scholarly journals SIGPRO: A Real-Time Progressive Notification System Using MQTT Bridges and Topic Hierarchy for Rapid Location of Missing Persons

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 149190-149198
Author(s):  
Ana Maria Zambrano V ◽  
Marcelo Zambrano V ◽  
Eduardo Luis Ortiz Mejia ◽  
Xavier Calderon H
Keyword(s):  
Real Time ◽  
Notification System ◽  
Missing Persons ◽  
Topic Hierarchy

scholarly journals An Internet of Things Buttons to Measure and Respond to Restroom Cleanliness in a Hospital Setting: Descriptive Study (Preprint)

2019 ◽  
Author(s):  
Peter R Chai ◽  
Haipeng Zhang ◽  
Guruprasad D Jambaulikar ◽  
Edward W Boyer ◽  
Labina Shrestha ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Reporting System ◽  
Hospital Setting ◽  
Time Of Day ◽  
Notification System ◽  
Main Hospital ◽  
Qualitative Feedback ◽  
System P ◽  
Actual Use

BACKGROUND Restroom cleanliness is an important factor in hospital quality. Due to its dynamic process, it can be difficult to detect the presence of dirty restrooms that need to be cleaned. Using an Internet of Things (IoT) button can permit users to designate restrooms that need cleaning and in turn, allow prompt response from housekeeping to maintain real-time restroom cleanliness. OBJECTIVE This study aimed to describe the deployment of an IoT button–based notification system to measure hospital restroom cleanliness reporting system usage and qualitative feedback from housekeeping staff on IoT button use. METHODS We deployed IoT buttons in 16 hospital restrooms. Over an 8-month period, housekeeping staff received real-time notifications and responded to button presses for restroom cleaning. All button presses were recorded. We reported average button usage by hospital area, time of day, and day of week. We also conducted interviews with housekeeping supervisors and staff to understand their acceptance of and experience with the system. RESULTS Over 8 months, 1920 requests to clean restrooms in the main hospital lobby and satellite buildings were received. The hospital lobby IoT buttons received over half (N=1055, 55%) of requests for cleaning. Most requests occurred in afternoon hours from 3 PM to midnight. Requests for cleaning remained stable throughout the work week with fewer requests occurring over weekends. IoT button use was sustained throughout the study period. Interviews with housekeeping supervisors and staff demonstrated acceptance of the IoT buttons; actual use was centered around asynchronous communication between supervisors and staff in response to requests to clean restrooms. CONCLUSIONS An IoT button system is a feasible method to generate on-demand request for restroom cleaning that is easy to deploy and that users will consistently engage with. Data from this system have the potential to enable responsive scheduling for restroom service and anticipate periods of high restroom utilization in a hospital.

Gisola: A High-Performance Computing Application for Real-Time Moment Tensor Inversion

2021 ◽  
Author(s):  
Nikolaos Triantafyllis ◽  
Ioannis E. Venetis ◽  
Ioannis Fountoulakis ◽  
Erion-Vasilis Pikoulis ◽  
Efthimios Sokos ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Real Time ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
Moment Tensor ◽  
Time Moment ◽  
Parallel Execution ◽  
Waveform Data ◽  
Notification System ◽  
Performance Computing

Abstract Automatic moment tensor (MT) determination is essential for real-time seismological applications. In this article, Gisola, a highly evolved software for MT determination, oriented toward high-performance computing, is presented. The program employs enhanced algorithms for waveform data selection via quality metrics, such as signal-to-noise ratio, waveform clipping, data and metadata inconsistency, long-period disturbances, and station evaluation based on power spectral density measurements in parallel execution. The inversion code, derived from ISOLated Asperities—an extensively used manual MT retrieval utility—has been improved by exploiting the performance efficiency of multiprocessing on the CPU and GPU. Gisola offers the ability for a 4D spatiotemporal adjustable MT grid search and multiple data resources interconnection to the International Federation of Digital Seismograph Networks Web Services (FDSNWS), the SeedLink protocol, and the SeisComP Data Structure standard. The new software publishes its results in various formats such as QuakeML and SC3ML, includes a website suite for MT solutions review, an e-mail notification system, and an integrated FDSNWS-event for MT solutions distribution. Moreover, it supports the ability to apply user-defined scripts, such as dispatching the MT solution to SeisComP. The operator has full control of all calculation aspects with an extensive and adjustable configuration. MT’s quality performance, for 531 manual MT solutions in Greece between 2012 and 2021, was measured and proved to be highly efficient.

scholarly journals Development of a real-time general medicine 30-day readmissions notification system

2012 ◽  
Vol 2 (1) ◽  
pp. 28
Author(s):  
Jonathan Bae ◽  
Thomas Owens ◽  
Jeffrey M. Ferranti ◽  
William Gilbert ◽  
Ilona Stashko ◽  
...  
Keyword(s):  
Real Time ◽  
Practice Patterns ◽  
Hospital Readmissions ◽  
General Medicine ◽  
Return Time ◽  
Care Providers ◽  
Notification System ◽  
Targeted Interventions ◽  
Average Return ◽  
Populations At Risk

Hospital readmissions present a costly problem for healthcare systems. Engaging care providers in reviewing readmissions may reveal opportunities for reducing readmissions and improving quality. We developed a real-time alerting method that e-mails providers when a discharged patient returns for care (emergency department [ED] or hospital admission) within 30 days. We analyzed the content of alerts to consider frequency of presentation and demographic characteristics of readmitted patients. From 3/15/2011 to 8/31/2011, 1544 alerts (943 ED returns; 601 inpatient readmissions) were generated, representing 621 unique patients (average return time: 12.8±8.5 days). Forty-eight faculty received alerts; 88.8% of alerts were sent to the correct discharging provider. Real-time alerting allows providers to re-engage with readmitted patients and offers a means for evaluating performance. Such systems may also elucidate reasons for readmission by detailing practice patterns and populations at risk for readmission as well as help to design targeted interventions to reduce hospital returns.

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