• Kulkarni Nikhil
• Duvvuri Sai Pravallika

Technological advancements has enabled the rapid growth and improved methods in the signal processing. Today, signal processing algorithms play a vital role in security measures taken to curb many menacing attacks all over the globe. Image processing has taken the signal processing algorithms to the next level where the security protocols are executed with improved efficiency. Mobile units with image processing capabilities have become handy in understanding various parameters related to the digital world and have become a powerful tool to analyse high-risk conditions. There are several methods that are put forth for the improved efficiency and increase in the rapidity of the processing mechanisms so as to achieve better results. This paper describes one such processes and deploy a mobile unit with image processing capabilities to provide reconnaissance. This robot is self-driven and also operates over the network. The robot provides the vigilance over a zone in which it is deployed. This will identify any trespassing and notifies to the master control of the device. Here we also discuss briefly about the algorithms that are used to identify the images using deep learning and how the different algorithms improve the accuracy and rate of processing.

datasets, pickle formats, encoders, detectors, deep learning, eigen faces, SMTP, HOG, HNN, Haar-Cascades

"Semi-Autonomous Robot for Reconnaissance", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.368-372, January-2019, Available :http://www.jetir.org/papers/JETIR1901847.pdf

"Semi-Autonomous Robot for Reconnaissance", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp368-372, January-2019, Available at : http://www.jetir.org/papers/JETIR1901847.pdf