FIELD OF THE DISCLOSURE

The present disclosure relates to the field of traffic control systems and in particular to Accident Detection and Notification control systems.

DEFINITION OF TERMS USED IN THIS SPECIFICATION

The term 'Vehicular Sensor Node" used in this specification relates to wireless sensor nodes which are embedded on the vehicles to sense vehicle activity e.g. accident occurrence.

The term 'Road Side Sensor' used in this specification relates to wireless sensor nodes, which are deployed in some predetermined distances on both sides way of highway roads

The term 'base station' used in this specification relates to semi-stationed equipment adapted to perform radio communication with a user's mobile equipment, such as traffic police station, firefighting station and rescue team station

The term 'fuzzy logic' used in this specification relates to a type of logic that generates reasoning as an output having an approximation level that is a level ranging in degree between 0 and 1 for quantification of linguistic information while allowing for imprecision.

The term 'fuzzy set' used in this specification relates to a collection of objects characterized by a membership function assigning to each object a grade of membership ranging between zero and one.

The term 'fuzzy variables' used in this specification relates to a variable for defining parameters like collision, jerk, inclination degree and temperature.

The term 'cognitive' used in this specification relates to technology that involves conscious intellectual activity, related to the environment.

The term 'cognitive radio' used in this specification relates to a radio technology which is able to change its transmission parameters with the environment in which it operates.
The term 'TV interleaved spectrum bands' used in this specification relates to a large portion of the spectrum (UHF and VHF) which are unused on geographical basis also known as Television White Spaces (TVWS).

BACKGROUND

As vehicular traffic started straining already overburdened roadways, congestion on the roads hampered safe and efficient movement of traffic causing more accidents and environmental pollution. Further, as reported by the authority, National Highway Traffic Safety Administration (NHTSA), car crashes on highways are on a steep rise. For example, in US alone, vehicle crashes on the highways result in loss of as many as 40,000 lives and overall economic losses of more than $230 billion per year.

A well known conventional system for integrating moving vehicles for engaging into intelligent data communication with each other is Vehicular Ad-Hoc Network (VANET). The VANET is configurable to send an alarm message about an accident on the road. However, a limitation of the VANET is that it is not able to detect an accident and report the accident to the police, rescue teams, firefighting trucks, etc., instantaneously. Further, the VANET does not provide any sensing functionality and is only restricted to voice and video data communication for rescue among vehicles moving on road. The VANET system includes a GPS unit that is adaptable to estimate a vehicle's position and velocity but it does not have any instantaneous sensing capabilities to avoid fatal accidents/mishaps on the road.

Thus, a need is felt for:

an accident detection and notification system that can reduce number of fatalities and injuries caused by car crashes;

and

an intelligent accident detection and notification system that can instantly connect with rescue and reinforcement teams on a priority basis.

OBJECTS OF THE INVENTION

It is an object of the present invention to configure an accident detection and notification system that can reduce number of fatalities and injuries caused by vehicle crashes.

It is still another object of the present invention to configure an intelligent accident detection and notification system that can instantly connect with rescue and reinforcement teams on a priority basis.

It is still another object of the present invention to utilize sensor nodes in vehicular networks to sense the vehicles activity e.g., accident detection.

Further to the above, another objective of the present invention is to employ cognitive radio technology to achieve more spectrum efficiency in vehicular ad hoc and sensor networks. Since, the originated packets and alarm by the system are very time sensitive, owing to high traffic in unlicensed bands, cognitive radio technology is the best tool to help sensor nodes to capture an available licensed spectrum band e.g. TV interleaved spectrum bands. Yet another object of the present invention is to implement the system based on fuzzy theory.

SUMMARY OF THE INVENTION
In accordance with present invention, there is provided a system and method for accident detection and notification in a network integrating an array of vehicles. The system includes: an array of static sensors and an array of mobile sensors adaptable to transmit accident intensity and geographical co-ordinates of an accident spot to a base station; a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance; a cognitive radio means adaptable to access interleaved spectrum bands; and a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

Typically, the cognitive radio means includes a spectrum sensing duplex radio device.

Typically, the fuzzy processor includes: a fuzzification means adapted to convert crisp inputs from the diverse sensor of VSNs to fuzzy variables; a fuzzy inference engine adapted to make an inference using indefiniteness in the fuzzy variables; and a defuzzification means adapted to convert the inference to a crisp output indicative of accident severity.

Typically, the array of diverse sensors of VSNs comprises: jerk sensors; collision intensity sensors; inclination sensors; and temperature sensors.

