A Review on Minimization of Ambulance Response Time Using Image Processing and Critical path Mapping Based on Traffic Control

India is a developing country; the population of India is growing exponentially. India ranks 2nd in the world in terms of population. As there will be a gradual increase in population there will be an increase in the number of vehicles, as a result of which traffic congestion is increasing and as a result, emergency vehicles such as ambulances, fire-fighters, etc. are having difficulty getting to their destination on time. Vehicle use is growing rapidly due to recent technological and economic developments, and at the same time, the lack of infrastructure against demand is leading to an increase in the number of accidents and fatalities. Minor problems in our health system have prompted us to come up with a petition to make this process work and save lives. Through book reviews and reflections, I have proposed a project in a smart traffic management system using image processing. The aim of this project is to improve simulation to determine traffic congestion, to detect a crash/accident, and to obtain an ambulance using image processing and machine learning techniques. The proposed independent work is simulated in the form of an experimental setup using Arduino and LED displays that mimic real-time traffic. These simulation results reflect the terms of the acquisition as it provides an emergency vehicle pass to catch up on peak hours.


Introduction
Population in developing countries such as India is increasing significantly. This result in a number of problems such as heavy traffic jams, violation of the traffic rules and sometimes even accidents. For example, the number of road accidents in major cities such as Chennai, Hyderabad and Delhi increased to 16 deaths per hour, as stated by the Indian Government. Additionally, traffic congestion leads to long waiting times, fuel depletion and even money waste. In particular, traffic congestion contributes to high rates of emissions impacting the health of the local population, shuttles and animals. Traffic congestion is often commonly associated with some other traffic issues, such as the blocking of emergency vehicles. Precisely, the traffic congestion often blocks the path of the emergency vehicles which may Human Life is a very valuable thing for any country. The regular occurrence of incidents and medical emergencies such as fire, road accidents, medical emergencies etc. It is very necessary that emergency vehicles arrive on time to prevent serious loss of humans. Thus, hospitals and fire stations are throughout the city to reduce response time in case of such emergencies. A very rapid population growth in cities has resulted in tremendous road traffic within the city. In addition, in recent times the number of deaths due to delays in the arrival of emergency vehicle has risen to greater extent. Hence emergency services such as ambulances and fire engines must be on time to avoid loss of human life. In the current traffic situation, therefore, helping an emergency vehicle move out of traffic congestion is very much important. To solve the problems given above. In this paper, we have come up with the 'Smart Ambulance and traffic controlling system'. The main purpose of this device is to allow the ambulance to reach a specific location without making it stop somewhere before it reaches the destination.

Proposed System
The objective of the proposed project is to develop a simulator to determine the traffic density, ambulance, and accident incidents using image processing and machine learning techniques. In the first phase, we determined traffic density to minimize the delay caused by traffic congestion and to provide the smooth flow of vehicles. The density of vehicles on each side can be identified by using datasets. If the density is low on a particular side, the time for that side is normal and if the density is high the time will automatically increase compared to normal density. The second phase work simulates a crash or accident detection and for the prototype consideration, used static accidental image and trained model. During the third phase, analyzed the ambulance detection using a dataset, for the prototype consideration used static ambulance image and trained dataset. On detection of an ambulance, the traffic light is automatically changed to green.

Literature Survey
Vanjale et al [1] proposed a RFID-based system, which controls and controls road signals at the intersection of an emergency vehicle, by allowing direct traffic to exit traffic congestion. This paper proposes a road traffic control system so that when an emergency vehicle is on its way to a designated destination. The ambulance case is being tracked using GPS. This place is being sent to the app. The app creates an algorithm with the help of this data and therefore google map. It controls the signals in its path. They also introduced the current blue light to the stop light to avoid confusion in the minds of people waiting at the stop.
Program performance depends on two key modules.

• GPS system
• Application Server An ambulance for any emergency vehicle must be equipped with a GPS System. This GPS System will always send car links to the Server application. Each car must be logged into the android app. This application keeps tracking car and track tracks.
The route has already been selected for the root cause of this route which is further accessed by the server. The application server receives all the information, depending on the information the server receives the car location and the selected route Journal of Informatics Electrical and Electronics Engineering (JIEEE) A2Z Journals to your destination. This helps to monitor the next stop light in the vicinity. Whenever a vehicle enters a certain distance from the signal server the server must send the required action so that the vehicle does not wait for the signal. A sign is also sent to the hospital where we are going so that the hospital management can treat the patient. Hospitals also provide the most important thing for the patient to support his or her condition. It helps when two ambulances arrive at a well-known signal at the same time. There is also a certain rule that the software should take the support of signal lights. The range of these possibilities is next if the signal is already green it will remain the same as long as the ambulance does not pass. there is also the threat that people may think it is a technical error if it is only green for a long time on a single track and may break the law to avoid this blue-green light being inserted into the signal, whenever other red signals give a car emergency.

Dang et al [2]
have done a proposed work that provides a priority approach. This aims to create an integrated user HPV system where the HPV driver can send requests to the system where the system responds intelligently. The priority of the Road Segment (RS) is determined at the intersection of the road and the light ends up green with a moving car. They tested the algorithm in SUMO (Simulation of Urban Mobility) and showed good results by saving more than 50% of the time in various road forces (low, medium, high). The program is primarily aimed at addressing HPV traffic congestion problems. It is an interactive system where the user (i.e. the HPV driver) first attaches to the system before moving on to the phone. It then sends an invitation to turn blue on the system at the crossroads to recall the green signal. The plan calculates the prioritization of the entire RS downhill road. The system converts the bright light of the RS at a very high value. The system is progressing well by calculating the priority of all intersections after the TLDC period. Traffic Light Time (TLDC) can be a time cycle 1 that consists of a red and green wavelength at a crossroads. The model takes two states into consideration: Imagine that there is no ambulance where a bright light is found in any RS and the light runs automatically. Keep in mind that there are ambulances on all RS at intersections as his system prioritizes any RS traffic intersection and RS with the highest value converts gre over other RS across TLDC in this way -system prioritizes ambulances and other essential vehicles.

