Automatic Vehicle Accident Indication and Reporting System for Road Ways Using Internet of Things

Throughout The development of transport system, though being one of the biggest revolutions of human inventions, it also brings disasters to human race by accidents. Road accidents have been the foremost cause of unexpected fatalities for decades [1]. The causes of road accident with accident rate are shown in the Figure 1.

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Figure 1. Causes of road accident

The main reason for road accidents are given below such as:

1. High speed
2. Drunken Drive
3. Distractions
4. Neglecting traffic rules and regulations
5. Human error
6. Non-adherence to lane driving and overtaking in a wrong manner

Thus, there are many factors that serve as root cause for accidents, but the high speed remains the primary concern.

Even though advised and regulated by government, the control of road accidents had always been a tedious task. Despite these causes, if the accident information could reach the emergency services much faster and their response in return, lot of fatalities could have been reduced. According to the statistical approach, more than 50% fatalities are due to the time delay of the injured user to the hospital. As of now, detecting accident at the instant of occurrence and reporting the same to the emergency services is very important to save the life of a human being.

The highest accident prone zone is Delhi and the range of accident location is prescribed in the Figure 2.

As per the government data in India, nearly 1.5 lakh people got injured due to road accidents in the year 2018 with over-speeding of vehicles. The city where the accidents has occurred is shown in the Figure 2 with the top most 10 cities more prone to the accident.

From Open Government Data (OGD) community, the database for road accident is listed. In this Figure 3 the graph clearly shows the number of road accidents observed form 1970 (A) – 2017 (A1), the number of persons injured and killed during the same years [2].

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Figure 2. Cities prone in accident in India

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Figure 3. Road accident data in India

From the above graph, it inferred that majority of death cases in India during the following years. The main cause for the accidents according to the survey indicates the death cases increased mainly because of the improper indication system to the hospitals and nearby ambulance. The injured people due to the accident data is around 6 lakh and the person’s death count after the accident occurred is around 1.5 lakh. The difference between accident injured and death cases are analyzed from the graph and it is necessary to the assist the accident occurred location to the hospital nearest. An efficient system is provided to the user and enabled to track the accident located region to both the family and AMRSC. As our respected ancient poets like Thiruvalluvar, Avaiyar, Bharathiyar, Bharathidasan says that “Right help at Right time” is the possible way to reduce death caused due to accidents.

Thus, here the proposed system is organised as follow. First, various accident indication methods are collected and analysed. Next, the proposed system is structured by collecting the motion data using accelerometer positioned on the car. Then, the GPS is located to track the location of the vehicle that is fitted to the system. Whenever a deviation occurred in the prescribed algorithm, controller plays a vital role. It sends message to the connected mobile number and AMRSC centre. At last, the prescribed location is observed by the AMRSC centre and immediate actions such as locating nearest hospital and giving message to the concerned hospital to rescue the injured person. This method is taken to avoid the death fatalities caused due to road accident.

The automatic accident indication and reporting system for road ways using Internet of Things system uses a MEMS ADXL335 (Micro-Electro-Mechanical-Systems) device called Accelerometer to detect sudden changes in a moving vehicle, and report such accidents with the corresponding location through a GSM network [5-9]. In addition to that, the location data is stored in the server. When the accident occurs, the accelerometer changes its co-ordinated axis. Now, the change in value is fed to the controller. The controller will check for the limit value for the proposed algorithm. When the deviation between the proposed value and the actual value then the signal is fed to the user and AMRSC centre. If there are no serious injuries, to the user, the user can respond to the message and it will not be indicated to the AMSRC Centre. Then AMRSC will neglect the message once it is ignored by the injured user. If not, the AMRSC centre will send the data to the nearest hospitals and precautions will be made to the injured person. In addition to this, the message will also be sent to the linked mobile number like mother, wife, husband etc.

The accelerometer senses the variation of the accelerometer sensor while hitting the object. This object may include hitting tree, hitting the pavement, hitting the transformer and hitting the other vehicle etc. The pictorial representation shows the planned system model as shown in the Figure 4.

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Figure 4. Overview of the proposed system

The block diagram for this accident indication and reporting system is shown in the Figure 5.