Typically, the repository includes a translation memory device built upon a Random Access Memory (RAM) circuit platform.

In accordance with the present invention, a method of accident detection and notification includes steps of: transmitting an array of sensed data packets towards at least one base station and vehicles moving on road, said sensed data packets pertaining to an accident; converting crisp inputs from said sensed data packets to fuzzy variables, making an inference using a degree of indefiniteness in said fuzzy variables and converting said inference to a crisp output indicative of accident severity; detecting unused interleaved spectrum bands; sharing said unused interleaved spectrum bands without harmful external interference; making an inference using a degree of indefiniteness in said fuzzy variables; and converting said inference to a crisp output indicative of accident severity.

Typically, the step of transmitting said sensed data packets is preceded by steps of: detection of at least one accidental event by at least one mobile sensor; estimating a severity of said accidental event; and sending sensed data packets to static sensor nodes.

Typically, the step of sharing said unused interleaved spectrum bands comprises step of accessing television (TV) interleaved spectrum bands.

Typically, the crisp output is used to notify rescue teams, Police Traffic Station, a Traffic Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group and an Urban Rescue Paramilitary Group.

Typically, the crisp inputs indicative of antecedents are selected from a group consisting of jerk intensity; collision intensity; inclination degree; and temperature level.

Typically, the crisp output indicative of consequent includes an estimate of crash severity.

Inventors, it is a standard practice to write all embodiments of the invention under the heading "Summary of the Invention'. In accordance with the present invention, an accident detection and notification device includes wireless sensor nodes adaptable into: mobile sensing nodes embedded into vehicles; and stationary sensing nodes deployed at predetermined distances beside the highway roads; a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance; a cognitive radio means adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and mobile vehicle user behavior; and inoperable state of network that integrates elements of said system; and a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

Typically, said device is coupled to front and rear fender of a vehicle, and, wherein an Electro-Magnetic (EM) wave transceiver is embedded in said device, and wherein said transceiver is adapted to estimate motion parameters of leading and trailing vehicles and said transceiver is adapted to control brakes of said vehicle automatically to prevent an accident.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING

The system will now be described with reference to the accompanying drawing, in which:

Figure 1 is a first block diagram depicting an accident detection and notification system in accordance with the present invention;

Figure 2 is a second block diagram depicting an accident detection and notification system in accordance with the present invention;

Figure 3 is a schematic depicting topology of the network connected by the intelligent accident detection and notification system in accordance with the present invention;

Figure 4 is flow of data in the proposed fuzzy system depicting configuration of fuzzy variables for intelligent accident detection and notification in accordance with the present invention;

Figure 5 is a schematic depicting membership function and sample fuzzy calculation for crash severity in accordance with the present invention;

Figure 6 is a surface view of crash severity with respect to inclination degree and collision in accordance with the present invention;

Figure 7 is a surface view of crash severity with respect to inclination degree and temperature in accordance with the present invention;

Figure 8 is another surface view of crash severity with respect to inclination degree and temperature in accordance with the present invention; and

Figure 9 is a flow chart depicting a method of accident notification and detection in accordance with the present invention.

DESCRIPTION OF THE INVENTION

The accident detection and notification system in accordance with the present invention will now be described with reference to the accompanying drawings, which does not limit the scope and ambit of the disclosure. The description provided is purely by way of example and illustration.

A typical system for integrating moving vehicles for engaging into intelligent data communication with each other is Vehicular Ad-Hoc Network (VANET). The VANET is configurable to make connection among vehicles on roads. However, a limitation of the VANET is that, it is not able to detect an accident and report the accident to the authorities e.g. police, rescue teams, firefighting trucks, etc., instantaneously. Further, the VANET does not provide any sensing functionality and is only restricted to voice and video data communication for rescue among vehicles moving on road. The VANET system includes a GPS unit that is adaptable to estimate a vehicle's position and velocity but it does not have any instantaneous sensing capabilities to avoid fatal accidents/mishaps on the road.

To overcome these shortcomings, the present invention envisages an instantaneous accident notification and detection system that includes two categories of sensor nodes. A first category of sensor nodes is embedded in the vehicles, termed as vehicular sensor nodes (VSN). A second category of sensor nodes is deployed in a predetermined distances beside the road, termed as Road Side Sensor (RSS) nodes. The VSNs are used to sense the accident intensity and the RSS are used to sense movement irregularities of vehicles on road. Both VSNs and RSS can be linked to a Base Station (BS) deployed in a Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group or an Urban Rescue Team. Thus, the base stations may be stationary or mobile. If an accident occurs on the road then instant help from rescue authorities (Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group or an Urban Rescue Team) is difficult to get.

