The of the Emergency vehicle from inside

The Android-GPS wireless application concept is based on the established research around poor pick-up rates of ERV sirens by drivers and the speculation that the wireless-GPS sort alert will be accessible at longer distances from the Emergency vehicle’s location which will enable timely corrective action by vehicular traffic. To overcome this problem of pick-up rates of ERV sirens we are sending the GPS coordinates of the ERV vehicles to the nearby users so that they can make way for the ERV vehicles.  The primary alert mechanism used by ERV’s worldwide is Sirens which have severe limitations. According to the Studies in the US, if the Emergency vehicle is about 100 meters away from the vehicle traveling at the speed of 60km/hour can’t hear the ERV’s siren assuming that there is no car radio or air-conditioner noise. In noisy conditions even if the ERV is within a distance of 1-2 meters the drivers can’t hear the ERV’s siren. According to US Dot, it is said that only 26% of the people can correctly determine the direction of the Emergency vehicle from inside a closed car and if the issues like traffic jams and high road noise are added then the probability of the driver hearing the ERV’s siren is even low. The main reason for the increase in the traffic congestion and transportation delays is the increase in the number of vehicles on the road. Emergency vehicles such as ambulances and fire engines should be capable of reacting to the emergency calls with minimum delay. The performance of the emergency services depends on how early the emergency vehicles can reach the desired destination. If the emergency vehicle gets stuck in a traffic jam and its arrival at the indicated destination is delayed it can cause loss of lives and property.   Motivation:  World Health Organization recommends a standard response time of 8-10 minutes for an ambulance which means that once the request for an emergency vehicle has been made, it must reach the intended destination, within under 10 minutes of time. Given the overall lag in emergency services, the response time is far from ideal.  If an emergency vehicle appears suddenly appears which is on its way to the intended destination can cause a problem to the nearby vehicles as individual drivers manipulate his movements to get out of the way. Many drivers will get confused and create conflicts that can cause the emergency vehicle to crash or block lanes which in turn increase the response times.  II. Specific Aims:  Creation of an android application used for the notification of the Emergency vehicle’s location to all the users driving vehicles within a radius of 3 miles from the ERV’s. The android application is used for locating all the ERVs within the 3 miles radius from user’s location. The location is retrieved in the form of latitude and longitude values from the GPS embedded in the Android devices.  The implementation of this system is divided into the multiple-client single-server architecture to centralize computing at the server end. Client:  The client in our system is the Android application used by the public as well as the emergency vehicle driver. The android application is developed using Android Studio IDE. The application consists of two parts for different users: • Public users: Upon the immediate access of the Android application, the application periodically updates the user’s location to the cloud server. The application also continually retrieves the ambulance’s location sent by the server, alerts the user through notifications in the first event of a new ambulance location being retrieved from the server and plots them onto Google maps. The location transmission to the server as well as the reception from the server terminates when the user closes the application.  • Emergency vehicle driver: The driver of the Emergency vehicle is required to login to the Android application through a secure PIN to confirm his/her authentication before the start of the ride. After a successful login, the Emergency vehicle’s location continually updates to the cloud server. The Emergency vehicle stops updating its location to the server when the Emergency vehicle driver selects the “STOP RIDE” option on the application. Server:  The server is developed using the XAMP software. It retrieves the location of all the ambulances making a ride as well as the location of all the users of the application. With this data, it computes the users of the application whose location is contained within a radius of 3 miles from the ambulance. Finally, the location of the ambulance is sent to these users.  III. Background and Significance:  Many cities in the developing countries are trying very hard to transform themselves into smart cities but for a city to be called as Smart City, it should have all possible advancement in the sector of smart technology. Healthcare sector includes getting Emergency Vehicle within a minimum amount of time, providing proper facilities and improving the efficiency of this sector is one of the most difficult and challenging jobs. But in urban areas, the traffic congestion causes many hitches for the Emergency Vehicle.  Meeting the required paramedic reaction time is an imperative marker of quality emergency medical care. Heart failure is one of the profoundly time-delicate medical situations which force a request to enhance the response time of medical care services. The national average EMS response time in the United States is far over the eight-minute standard which is predominantly because of the time delays happening in the communication among 911 callers, First Responders, Public Safety Answering Points and street traffic vulnerability. These postponements can prompt an increase in response time of emergency vehicles. The present Emergency Medical Service response system is subjected to time postpones engaged in wireless communication, transportation and vulnerability factors. These different time delays are highly subjected to technical constraints, for example, questionable GPS situating of wireless calls and restricted level of traffic preemption, and are additionally intensified by miscommunications and dialect barriers.

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