Time-to-scene for opioid overdoses: are unmanned aerial drones faster than traditional first responders in an urban environment?

2020 ◽  
Vol 6 (4) ◽  
pp. 204-208
Author(s):  
Connor Andrew Tukel ◽  
Matthew Ryan Tukel ◽  
Robert Jacob Weinbaum ◽  
Valerie H Mika ◽  
Phillip D Levy
Keyword(s):  
Response Time ◽  
Emergency Response ◽  
Opioid Overdose ◽  
Time Data ◽  
Arrival Times ◽  
Straight Line ◽  
Life Saving ◽  
Rural Settings ◽  
Prospective Trials ◽  
Time Required

IntroductionOpioid overdoses claim tens of thousands of lives every year. Many of these deaths might be prevented if overdose-reversal medications such as naloxone are administered in a timely manner. Drones may help overcome barriers to timely arrival on scene for opioid overdoses. This study analyses the time required for a drone carrying naloxone to traverse various distances, simulating the response time for a drone to the scene of an opioid overdose. For comparison, we used the time required for ambulances to traverse similar distances while responding to the scene of actual or suspected opioid overdoses.MethodsFifty flight trials, using a modified Dà-Jiāng Innovations (DJI) ‘Inspire 2’ drone, were conducted across seven distances, and the travel time for the drone was then compared with historical response time data from 200 actual or suspected opioid overdose cases that occurred within Detroit, Michigan.ResultsWe determined with 95% certainty that drone arrival times were discernibly quicker than ambulance arrival times at all distances where sufficient data were available to perform statistical comparisons including 0.5 km, 1.0 km, 1.5 km, 2.0 km and 3.0 km.ConclusionWe have shown that a drone is capable of travelling several ranges of straight-line (ie, ‘as the crow flies’) distance faster than an ambulance. Further exploration into the use of drones to deliver life-saving therapies in urban and rural settings is warranted. Head-to-head prospective trials that consider the practical challenges of medical drone delivery are needed to better understand the viability of incorporating this technology into existing emergency response infrastructure.

Travel times from central Pacific nuclear explosions and inferred mantle structure

1964 ◽  
Vol 54 (6B) ◽  
pp. 2271-2294
Author(s):  
Dean S. Carder
Keyword(s):  
Single Point ◽  
P Wave ◽  
Graphical Form ◽  
Travel Times ◽  
Time Data ◽  
Central Pacific ◽  
Arrival Times ◽  
Nuclear Explosions ◽  
Straight Line ◽  
Travel Time Data

Abstract Travel time data, from widely recorded nuclear detonations in the Eniwetok and Bikini atolls of the central Pacific, have been compiled and are presented. Although a number of stations recorded ten or more events from each atoll, the resulting data may be considered as from a single point source, precisely known in time and place. Composite P-wave travel times are presented in a graphical form and, in the distance range from 3 to 102 degrees, are represented as eight near straight-line segments. P-wave speeds in the top of the mantle average about 8.2 km/sec to distances beyond 17 degrees, and a sharp discontinuity at 19.5 degrees is indicated. There is no evidence for or against a low-speed layer in the upper mantle nor for a regional shadow zone. A mantle model consisting of a number of discrete spherical shells has been constructed. A core depth of 2,870 km, 30 km short of the accepted value, is calculated from PcP arrival times at Matsushiro and College, which are 2.5 and 3.5 sec. earlier than are indicated in the Jeffreys-Bullen tables.

Time required to notify 9-1-1 with automated collision notification systems

2007 ◽  
Vol 5 (5) ◽  
pp. 43
Author(s):  
Alan J. Blatt, BS, MEng ◽  
Dietrich Von Kuenssberg Jehle, MD, FACEP ◽  
Anthony J. Billittier IV, MD, FACEP ◽  
David G. Wagner, MD ◽  
Jill Schleifer-Schneggenburger, BS, MEng
Keyword(s):  
Confidence Interval ◽  
Response Time ◽  
Emergency Response ◽  
Field Test ◽  
Traditional Method ◽  
Motor Vehicle ◽  
Motor Vehicle Crash ◽  
Percent Confidence Interval ◽  
System A ◽  
Time Required