In an embodiment of the invention, when VSNs detect a collision or overturning movements they immediately initiate transmittal of a data packet towards the Base Stations via RSS nodes. Hence, critical details about the accident that is intensity, is also considered and the details are conveyed for relevant action that in turn saves time and resources using fuzzy set theory modules, wherein, jerk, collision intensity, inclination degree and temperature are input fuzzy variables (antecedents) and intensity and severity of crash in an accident is an output variable (consequent). Further, to handle spectrum scarcity, cognitive radio technology is utilized to access television (TV) interleaved spectrum bands.

In an embodiment of the invention, dynamics of accident detection and notification is discussed. Both VSNs and RSS are wireless nodes adaptable to estimate severity of accident and sending data packet to RSS nodes, wherein the RSS nodes retransmit the data packet towards Base Stations and trailing vehicles on road. The VSNs are mobile sensor nodes embedded on moving vehicles adaptable to sense activities of the vehicles and the RSS are stationary nodes deployed at predetermined distances beside the highway roads. The VSNs are adapted to transmit the reading of sensed vehicle data to the RSS and the sensed data packets are retransmitted to the base stations thereon. Both the VSNs and RSS are equipped with cognitive radio technology that is adaptable to change its transmission and reception parameters in a way that entire wireless communication among control stations (base station, for example) and the vehicles take place without interfering signals to the primary users.

In accordance with a first aspect of the present invention, there is provided a system and method for accident detection and notification in network integrating an array of vehicles. The system includes: an array of static sensors and an array of mobile sensors adaptable to transmit accident intensity and geographical co-ordinates of an accident spot to a base station; a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance; a cognitive radio means adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and dynamic vehicle user behavior; and inoperable state of network that integrates elements of said system; and a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository, receive crisp input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

Still, according to the first aspect, the cognitive radio means includes a spectrum sensing duplex radio device and the fuzzy processor includes: a fuzzification means adapted to convert crisp inputs from the diverse sensors of dynamic node to fuzzy variables; a fuzzy inference engine adapted to make an inference using indefiniteness in the fuzzy variables; and a defuzzification means adapted to convert the inference to a crisp output indicative of accident severity.

Again, static sensors are for receiving data from dynamic nodes and forward towards the base stations, the static sensor only sense the spectrum for spectrum access by employing cognitive radio. Furthermore, static nodes are needed for localization of VSNs. wherein, On each vehicle there is only one sensor nodes which is include 4 diverse sensor e.g. collision sensor, jerk sensor, inclination sensor and temperature sensor. Further, the repository includes a translation memory device built upon a Random Access Memory (RAM) circuit platform.

In accordance with a second aspect of the invention, a method of accident detection and notification includes steps of: transmitting an array of sensed data packets towards at least one base station and vehicles moving on road, said sensed data packets pertaining to an accident; sharing said unused interleaved spectrum bands without harmful external interference; making an inference using a degree of indefiniteness in said fuzzy variables and converting said inference to a crisp output indicative of accident severity.

Still, according to the second aspect of the invention, the step of transmitting said sensed data packets is preceded by steps of: detection of at least one accidental event by at least one dynamic sensor; estimating a severity of said accidental event; and sending sensed data packets to static sensor nodes, whereby, the step of sharing said unused interleaved spectrum bands comprises step of accessing television (TV) interleaved spectrum bands.

Again, according to the second aspect of the invention, the crisp output is used to notify rescue teams selected from a group consisting of Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group and an Urban Rescue Paramilitary Group. Further
the crisp inputs are indicative of antecedents are selected from a group consisting of jerk intensity; collision intensity; inclination degree; and temperature level and the crisp output indicative of consequent includes an estimate of crash severity.

In accordance with a third aspect of the invention, an accident detection and notification device includes wireless sensor nodes adaptable into: mobile sensing nodes embedded into vehicles; and stationary sensing nodes deployed at predetermined distances beside the roads; a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance; a cognitive radio means adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and dynamic vehicle user behavior; and inoperable state of network that integrates elements of said system; and a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

Still, according to the third aspect, said device is coupled to front and rear fender of a vehicle, and, wherein an Electro-Magnetic (EM) wave transceiver is embedded in said device, and wherein said transceiver is adapted to estimate motion parameters of leading and trailing vehicles and said transceiver is adapted to control brakes of said vehicle automatically to prevent an accident.

