Traffic surveillance systems have been around for quite a while across various cities worldwide. The ubiquitous presence of closed circuit cameras, vehicle plate detection systems and LED lane control lights has made traffic and incident management smooth and efficient. With such advanced technologies changing the face of traffic systems, it was just a matter of time before sensor integration came to the fore.

Currently, magnetic loops are used to count and categorize vehicles on the street. The magnetic coil monitors the vehicles passing by while fetching other parameters like vehicle speed, traffic congestion, accidents and such. The basic requirement for traffic surveillance is to define how road traffic can be controlled and the process through which wireless sensor based systems should be analyzed. The traffic control system is a real time application in which the wireless sensor based network serves well. The reason behind it is that the WSN design can meet all real-time requirements for monitoring traffic and road conditions. Also, the sensor-based system offers energy-efficient operation, reliable data transmission, and accurate operations.

The key requirements of traffic surveillance system using wireless sensor networks are:

• Precise vehicle detection
• Energy-efficient sensor networks
• Reliable wireless data transmission in real-time
• Real-time data processing from sensors

The traffic surveillance works in three main stages.

• First, magnetic sensor nodes detect vehicles on the surface of roads and gates and send the gathered data to the nearest base-station. To be more precise, magnetic sensors detects vehicles based on magnetic field variation of earth caused by moving vehicles.
• After collecting the data of vehicle detection, base station processes them. The process extracts valuable data like speed of vehicle from received detected data.
• At last, the system transfers the data to monitoring devices or database management. The monitoring devices check if the base station operates normally or not. And if it finds any error, it sets triggers or resets the procedure.

To provide energy efficiency, a sensor-node operates only when there is a vehicle on the road in certain proximity. The sensor node enters into sleep mode when there is no vehicle or specific event. The sensor-node identifies a vehicle by analyzing variations of magnitude of magnetic fields of earth occurred by a moving vehicle. So the signals when there is absolutely no obstacle, are compared to the signals when there are several obstacles and vehicles. This approach reduces the complexity between magnetic signals.  A base-station calculates speed using vehicle detection data from sensor-nodes, distance between two sensor-nodes, and time data (clock ticks) of the vehicle detection.

The system is capable of accomplishing following tasks:

• Vehicle tracking over long distances for travel-time approximation.
• Counting vehicles at crossings. This service is important in cities, where traffic volume information is necessary for traffic management systems.
• Inconsistent driving recognition and driver warning. With higher computational capability, sensor nodes can process large amount of data and generate patterns.
• Incident detection. It is similar to irregular driving detection, with one difference that nodes transfer the details of incident and warn the driver of powerful devices that are required for long range communication.
• Periodic traffic volume photograph. This service counts or estimates the number of vehicles along the whole road at a particular time and sends it to a traffic management centre.
• Recording road condition. Equipping sensor nodes with additional sensors like temperature and humidity sensors would allow users to collect information about the road-surface condition. The information could be sent to a traffic management centre, displayed through a variable message sign or communicated to passing vehicles.
• Message broadcast service. Nodes can also forward messages along the road and broadcast them to passing cars.

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