[HTML][HTML] Deep and transfer learning for building occupancy detection: A review and comparative analysis
The building internet of things (BIoT) is quite a promising concept for curtailing energy
consumption, reducing costs, and promoting building transformation. Besides, integrating …
consumption, reducing costs, and promoting building transformation. Besides, integrating …
Deep learning-based real-time building occupancy detection using AMI data
Building occupancy patterns facilitate successful development of the smart grid by
enhancing building-to-grid integration efficiencies. Current occupancy detection is limited by …
enhancing building-to-grid integration efficiencies. Current occupancy detection is limited by …
Integrated sensor data processing for occupancy detection in residential buildings
Based on the data from US Energy Information Administration (EIA), the total annual energy
consumed by buildings in the United States has increased by 325% over the past 70 years …
consumed by buildings in the United States has increased by 325% over the past 70 years …
[HTML][HTML] From time-series to 2d images for building occupancy prediction using deep transfer learning
Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …
maintaining the end-user comfort level. Energy conservation becomes essential since …
Building occupancy estimation with environmental sensors via CDBLSTM
Buildings consume quite a lot of energy; hence, the issue of building energy efficiency has
attracted a great deal of attention in recent years. A key factor in achieving this objective is …
attracted a great deal of attention in recent years. A key factor in achieving this objective is …
Smart spaces: occupancy detection using adaptive back-propagation neural network
In recent years, the concept of smart spaces and occupancy detection is crucial for creating
more efficient and sustainable buildings that prioritize both energy efficiency and occupant …
more efficient and sustainable buildings that prioritize both energy efficiency and occupant …
Fusion of nonintrusive environmental sensors for occupancy detection in smart homes
L Zimmermann, R Weigel… - IEEE Internet of Things …, 2017 - ieeexplore.ieee.org
We presented an approach to detect and count occupants using a fusion of environmental
sensors from an indoor air quality measurement system. Environmental sensors, as …
sensors from an indoor air quality measurement system. Environmental sensors, as …
A vision-based deep learning approach for the detection and prediction of occupancy heat emissions for demand-driven control solutions
This paper introduces a vision-based deep learning approach that enables the detection
and recognition of occupants' activities within building spaces. The data can feed into …
and recognition of occupants' activities within building spaces. The data can feed into …
A computer vision-based occupancy and equipment usage detection approach for reducing building energy demand
Because of extensive variations in occupancy patterns around office space environments
and their use of electrical equipment, accurate occupants' behaviour detection is valuable …
and their use of electrical equipment, accurate occupants' behaviour detection is valuable …
Occupancy prediction using deep learning approaches across multiple space types: A minimum sensing strategy
The proliferation of sensing technologies has allowed the collection of occupancy-related
data to support various building applications, including adaptive HVAC and lighting controls …
data to support various building applications, including adaptive HVAC and lighting controls …