opening/closing events, which are information sources often available in HVAC systems of modern buildings and homes.

CO2 based occupancy detection algorithm: Experimental analysis and validation for office and residential buildings

ThermoSense: Occupancy Thermal Based Sensing for HVAC Control

This paper demonstrates ThermoSense, a new system for estimating occupancy that can condition rooms based on usage and shows that it can save 25% energy annually while maintaining room temperature effectiveness.

Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models

...

Related Papers

Showing 1 through 3 of 0 Related Papers