Aspects of the invention will now be described in detail with reference to accompanying drawings, whereby, the figures and the description hereto are merely illustrative and only exemplify the system and method and in no way limit the scope thereof.

Referring to the accompanying drawings, Figure 1 illustrates a first block diagram 100 depicting an accident detection and notification system in accordance with the present invention. The system includes a Wireless Sensor Control Unit 102 adaptable to control transmittal of static and mobile sensing parameters to a base station, wherein, said sensing parameters pertain to accident intensity and geographical co-ordinates of an accident spot. A memory 104 is adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance. A cognitive radio means 106 is adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and mobile sensors; and inoperable state of network that integrates elements of said system. A fuzzy processor 108 adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

Referring to Figure 2, a second block diagram 200 depicts an accident detection and notification system in accordance with the present invention. The system includes a Wireless Sensor Control Unit 202 adaptable to control transmittal of sensing parameters to a base station, wherein, said sensing parameters pertain to accident intensity and geographical co-ordinates of an accident spot. A translation memory 204 is adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance. A cognitive radio means 206 is adaptable to access interleaved spectrum bands based on change in parameters pertaining to: the vehicle behavior; and inoperable state of network that integrates elements of said system. A fuzzy processor 208 is adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level. A signal conditioning circuit 210 is coupled to an output node of the fuzzy processor to filter the output of the fuzzy processor making it free of electrical noise. An audio-video amplifier 212 is coupled to an output node of the signal conditioning circuit 210 for amplifying the audio-video content in the accident notification signal and accident severity level. Thus, an amplified audio-video output 214 is generated by the amplifier 212.
Referring to Figure 3, a topology 300 of a network connecting a plurality of moving vehicles 302 is depicted in accordance with the present invention. The vehicles move on a road 304 having a plurality of static sensors (RSS0 through RSS6) 306 deployed along road-sides, wherein the plurality of static sensors 306 can include temperature sensors; humidity sensors; light sensors; moving obstacle sensors; and induction loops. The moving vehicles 302 are fitted with Vehicular Sensor Nodes (VSNs) configured as dynamic sensors including jerk sensors; collision intensity sensors; inclination sensors; and global positioning system (GPS) sensors. A TV tower 308 is adapted to house a base station that is adapted to utilize cognitive radio technology to access TV interleaved spectrum bands in an opportunistic configuration.

Referring to Figure 4, a data flow diagram 400 depicting fuzzy control system in accordance with the present invention is shown. In a first step 402, a plurality of sensor parameters are sent as crisp input variables to a fuzzy logic processor. In a second step 404, the crisp input variables are converted to fuzzy variables through a process of fuzzification. In a third step 406, a fuzzy inference engine is adapted to make an inference using a degree of indefiniteness in said fuzzy variables. In a fourth step 408, said inference is subjected to defuzzification. In a fifth step 410, a crisp output is generated that is indicative of crash severity in an accident.

Referring to Figure 5, a graphical representation 500 depicts a membership function and sample fuzzy calculation for crash severity in an accident. It is an example of the defined rules to find out the crash severity. For instance, if J=45, C=45, T=50 and 1=90 then the Crash Severity is equal to 25.

Referring to Figure 6, a surface view 600 depicts crash severity with respect to inclination degree and collision. The surface view is displayed on the graphical monitors deployed in the base station, wherein, a three dimensional view of crash is displayed that can be further codified and communicated to various rescue and relief crews/ stations including a Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group and an Urban Rescue Paramilitary Group.

Referring to Figure 7, a first surface view 700 depicts crash severity with respect to inclination degree and temperature. The surface view is displayed on the graphical monitors deployed in the base station, wherein, a three dimensional view of crash is
displayed that can be further codified and communicated to various rescue and relief crews/ stations including a Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group and an Urban Rescue Paramilitary Group.

Referring to Figure 8, a second surface view 800 depicts crash severity with respect to inclination degree and temperature. The surface view is displayed on the graphical monitors deployed in the base station, wherein, a three dimensional view of crash is displayed that can be further codified and communicated to various rescue and relief crews/ stations including a Police Traffic Station, a Traffic Patrolling Vehicle, a Police Patrolling Vehicle, a Highway Rescue Vehicle, an Urban Rescue Vehicle, a Firefighting Group and an Urban Rescue Paramilitary Group.

