Improving Indoor Occupancy Detection Accuracy of the SLEEPIR Sensor Using LSTM Models
Not provided.
Engineering↗
Engineering topics
Wang, Ya
Publications and source records attributed to Wang, Ya.
Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review
In the past decade, different sensing mechanisms and algorithms have been developed to detect or estimate indoor occupancy. One of the most recent advancements is using networked sensor nodes to create a more comprehensive occupancy detection system where multiple sensors can identify human presence within more expansive areas while delivering enhanced accuracy compared to a system that relies on stand-alone sensor nodes. The present work reviews the studies from 2012 to 2022 that use networked sensor nodes to detect indoor occupancy, focusing on PIR-based sensors. Methods are compared based on pivotal ADPs that play a significant role in selecting an occupancy detection system for applications such as Health and Safety or occupant comfort. These parameters include accuracy, information requirement, maximum sensor failure and minimum observation rate, and feasible detection area. We briefly describe the overview of occupancy detection criteria used by each study and introduce a metric called “sensor node deployment density” through our analysis. This metric captures the strength of network-level data filtering and fusion algorithms found in the literature. It is hinged on the fact that a robust occupancy estimation algorithm requires a minimal number of nodes to estimate occupancy. This review only focuses on the occupancy estimation models for networked sensor nodes. It thus provides a standardized insight into networked nodes’ occupancy sensing pipelines, which employ data fusion strategies, network-level machine learning algorithms, and occupancy estimation algorithms. This review thus helps determine the suitability of the reviewed methods to a standard set of application areas by analyzing their gaps.
Emad-Ud-Din, Muhammad (ORCID:0000000279515538)↗
An overactivated ATR/CHK1 pathway is responsible for the prolonged G2 accumulation in irradiated AT cells
Induction of checkpoint responses in G1, S, and G2 phases of the cell cycle after exposure of cells to ionizing radiation (IR) is essential for maintaining genomic integrity. Ataxia telangiectasia mutated (ATM) plays a key role in initiating this response in all three phases of the cell cycle. However, cells lacking functional ATM exhibit a prolonged G2 arrest after IR, suggesting regulation by an ATM-independent checkpoint response. The mechanism for this ataxia telangiectasia (AT)-independent G2-checkpoint response remains unknown. We report here that the G2 checkpoint in irradiated human AT cells derives from an overactivation of the ATR/CHK1 pathway. Chk1 small interfering RNA abolishes the IR-induced prolonged G2 checkpoint and radiosensitizes AT cells to killing. These results link the activation of ATR/CHK1 with the prolonged G2 arrest in AT cells and show that activation of this G2 checkpoint contributes to the survival of AT cells.
NASA Discipline Radiation Health↗
An ATM-independent S-phase checkpoint response involves CHK1 pathway
After exposure to genotoxic stress, proliferating cells actively slow down the DNA replication through a S-phase checkpoint to provide time for repair. We report that in addition to the ataxia-telangiectasia mutated (ATM)-dependent pathway that controls the fast response, there is an ATM-independent pathway that controls the slow response to regulate the S-phase checkpoint after ionizing radiation in mammalian cells. The slow response of S-phase checkpoint, which is resistant to wortmannin, sensitive to caffeine and UCN-01, and related to cyclin-dependent kinase phosphorylation, is much stronger in CHK1 overexpressed cells, and it could be abolished by Chk1 antisense oligonucleotides. These results provide evidence that the ATM-independent slow response of S-phase checkpoint involves CHK1 pathway.
Non-NASA Center↗