Meera et al [3] explored different light systems and other navigation systems and came to the conclusion that this method
allows the android mobile device (emergency vehicle) to override the traditional stoplight functionality. The android and cloudbased control system using the GSM module is an effective and affordable solution that can solve this problem. The program contains 5 categories which are android mobile device, GSM module, MQTT (IoT) for Arduino IDE, Arduino Uno microcontroller and road signs. The upgraded system has allowed the android mobile device (emergency vehicle) to override the traditional functionality of the station. In this paper they developed an android-based control system and cloud using the GSM module.
Travel debates probably only involve performance analysis of how special mobile technology can reduce the barriers to a particular area of activity. The upgraded version within this paper has allowed the Android mobile device (emergency vehicle) to bypass traditional stoplight functionality. They are using an android and cloud-based control system using the GSM module.
The system contains an Android mobile device, GSM module, MQTT (IoT) for Arduino IDE, Arduino Uno microcontroller and road signs this method will be very useful for the safety and security of the public, thus ensuring that no current adherence is present. MQTT is a "Internet of Things" tracking system and is used for sensors that connect to home automation devices and small device environments, which explains how the system works. The stop unit will be built and controlled by Arduino Uno microcontroller with proper pro. In this paper they developed an android and cloud-based control system using the GSM module.

Smith et al [4]
have proposed the system which comprises of 5 stages which are Android mobile device, GSM module, MQTT (IoT) for Arduino IDE, Arduino Uno microcontroller and traffic signals this paper, they need proposed an adaptive Traffic Management System (TMS) combined with a symbolic logic-based scheme so as to require appropriate actions to hurry up the progress of emergency vehicles while avoiding the creation of bottlenecks around their routes. This is often achieved through.
The TMS has multiple steps at its disposal to ensure the quickest possible response to an emergency; a number of these will

Faldu et al [5]
announced a paper on constant versatile control framework. In present world, the matter of gridlock has become a huge concern. It's limited to megacities or metropolitans as well as in any event, for little urban communities; thus they require a savvy or insightful control framework. Their current control framework isn't versatile yet depends on schedule all incorporates ambulances benefits as well. In this, by utilizing clever rescue vehicle framework they'll accomplish the continuous help of the control framework by executing the substitute strategies for signal change to allow stream control. The exactness of the RFID is very camera's so this additionally improves the presentation of stoplight infringement discovery framework.
Plan framework is financially savvy, different uses and sent utilizing moving IOT, which is more productive.

Singh et al [9]
have done examination concentrate on tie up and flowing on current traffic the board, which is dealing with two significant issues in present day metropolitan zones which cause street mishap and death toll. To conquer this, they pre- shrewdly settled upheld the traffic on streets. When contrasted with past fixed mode light regulator this new framework is more proficient and adaptable. It additionally has office to pass the crisis vehicles like rescue vehicle, fire detachment and so on so distinguishing and furthermore recording taken vehicles. The look additionally has scope for additional extension. Green wave framework was acclimated give freedom to any crisis vehicle by turning all the red lights to green on the path of the crisis vehicle, the biggest weakness For the green waves, the disturbance will mess traffic up when might be heightened by the synchronization. In such cases, the line of vehicles during a green wave fills in size until it gets overlarge and a couple of the vehicles can't arrive at the green lights this is brought excess as expected, and should dodge.

Sudhakara H M et al[11]
India is an agricultural nation, populace of India is altogether developing. India remains inside the second spot on the planet as far as populace. As there will be increment in populace steadily there will be increment in number of vehicles, because of which the gridlock increments and due to which the crisis vehicles like emergency vehicle, fire motor and so on face hard to arrive at the objective as expected. Under these conditions, a promising framework that can clear the traffic light particularly I n top hours and accordingly give a protected course to crisis vehicles is critical. In existing writing there's less spotlight show on the crisis vehicles to clear the path, to defeat this issue a RFID based framework is proposed by utilizing this method we will oversee and manage the traffic lights at intersection which crisis vehicle draws near. Accordingly, there'll be simple dropping for the crisis vehicles in gridlock. The proposed outline work is demonstrated by the methods for a trial arrangement utilizing Arduino and LED shows which mimics a genuine time traffic situation. This reenactment results represent the terms of identification still as is giving.

Conclusions
The existing system doesn't provide a transparent path for emergency vehicles during traffic congestion. Traffic Density Analysis, Ambulance, and Accident detection System Using Image Processing has been discussed in this proposed system. From the literature survey, we've found that RFID-based smart traffic control system provides an answer to the traffic congestion problem and this can be also an efficient method to supply a transparent path for the emergency vehicles when identified within the lane, as we also implemented sharing of patient's vital data with hospital we updated Arduino uno with Arduino mega board so it'd be sufficient for storing of patient vital parameter and simultaneously it performs capturing of present status of traffic signal present in different path and we also added another system in the junction which repeatedly scans the density of the lanes so that the system can automatically allow the lane which has high density by this technique the emergency vehicles experience less congestion and reach faster to the destination and thus many life's were been saved.