Background: Automated Collision Notification (ACN) systems reduce emergency response time to a vehicular crash by immediately alerting a Public Safety Answering Point (PSAP) of the collision and its details.Methods: An operational field test was performed to evaluate the effectiveness and reliability of the ACN system: a total of 874 vehicles were equipped with ACN systems and, for a period of 29 months, all collisions involving these vehicles were included in a study of the automatic notification time. Fifteen collisions of ACN-equipped vehicles registered with a PSAP. Both the time for the ACN notification to be received and the time for a traditional method of notification to be received were recorded for each crash.Results: The ACN notified a PSAP of a collision in an average time of 74.2 seconds and between 79.9 and 456.1 seconds sooner than a traditional notification method (paired mean difference 95 percent confidence interval).Conclusion: The ACN system significantly improves emergency notification time to a motor vehicle crash.

Modeling operators' emergency response time for chemical processing operations

2014 ◽  
Vol 12 (6) ◽  
pp. 479
Author(s):  
Susan L. Murray, PhD ◽  
Emrah Harputlu, MS ◽  
Ray A. Mentzer, PhD ◽  
M. Sam Mannan, PhD
Keyword(s):  
Response Time ◽  
Emergency Response ◽  
Industrial Engineering ◽  
Time Range ◽  
Chemical Processing ◽  
Emergency Situations ◽  
Time Requirements ◽  
Corrective Actions ◽  
Time Required ◽  
Time Standard

Operators have a crucial role during emergencies at a variety of facilities such as chemical processing plants. When an abnormality occurs in the production process, the operator often has limited time to either take corrective actions or evacuate before the situation becomes deadly. It is crucial that system designers and safety professionals can estimate the time required for a response before procedures and facilities are designed and operations are initiated.There are existing industrial engineering techniques to establish time standards for tasks performed at a normal working pace. However, it is reasonable to expect the time required to take action in emergency situations will be different than working at a normal production pace. It is possible that in an emergency, operators will act faster compared to a normal pace. It would be useful for system designers to be able to establish a time range for operators' response times for emergency situations. This article develops a modeling approach to estimate the time standard range for operators taking corrective actions or following evacuation procedures in emergency situations. This will aid engineers and managers in establishing time requirements for operators in emergency situations.The methodology used for this study combines a well-established industrial engineering technique for determining time requirements (predetermined time standard system) and adjustment coefficients for emergency situations developed by the authors. Numerous videos of workers performing well-established tasks at a maximum pace were studied. As an example, one of the tasks analyzed was pit crew workers changing tires as quickly as they could during a race. The operations in these videos were decomposed into basic, fundamental motions (such as walking, reaching for a tool, and bending over) by studying the videos frame by frame. A comparison analysis was then performed between the emergency pace and the normal working pace operations to determine performance coefficients. These coefficients represent the decrease in time required for various basic motions in emergency situations and were used to model an emergency response. This approach will make hazardous operations requiring operator response, alarm management, and evacuation processes easier to design and predict. An application of this methodology is included in the article. The time required for an emergency response was roughly a one-third faster than for a normal response time.

Using response time data to reduce testing time in cognitive tests.

2018 ◽  
Vol 30 (3) ◽  
pp. 328-338 ◽  
Author(s):  
Maria Bertling ◽  
Jonathan P. Weeks
Keyword(s):  
Response Time ◽  
Response Time Data ◽  
Testing Time ◽  
Cognitive Tests ◽  
Time Data

scholarly journals Comparison of Forest Inventory Methods at Plot-Level between a Backpack Personal Laser Scanning (BPLS) and Conventional Equipment in Jeju Island, South Korea

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 308
Author(s):  
Chiung Ko ◽  
Seunghyun Lee ◽  
Jongsu Yim ◽  
Donggeun Kim ◽  
Jintaek Kang
Keyword(s):  
South Korea ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Jeju Island ◽  
Time Data ◽  
Non Invasive ◽  
Coniferous Plantation ◽  
Standing Trees ◽  
Time Required ◽  
Inventory Method

