This paper presents a literature review on some of the important segments in an autonomous vehicle development arena which touches real time embedded systems applications. This paper surveyed research papers on the technologies used in autonomous vehicles which includes lane detection, traffic signal identification, and speed bump detection. The paper focuses on the significance of image processing and real time embedded systems in driving the automotive industry towards autonomy and high security pathways.
See PublicationMobile WiMAX is the latest technology that promises broadband wireless access over long distance s. This mobile WiMAX has proven to be more stable and applicable for fixed, portable, noma dic and mobile network. The main consideration of Mobile WiMAX is to achieve seamless handover such that there is no loss of data. Handover is an essential process in wireless networks to guarantee continuous and effective services. The basic meaning of handover process is to provide uninterrupted connectivity when a mobile station transfers from the air interface of one base station to the air interface of another base station. The handover performance in mobile network is the most important factor that can influence the Quality of Service (QoS). The parameters such as delay, packet delivery ratio, throughput etc. are some factors which affect the WiMAX network performance. This paper aims to analyze the effect of such parameters on handover performance.
See PublicationContributed to the Wikipedia page on the topic "Lane Departure Warning System". Presented the working principle of a road lane detection system with explanation, algorithmic block diagram and an example implementation done using the concepts of Canny edge detector and Hough transform. Also presented the working principle on Lane Keeping Assist system which includes advanced image processing techniques.
See PageContributed to the Wikipedia page on the topic "Traffic sign recognition". Presented the working principle of a traffic sign recognition system with explanation, algorithmic block diagram and an example implementation done using the concepts of Gaussian smoothening and Canny edge detector. Also presented about the application of image processing techniques in traffic sign detection.
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