Research Article Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks Mohammad Jalil Piran, Amjad Ali, and Doug Young Suh Electronics and Radio Engineering Department, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do 446-701, Republic of Korea Correspondence should be addressed to Doug Young Suh; suh@khu.ac.kr Received 3 November 2014; Accepted 3 February 2015 Academic Editor: Chunlin Chen Copyright © 2015 Mohammad Jalil Piran et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unifed interpretation. Te best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and defnitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET). In the proposed technique, we considered four input sensor readings (antecedents) and one output (consequent). Te employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, Te Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash Severity is considered as the consequent variable. Te processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes. 1. Introduction Wireless sensor networks (WSNs) are composed of a large number of sensor nodes, which are constrained in power and communication range and are having multimodal sensing capacity. Te tiny motes consist of sensing, data processing, and communication components, which leverage on the idea of sensor networks based on the collaborative efort ofa large number of nodes [1]. Te operations of the network are performed under environmental conditions, which are characterized by low signal-to-noise ratio, interference, and multipath efects [2]. Te nodes are randomly distributed over a region to detect a physical phenomenon or an event. Te harsh felds and power constraint may make some sen- sor nodes inoperable. Hence, the network’s lifetime mainly depends on the power source. Due to the network constraints, it is necessary to fnd out some techniques that improve the fow of information. One of the suggested solutions is data aggregation or data fusion. Data fusion techniques provide a single data by collecting a set of various source data. Data fusion can reduce the amount of data fowing and the energy consumed for data processing and transmission by eliminat- ing redundant data. As a defnition, data fusion is a process of combining information from several sources to reduce ben- efciary and reliable information. In WSNs, data fusion can be achieved by deletion of redundancy, energy consumption, and assuring fault-tolerance among sensor nodes. In order to reduce nodes’ power consumption and con- sequently enlarge the network life time, numerous research works considered data aggregation and sensor fusion tech- niques, such as those regarding aggregation, metadata nego- tiation, or data fusion [3–8]. Te authors in [3] address the fusion problem in WSNs where the cross-correlation between the estimates is unknown. With the assumptions that the covariance matrix has a prior distribution and also information about the covariance of each estimate is known, the conditional distribution of the ofdiagonal blocks is derived. In [4], the authors focused on a data aggregation mechanism to the number of transmissions and thereby minimize energy consumption. For congestion Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2015, Article ID 439272, 9 pages http://dx.doi.org/10.1155/2015/439272