State transportation agency spends millions of dollars annually to maintain and improve the service provided to the drivers in the highway rest areas. In order to collect traffic data in real-time, Researchers can use the vehicle data in the rest areas. Therefore, it is helpful immensely to update the existing safety policies in the rest areas. Transportation agencies don\u2019t have any automated systems to perform \u201cautomatic\u201d and \u201creal-time\u201d vehicle identification and classification in the highway rest areas. Motivated by a dire need to enhance and modernize the transportation system, the author proposes an advanced modular system that will integrate a smart sensor to extract a rest area traffic pattern in real-time. Currently, Caltrans collects traffic data from Automated Vehicle Classification (AVC) stations and also manual census collected in the specific locations. However, this technology is too expensive, time consuming, and disruptive; therefore it has not been used widely in many different locations. In recent years, There have been many significant improvements in MEMS sensors domain with respect to size, cost and accuracy. Moreover, extreme miniaturization of RF transceivers and low power micro-controllers have motivated researchers to develop small and low power sensors and radio equipped modules. These sensors are gradually replacing traditional wired sensor systems. These modules which are often called \u201csensor mote\u201d (size of a quarter) communicate with other sensor nodes and build an intelligent network of sensors. Because of the miniaturization and low power consumption, these sensor motes are extremely efficient due to their low power budget. The authors propose a wireless MEMS sensor based automatic vehicle classification and identification system for highways rest areas. The author's developed Automatic Vehicle Classification and Identification (AVCI) system consists of two parts, AVCI sensor nodes containing magneto-resistive and accelerometer sensors. These sensors calculate speed and axles respectively. The next part, the system proposes a Access Point (AP) which collects data from sensor motes and calculate speed, axles counts and then it classifies the collected data based on Federal Highway Administration (FHWA) 13-categories Scheme-F[5]. The AP includes a RF transceiver to communicate with the sensor motes and also a GPRS (General Packet Radio Service) shield to transmit aggregated traffic data to the county or regional traffic data collection center