In recent years, light detection and ranging (LiDAR) has been increasingly utilized to estimate forest resources. This study was conducted to identify the applicability of a LiDAR sensor for such estimations by comparing data on a tree’s position, height, and diameter at breast height (DBH) obtained using the sensor with those by existing forest inventory methods for a Cryptomeria japonica forest in Jeju Island, South Korea. For this purpose, a backpack personal laser scanning device (BPLS, Greenvalley International, Model D50) was employed in a protected forest, where cutting is not allowed, as a non-invasive means, simultaneously assessing the device’s field applicability. The data collected by the sensor were divided into seven different pathway variations, or “patterns” to consider the density of the sample plots and enhance the efficiency. The accuracy of estimating the variables of each tree was then assessed. The time spent acquiring and processing real-time data was also analyzed for each method, as well as total time and the time required for each measurement. The findings showed that the rate of detection of standing trees by LiDAR was 100%. Additionally, a high statistical accuracy was observed in pattern 5 (DBH: RMSE 1.22 cm, bias—0.90 cm, Height: RMSE 1.66 m, bias—1.18 m) and pattern 7 (DBH: RMSE 1.22 cm, bias—0.92 cm, Height: RMSE 1.48 m, bias—1.23 m) compared to the results from the typical inventory method. A range of 115–162.5 min/ha was required to process the data using the LiDAR, while 322.5–567.5 min was required for the typical inventory method. Thus, the application of a backpack personal LiDAR can lead to higher efficiency when conducting a forest resource inventory in a coniferous plantation with understory vegetation. Further research in various stands is necessary to confirm the efficiency of using backpack personal laser scanning.

Decision-making by laypersons equipped with an emergency response smartphone app for opioid overdose

2021 ◽  
Vol 95 ◽  
pp. 103250
Author(s):  
Janna Ataiants ◽  
Megan K. Reed ◽  
David G. Schwartz ◽  
Alexis Roth ◽  
Gabriela Marcu ◽  
...  
Keyword(s):  
Decision Making ◽  
Emergency Response ◽  
Smartphone App ◽  
Opioid Overdose

scholarly journals Dynamic Computation Offloading Scheme for Drone-Based Surveillance Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2982 ◽  
Author(s):  
Bongjae Kim ◽  
Hong Min ◽  
Junyoung Heo ◽  
Jinman Jung
Keyword(s):  
Response Time ◽  
Target Object ◽  
Computation Offloading ◽  
Moving Target ◽  
Surveillance Systems ◽  
Network Failure ◽  
Dynamic Computation ◽  
Tracking Time ◽  
Time Required ◽  
Time Critical

Recently, various technologies for utilizing unmanned aerial vehicles have been studied. Drones are a kind of unmanned aerial vehicle. Drone-based mobile surveillance systems can be applied for various purposes such as object recognition or object tracking. In this paper, we propose a mobility-aware dynamic computation offloading scheme, which can be used for tracking and recognizing a moving object on the drone. The purpose of the proposed scheme is to reduce the time required for recognizing and tracking a moving target object. Reducing recognition and tracking time is a very important issue because it is a very time critical job. Our dynamic computation offloading scheme considers both the dwell time of the moving target object and the network failure rate to estimate the response time accurately. Based on the simulation results, our dynamic computation offloading scheme can reduce the response time required for tracking the moving target object efficiently.

scholarly journals An Extended Rule of the SysML Requirement Diagram Transformation into OWL Ontologies

2021 ◽  
Vol 14 (1) ◽  
pp. 506-515
Author(s):  
Ahmad Ashari ◽  
◽  
Anny Sari ◽  
Helna Wardhana ◽  
◽  
...  
Keyword(s):  
Response Time ◽  
System Modeling ◽  
Unified Modeling Language ◽  
Modeling Language ◽  
Functional Requirements ◽  
Unified Modeling ◽  
Object Property ◽  
Transformation Rules ◽  
Owl Ontology ◽  
Time Required

The System Modeling Language (SysML) used the Requirement Diagram to model non-functional requirements, such as response time, size, or system functionality, which cannot be accommodated in the Unified Modeling Language (UML). SysML Requirement Diagram, in its implementation, integrates with several diagrams describing the requirements, which are referred to as additional elements. The absence of transformation rules for these additional elements to become OWL ontology causes difficulties in reading, understanding, and tracking the requirements. In this research, an extended rule of the Requirement Diagram transformation is proposed to solve the problems. First, some transformation rules are defined to make requirements easier to trace and realize the ontology generation's automatic transformation. Second, the time required during transformation processing to prepare and generate the OWL file shows the proposed model's performance. The ontology components produced from this research, such as class, subclass, object property, and data property, can be viewed in Protégé.

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