The Effect of a “Design-of-Awareness” Process on Recognition of AVAS Sound of Quiet Vehicles

The development of quiet vehicles, such as hybrid and electric vehicles, has environmental benefits. However, the quietness of these vehicles may increase the risk to pedestrians, particularly those with visual impairment. We hypothesized that a “design-of-awareness” process based on the concept of sound education for hearing and recognizing the sound generated by the Acoustic Vehicle Alerting System (AVAS) installed in quiet vehicles may change peoples’ attitudes toward the sound and improve their ability to detect it. To verify this hypothesis, two experiments using a quiet vehicle were conducted to examine whether participants were able to detect the AVAS sound. The results revealed that few participants were initially able to detect the AVAS sound. After the design-of-awareness process was conducted, 1 and 3 month follow-up surveys were conducted to clarify its effects and longevity. The results revealed that approximately half of the participants became able to detect the sound, and that their attitudes toward the sound were changed. In addition, the number of participants who were able to detect the sound increased over time. These results indicate that a design-of-awareness process could be helpful for training people to detect the sound of quiet vehicles.

Real Time Tracing and Alerting System for Vehicles and Children to Ensure Safety and Security Using Labview

The Absolute time monitoring, detecting and Alerting System for vehicles and children is required to trace and transmit the collected information at regular intervals to ensure safety and security of children. The illustration of the Realtime detecting and warning System consists of two units: Tracing Unit that traces the location information, transfers to the monitoring area, records the data in the database and takes the help of these data to locate the exact point of area of the vehicle with Google/other maps. The second unit is Alerting Unit that tracks the students using active Radio Frequency Identification Devices (RFID)which will be placed on student ID card. radio-wave trans-receiver transmits a common radio wave which is received by the RFID in the ID card. This radio-wave is modified by the RFID’s coil and resent to the receive RFID tags are also used for attendance which is updated directly to the database and displays the other student information.

Incorporating a real-time automatic alerting system based on electronic medical records could improve rapid response systems: a retrospective cohort study

Background Rapid response systems (RRSs) are essential components of patient safety systems; however, limited evidence exists regarding their effectiveness and optimal structures. We aimed to assess the activation patterns and outcomes of RRS implementation with/without a real-time automatic alerting system (AAS) based on electronic medical records (EMRs). Methods We retrospectively analyzed clinical data of patients for whom the RRS was activated in the surgical wards of a tertiary university hospital. We compared the code rate, in-hospital mortality, unplanned intensive care unit (ICU) admission, and other clinical outcomes before and after applying RRS and AAS as follows: pre-RRS (January 2013–July 2015), RRS without AAS (August 2015–November 2016), and RRS with AAS (December 2016–December 2017). Results In-hospital mortality per 1000 admissions decreased from 15.1 to 12.9 after RRS implementation (p < 0.001). RRS activation per 1000 admissions increased from 14.4 to 26.3 after AAS implementation. The severity of patients’ condition calculated using the modified early warning score increased from 2.5 (± 2.1) in the RRS without AAS to 3.6 (± 2.1) (p < 0.001) in the RRS with AAS. The total and preventable code rates and in-hospital mortality rates were comparable between the RRS implementation periods without/with AAS. ICU duration and mortality results improved in patients with RRS activation and unplanned ICU admission. The data of RRS non-activated group remained unaltered during the study. Conclusions Real-time AAS based on EMRs might help identify unstable patients. Early detection and intervention with RRS may improve patient outcomes.

Real-time alerting system for COVID-19 and other stress events using wearable data

Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals. Pre-symptomatic signals were observed at a median of 3 days before symptom onset. Examination of detailed survey responses provided by the participants revealed that other respiratory infections as well as events not associated with infection, such as stress, alcohol consumption and travel, could also trigger alerts, albeit at a much lower mean frequency (1.15 alert days per person compared to 3.42 alert days per person for coronavirus disease 2019 cases). Thus, analysis of smartwatch signals by an online detection algorithm provides advance warning of SARS-CoV-2 infection in a high percentage of cases. This study shows that a real-time alerting system can be used for early detection of infection and other stressors and employed on an open-source platform that is scalable to millions of users.

Improving Lidar Windshear Detection Efficiency by Removal of “Gentle Ramps”

The Doppler Lidar windshear alerting system at the Hong Kong International Airport (HKIA), the first of its kind in the world, has been in operation since 2006. This paper reports on an enhancement to the automatic windshear detection algorithm at HKIA, which aims at filtering out alerts associated with smoother headwind changes spread over longer distances along the aircraft glide path (called “gentle ramps”) which may nonetheless exceed the well-established alerting threshold. Real-time statistics are examined over a 46-month study period between March 2016 and December 2019, covering a total of 2,017,440 min and over 1500 quality-controlled pilot reports of windshear (PIREP). The “gentle ramp removal” (GRR) function is able to effectively cut down the alert duration over the 5 major runway corridors, inclusive of both landing and take-off, which together account for over 98% of the PIREP received at HKIA during the study period. In all 5 runway corridors this is achieved with a proportionately smaller decrease—even with no changes in 2 cases—in the hit rate, highlighting the efficiency of the GRR function. The difference in statistical behaviour across the runway corridors also echo literature findings about the differences in length scale of wind disturbances at different locations within HKIA. This study serves as a unique documentation of the state-of-the-art in operational Lidar windshear detection and can provide useful reference to airports and aviation meteorologists around the world.

Prevalence of potentially harmful multidrug interactions on medication lists of elderly ambulatory patients

Background It has been hypothesized that polypharmacy may increase the frequency of multidrug interactions (MDIs) where one drug interacts with two or more other drugs, amplifying the risk of associated adverse drug events (ADEs). The main objective of this study was to determine the prevalence of MDIs in medication lists of elderly ambulatory patients and to identify the medications most commonly involved in MDIs that amplify the risk of ADEs. Methods Medication lists stored in the electronic health record (EHR) of 6,545 outpatients ≥60 years old were extracted from the enterprise data warehouse. Network analysis identified patients with three or more interacting medications from their medication lists. Potentially harmful interactions were identified from the enterprise drug-drug interaction alerting system. MDIs were considered to amplify the risk if interactions could increase the probability of ADEs. Results MDIs were identified in 1.3 % of the medication lists, the majority of which involved three interacting drugs (75.6 %) while the remainder involved four (15.6 %) or five or more (8.9 %) interacting drugs. The average number of medications on the lists was 3.1 ± 2.3 in patients with no drug interactions and 8.6 ± 3.4 in patients with MDIs. The prevalence of MDIs on medication lists was greater than 10 % in patients prescribed bupropion, tramadol, trazodone, cyclobenzaprine, fluoxetine, ondansetron, or quetiapine and greater than 20 % in patients prescribed amiodarone or methotrexate. All MDIs were potentially risk-amplifying due to pharmacodynamic interactions, where three or more medications were associated with the same ADE, or pharmacokinetic, where two or more drugs reduced the metabolism of a third drug. The most common drugs involved in MDIs were psychotropic, comprising 35.1 % of all drugs involved. The most common serious potential ADEs associated with the interactions were serotonin syndrome, seizures, prolonged QT interval and bleeding. Conclusions An identifiable number of medications, the majority of which are psychotropic, may be involved in MDIs in elderly ambulatory patients which may amplify the risk of serious ADEs. To mitigate the risk, providers will need to pay special attention to the overlapping drug-drug interactions which result in MDIs.