【正文】 ghest priority are pared. 4) If a single road has traffic till Ax, it is given green signal in the next time slot. 5) If multiple roads have traffic till Ax, the road waiting for the longest duration is given the green. 6) Once a road is given green, its waiting time is reset and its sensor status is neglected for that time slot 7) If traffic in middle lane, green is given for straight direction, based on traffic, either right side neighbor is given green for right direction, of opposite road is give green for straight direction. 8) If traffic in right lane, green is given for right, and based on traffic, left side neighbor is given green for straight or opposite is given green for right. 9) Similar smart decisions are incorporated in the signal based on traffic density and directional traffic can be controlled. C. Implementation and Restrictions This system can be implemented by just placing the sensor nodes beneath the road or on lane divider and interfacing the central controller to the existing signal lights and connecting the sensor nodes to the controller via the proposed wireless protocol. The only restriction for implementing the system is taking the pedestrians into consideration. This has to be visualized for junctions with heavy traffic such as highway intersections and amount of pedestrians is very less. Also major intersections have underground or overhead footpaths to avoid interaction of pedestrians with heavy traffic. VI. CONCLUSION The above proposed system for automated traffic signal routing using Wireless Sensor Networks is advantageous to many existing systems. The wireless sensors nodes create a standalone system at each intersection making it easy to implement in the intersections having heavy density of vehicles. It is also cost inexpensive and does not require any system in the vehicles making it more practical than existing systems. The use of various systems of sensor nodes can be altered based on the requirement and any type of sensor can be used based on the feasibility of the location. ACKNOWLEDGMENT The Authors would like to take this opportunity to thank Ms. P. Sasikala, Assistant Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who gave the basic insight into the field of Wireless Sensor Networks. We also thank Mrs. G. Padmavathi, Associate Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who with her expertise in the field of works advised and guided on practicality of the concept and provided helpful ideas for future modifications. We also express our gratitude to Dr. S. Ganesh Vaidyanathan, Head of the department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, who supports us for every innovative project and encourages us “ think beyond” for better use of technology. And finally we express our heart filled gratitude to Sri Venkateswara College of Engineering, which has been the knowledge house for our education and introduced us to the field of Engineering and supports us for working on various academic projects. 基于無(wú)線傳感器網(wǎng)絡(luò)的智能交通信號(hào)控制 摘要： 在所有發(fā)展中國(guó)家和發(fā)達(dá)國(guó)家，不斷增長(zhǎng)的汽車數(shù)量將促使現(xiàn)有的交通信號(hào)系統(tǒng)發(fā)生重大變革。 and GHz. The functionality of bothtransmitter and receiver are bined into a single deviceknown as a transceiver [3]. To bring about uniqueness in transmitting and receiving toany particular device various protocols/algorithms are devised. The Motes are often are often provided with powerful transmitters and receivers collectively known as transceivers for better long range operation and also toachieve better quality of transmission/reception in any environmental conditions. F. Power Source The sensor node consumes power for sensing, municating and data processing. More energy is required for data munication than any other process. Power is stored either in batteries or capacitors. Batteries, both rechargeable and nonrechargeable, are the main source of power supply for sensor nodes. Current sensors are able to renew their energy from solar sources, temperature differences, or vibration. Two power saving policies used are Dynamic Power Management (DPM) and Dynamic Voltage Scaling (DVS). DPM conserves power by shutting down parts of the sensor node which are not currently used or active. A DVS scheme varies the power levels within the sensor node depending on the nondeterministic workload. By varying the voltage along with the frequency, it is possible to obtain quadratic reduction in power consumption. G. Tmote Sky Tmote Sky is an ultra low power wireless module for use in sensor works, monitoring applications, and rapid application prototyping. Tmote Sky leverages industry standards like USB and to interoperate seamlessly with other devices. By using industry standards, integrating humidity, temperature, and light sensors, and providing flexible interconnection with peripherals, Tmote Sky enables a wide range of mesh work applications [4]. The TMote is one of the most monly used motes in wireless sensor technology. Any type of sensor can be used in bination with this type of mote. Tmote Sky features the Chipcon CC2420 radio for wireless munications. The CC2420 is an IEEE pliant radio providing the PHY and some MAC functions [5]. With sensitivity exceeding the IEEE specification and low power operation, the CC2420 provides reliable wireless munication. The CC2420 is highly configurable for many applications with the default radio settings providing IEEE pliance. ZigBee specifications can be implemented us