Referring to Figure 9, a flow chart 900 is shown that depicts a method of accident detection and notification. A first step 902 includes transmitting an array of sensed data packets towards at least one base station and trailing vehicles, said sensed data packets pertaining to an accident. A second step 904 includes converting crisp inputs from said sensed data packets to fuzzy variables. A third step 906 includes detecting unused interleaved spectrum bands responsive to said fuzzy variables. A fourth step 908 includes sharing said unused interleaved spectrum bands without harmful external interference. A fifth step 910 includes making an inference using a degree of indefiniteness in said fuzzy variables. A sixth step 912 includes converting said inference to a crisp output indicative of accident severity.

TECHNICAL ADVANTAGES AND ECOMONIC SIGNFICANCE

The technical advancements and economic significance of the present invention include configuring an accident detection and notification system having high accuracy, high reliability, and is cost efficient. Further, applications of the system and method of present disclosure include vehicular velocity monitoring, vehicle tracking, highway monitoring, and road side advertisement. Still further, the system is applicable to vehicles including cars, truck, buses, train and mobikes/ motor-bicycles.

While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiment as well as other embodiments of the invention will be apparent to those skilled in the art from the invention herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the invention and not as a limitation.

Claims:

1. An accident detection and notification system comprising:

- an array of static sensors and an array of mobile sensors adaptable to transmit accident intensity and geographical co-ordinates of an accident spot to a base station;

- a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance;
- a cognitive radio means adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and dynamic vehicle user behavior; and inoperable state of network that integrates elements of said system; and

- a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

2. A system as claimed in claim 1, wherein said cognitive radio means comprises a
spectrum sensing duplex radio device.

3. A system as claimed in claim 1, wherein said fuzzy processor comprises:

- a fuzzification means adapted to convert crisp inputs from said static and dynamic sensors to fuzzy variables;

- a fuzzy inference engine adapted to make an inference using indefiniteness in said fuzzy variables; and

- a defuzzification means adapted to convert said inference to a crisp output indicative of accident severity.

4. A system as claimed in claim 1, wherein said array of static sensors comprises:
temperature sensors; humidity sensors; light sensors; moving obstacle sensors;
and induction loops.

5. A system as claimed in claim 1, wherein said array of dynamic sensors comprises: jerk sensors; collision intensity sensors; inclination sensors; and global positioning system (GPS) sensors.

6. A system as claimed in claim 1, wherein said repository comprises a translation memory device built upon a Random Access Memory (RAM) circuit platform.

7. A method of accident detection and notification, comprising:

- transmitting an array of sensed data packets towards at least one base station and vehicles moving on road, said sensed data packets pertaining to an accident;

- converting crisp inputs from said sensed data packets to fuzzy variables; detecting unused interleaved spectrum bands responsive to said fuzzy variables;

- sharing said unused interleaved spectrum bands without harmful external interference;

- making an inference using a degree of indefiniteness in said fuzzy variables; and
- converting said inference to a crisp output indicative of accident severity.

8. A method as claimed in claim 7, wherein the step of transmitting said sensed data packets is preceded by steps of:

- Detection of at least one accidental event by at least one mobile sensor;

- estimating a severity of said accidental event; and

- sending sensed data packets to static sensor nodes.

9. A method as claimed in claim 7, wherein the step of sharing said unused interleaved spectrum bands comprises step of accessing television (TV) interleaved spectrum bands.

10. An accident detection and notification device comprising:

- wireless sensor nodes adaptable into: mobile sensing nodes embedded into
vehicles; and stationary sensing nodes deployed at fixed distances beside the roads;

- a repository adapted to store parameters pertaining to: geographical importance of roads; density of vehicles on said roads; and statistics pertaining to roads condition and maintenance;

- a cognitive radio means adaptable to access interleaved spectrum bands based on change in parameters pertaining to: static and dynamic vehicle user behavior; and inoperable state of network that integrates elements of said system; and

- a fuzzy processor adaptable to: engage into a duplex communication with said cognitive radio means; retrieve data from said repository; and receive input signals from said static sensors and said dynamic sensors to output an accident notification signal appended with an accident severity level.

11. A device as claimed in claim 10, wherein said device is coupled to front and rear fender of a vehicle, and, wherein an Electro-Magnetic (EM) wave transceiver is embedded in said device, and wherein said transceiver is adapted to estimate motion parameters of leading and trailing vehicles and said transceiver is adapted to control brakes of said vehicle automatically to prevent an accident.