The block diagram in the Figure 5 shows the working of the proposed system. The accelerometer gives an output signal whenever an accident occurs. When the controller senses the deviation in the prescribed values, the receiver receives message related to the accident location and sent to the cloud. Thereby, further detection techniques with the implementation of Internet of Things (IoT) can be done for protection. Here, it is used to measure the dynamic accelerations (motions or vibrations) caused due to accidents and report them [18-20]. The main hardware essentials of the proposed system include:

• MEMS accelerometer
• GPS Module
• GSM Module
• NodeMCU Controller

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Figure 5. Block diagram of the proposed system

3.1 MEMS Accelerometer

An accelerometer is an electromechanical device that measures acceleration due to both gravity and motions (or) vibrations. MEMS have made the accelerometer applications much more accurate with low power and minimum size. The MEMS used here act as a micro-sensors.

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Figure 6. Spring – Mass Diagram

By Newton’s law, the working of accelerometer is mentioned as shown in the Figure 6. Generally, the force is given by

F=Mass*Acceleration =Force due to spring tension

Force due to spring tension = t * X

where, x= displacement, t = spring constant

Thus, Acceleration A= function (x).

The acceleration is calculated by finding the displacement. To measure the displacement there are different methods such as resistive method, inductive method and capacitance method. The most prominent method to measure the displacement is capacitance method.

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Figure 7. Displacement measurement using capacitance effect

Thus from the above Figure 7, the fixed plate capacitance is located at the initial position and movable plate is moving across the displacement (x) by applying a force (F), that activated the system to accelerate (A). Thus

A = function (X)

Capacitance = function (1/ X)

Thus, the Capacitance = function (1/A)

But this not possible for such a large system as it increases the component size. So, MEMS came into existence fabricated at 20 micro meters with both electronic and mechanical component. The MEMS based accelerometer internal view is shown in the Figure 8.

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Figure 8. MEMS based accelerometer sensor

By measuring this capacitance change in value, it is inferred to measure the acceleration of an active system. Whenever the deviation occurs on the movable plates, the capacitance varies and corresponding acceleration is determined. The different phases assumed by the proposed system are X-axis, Y-axis, and Z-axis.

The ADXL335 is a 3 axis accelerometer used in the vehicle to measure x, y and z co-ordinate axis [21]. As mentioned earlier, it is small in size and consumes less power as it is MEMS based accelerometer. It is a complete 3-axis accelerometer with signal conditioned voltage outputs. This measures acceleration with a minimum full-scale range of ±3g with low power consumption of 350 µA. This MEMS ADXL335 provides better temperature co-efficient and linearity is better compared to the ADXL3XX series. It measures both the static acceleration due to gravity in titling position and dynamic acceleration during motion, shock and vibration. The pin diagram of the ADXL335 is shown in the Figure 9 below.

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Figure 9. Pin diagram of ADXL335

The Steps involved to interface the components are: Initially, connect the accelerometer on the board. The supply voltage of 3.3 V and GND pins of ardunio is connected to the ADXL335.Connect the X_out, Y_out and Z_out pins of ADXL335 pins to analog pins A1, A2 and A3 respectively. Read the analog outputs of each axis and print them in the serial monitor respectively. Provide a delay of 1 second for each reading. Upon executing, the readings of x, y and z axis are displayed in the serial monitor respectively with a delay of 1 second for every reading.

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Figure 10. Output of ADXL335 before and after Calibration using Serial Monitor

The anlaog output of x, y and z axes of the accelerometer are obtained as some random values. But to use for vehicle accident application, the accelerometer must be calibrated to provide standard values. To avoid such random values the calibration is done. Based ‘n’ samples of each axis calculate their average at every reset. Now the readings are assignment as follows

Xvalue = Xvalue - Xaverage

Yvalue = Yvalue - Yaverage

Zvalue = Zvalue – Zaverage

By employing the above logic, the accelerometer is calibrated and corresponding value is uploaded in the serial monitor as shown in the Figure 10. The main parameters of ADXL335 considered for the proposed system is shown in the Table 2.

Table 2. Specification of ADXL335 sensor

The readings of the accelerometer is taken and analysis is done for simple vehicle based on different incidences such movement in left, right, up and down at different directions is shown in the Table 3.

Table 3. Readings of accelerometer

From this above table, the proposed algorithm assumes the normal operation mode value lies in the order of +50 to -50. For an instance, if the maximum value of any axis for the vehicle to be stable is given as +50 and the minimum value as -50, whenever the accelerometer is found to be crossing these upper and lower limits, the system senses the sudden change and continues to proceed with the further functions.

3.2 GPS module

The Global Positioning System is a most popular component to track the location of the car and other location for various applications. It is embedded with the antenna to track the signals at a narrow band. The button cell used to redundant the last position. The antenna can be connected easily with GPS. The main four pins are T_x, R_x, VCC and GND connected to a [22].

