Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/336494
Title: Design of agent interaction system For monitoring data logging in Remote location
Researcher: Manikandan S
Guide(s): Chinnadurai M
Keywords: Computer Science
Engineering and Technology
Computer Science Cybernetics
Remote location
data logging
University: Anna University
Completed Date: 2020
Abstract: Artificial Intelligence is the concept of creating machine learning inputs that can operate autonomously with the design, construction, operation and applications. Image quality is important feature in artificial intelligence applications that require excellent Computer Vision. Machine learning Algorithm is used for Image Colour Analysis from fusing images from different spectra and different foci which improves the image quality. Autonomous Agent Interaction system is a field with wide range of applications, from bomb-sniffing robots to autonomous devices for finding humans in wreckage to home automation. Many people are interested in lowpower, high speed, reliable solutions. Agent can gather more accurate information from the resulting improved images. An agent has visual sensors and embedded into the system for acquiring data. For demonstration of this application, a scenario is created in which the agent captures the image of the object and in accordance to its configuration. It detects using the sensors, it places the object to desired location. With this complex algorithm from image processing, the data is manipulated into fast processing embedded application which produces an output on a real-time basis. To further accompany the autonomous nature of the system on field, a data logging and monitoring from a remote location via internet is also shownto explain the efficiency.An internet logging shows its capabilities in being a part of centralized operation in any industry. The Intelligent Data analysis system are used to monitor the data log from various locations. Each log is analysed and predict the result for making decision. The data log applications are analysed by using Inception Collaboration approach and test results using deep learning approach newline
Pagination: xiv, 110p
URI: http://hdl.handle.net/10603/336494
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificates.pdf58.91 kBAdobe PDFView/Open
03_vivaproceedings.pdf77.45 kBAdobe PDFView/Open
04_bonafidecertificate.pdf61.82 kBAdobe PDFView/Open
05_abstracts.pdf241.51 kBAdobe PDFView/Open
06_acknowledgements.pdf159.7 kBAdobe PDFView/Open
07_contents.pdf333.26 kBAdobe PDFView/Open
08_listoftables.pdf178.29 kBAdobe PDFView/Open
09_listoffigures.pdf185.2 kBAdobe PDFView/Open
10_listofabbreviations.pdf200.74 kBAdobe PDFView/Open
11_chapter1.pdf100.3 kBAdobe PDFView/Open
12_chapter2.pdf211.41 kBAdobe PDFView/Open
13_chapter3.pdf297.36 kBAdobe PDFView/Open
14_chapter4.pdf410.66 kBAdobe PDFView/Open
15_chapter5.pdf302.88 kBAdobe PDFView/Open
16_chapter6.pdf289.85 kBAdobe PDFView/Open
17_chapter7.pdf365.58 kBAdobe PDFView/Open
18_conclusion.pdf85.22 kBAdobe PDFView/Open
19_appendices.pdf103.9 kBAdobe PDFView/Open
20_references.pdf115.91 kBAdobe PDFView/Open
21_listofpublications.pdf79.42 kBAdobe PDFView/Open
80_recommendation.pdf94.82 kBAdobe PDFView/Open
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