The board application of GPS is position, navigation and pointing the time of a particular location. The receiver in GPS is used to receive signals to module and determine the vehicle present position and point the correct latitude, longitude and altitude of the vehicle [23, 24]. The pictorial representation of SIM28ML GPS is shown in the Figure 11.

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Figure 11. Model of SIM28ML GPS

When interfacing with ardunio the common library file to extract the data is shown below. The TinyGPS++ library which does the extraction of individual parameters from NMEA sentences sent by the GPS module. It uses functions to display individual parameters such as:

1. memberName.location.lat() - Latitude
2. memberName.locaton.lng() - Longitude

The ardunio serial monitor screen displays the latitude and longitude of a location. The serial monitor diaplay for latitude and longitude is shown in the Figure 12.

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Figure 12. Output of GPS module

The range of voltage, frequency, signal level and accuracy of SIM28ML GPS is shown in the Table 4.

Table 4. Specification of SIM28ML GPS

3.3 GSM module

The Global System for Mobile communications (GSM) commonly available in India market with a flexible cellular network to transmit voice call and large data services. For transmitting signals, GSM uses narrow band TDMA. This TDMA assigns on same frequency for different time slots for different users. Here, GSM is used to send the information regarding vehicle accidents via SMS using AT commands. The SIM900A GSM module is top-viewed as shown in the Figure 13.

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Figure 13. SIM900A GSM module

This SIM900A works with a set of AT commands. These AT commands usually operated using UART / Serial protocol. It has T_x, R_x, VCC and GND [25-27]. The interface of GSM module with the controller is shown in the Figure 14.

This GSM is embedded with all hardware interfaces between the module and customer’s boards. It is also easier to develop user’s application using serial port, audio channel with microphone, receiver output, programmable general purpose input and output pins and debug port with keypad and SPI display interfaces [28]. The specification of SIM900A GSM Module is shown in the Table 5.

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Figure 14. Interfacing GSM module with controller

Table 5. Specification of GSM Module

3.4 Controller

The NODE MCU is a scorching open source development kit on Internet of Things platform. The main advantage of using NODEMCU is easily available in market with inbuilt- Wi-Fi module ESP8266 – 12E. Thus the Controller makes this system mores easier, smaller, less costly and low power consumer as compared to other methods as compared Figure 2 in comparison methods [28]. It is more powerful with high level I/O pins and Digital pins. The major parameter for NODE MCU controller is shown in the Table 6.

Table 6. Specification of NODEMCU controller

3.5 AMRSC

Accidents Monitoring and Rescue Services Centre (AMRSC) is a group of servers maintained at a single place allocated for a region. AMRSC monitors all the accidents occurring in the particular region. The rescue services for this region are also controlled by AMRSC.

All the accidents are reported to AMRSC by the proposed detection system and thus AMRSC responds with the rescue services. Thus, the difficulties are reduced in this, as compared to the present system as it is controlled at a single centre [29, 30]. The Internet of Things (IoT) is the network of devices that contains electronics, software and sensors that allows connecting and exchanging of data without requiring human-human or human-computer interaction as shown in the Figure 15.

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Figure 15. Cloud server data

The result of the proposed system is analyzed based on the above flow chart Figure 17.

The accelerometer values are recorded continuously and the change value is sensed by controller. The controller gives signal to both the user and AMRSC. The Figure 18 and 19 shows the accident occurred location (i.e. latitude and longitude with date) using IoT platform.

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Figure 18. Latitude Readings taken from the server

The Figure 18 and 19 displays, the data taken from the server for an event when the object suddenly hits another object with a deviation mentioned in the controller.

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Figure 19. Longitude Readings taken from the server

The Figure 20 shows the message of accident occurred location (i.e. latitude and longitude with Google map link) using GSM module.

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Figure 20. Alert message along with Google Map link

The location of the accident is also monitored and observed using Google map and shown in the Figure 21.

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Figure 21. Accident location using Google Map

Therefore the alert message is sent to the given phone number and the details of the location is also sent to the Thingspeak server. Thus, by using IoT technology, the accident location data can be analysed and if there is a high risk of an accident taking place in a particular location, then this data will be very useful in order to analyse why that location is an accident prone region and take necessary action to reduce the number of such incidents in future [31].

The proposed system can also be extended by creating a mobile app displaying accident prone zone or making the accident prone zone display in the Google Maps.