This M. Tech. programme aims at preparing the students to take up application, research and development activities in core and some emerging areas in Computer Science, with focus on AI and AI related applications in a distributed computing environment. The programme includes advanced level courses in Computer Architecture, Networking, Algorithms, Data Bases, Distributed Computing and Computational Intelligence. This programme will provide a strong basis in Computer Science for those who opt for a serious career in industry.
The purpose of the programme is to generate human resources capable of supporting R & D activities in critical areas like automated, secured, monitoring and surveillance systems, medical diagnostics, intelligent monitoring systems etc. The diversity of platforms available for implementation and the huge volume of data available for analysis, knowledge mining activities associated with biological systems, medical field, data related to climate changes etc. attract employment opportunities.
Company: Robert Bosch Engineering and Business Solutions Private Limited, Coimbatore
Air conditioning systems in large scale buildings contribute a major portion of the energy requirements. A centralized temperature monitoring system would result in the enhancement of air conditioning services in large scale buildings. Here we develop a centralized temperature monitoring scheme suitable for office environments. Wireless sensors are placed inside a compartmentalized office area, which collects the surrounding temperature data and sends it to the cloud. The application in the cloud will receive this data, store the data and present this data graphically to the end user. In order to reduce the redundant data as well as for making the sensor network energy efficient, we carry out a data analytics algorithm to identify the redundant sensors in the network based on data correlation.
Main focus of this research work is to design an efficient and scalable RFID based hybrid indoor localization algorithm that operates over long-range RFID readers. The major objectives of this work are to design an approach that is extensible to large environments with minimal calibration and to provide high accuracy. Asset tracking is important for resource utilization and recovery. It is a service that helps locate objects instantly by providing easy access of item locations without much manual effort. We design a hybrid localization algorithm to accurately estimate the position of an object within a finite indoor space. Our approach uses power level and signal strength parameters which are readily available without the requirement of additional hardware. Furthermore, our algorithm applies intelligent region elimination techniques, thereby avoiding the use of heavy calibration and computationally complex algorithms.
The most unbeatable technology, Internet brings to people for communication is social networks. With the exponential growth of users in internet, there is an equivalent growth among internet users to regularly visit social websites for linking with their friends, sharing thoughts, photos, videos and even discuss about their day today activities. The fact these social networks are available to all the users for free, leads to various types of security issues. Image security has been a topic of research over decades. Enhancements to individual techniques and combinations proposed till date have offered different levels of security assurances. This work aim to present a technique for secure sharing of image posts in social network. The significant feature of the scheme lies in the selection of security technique based on image content, evaluation of peers with whom the image can be shared based on text classification, transliteration and tone analysis. The proposed scheme a cost effective solution as it does not require any additional hardware. The utility of the model is demonstrated by mapping the scheme with Facebook and analyzing its performance through simulation.
|FIRST SEMESTER||SECOND SEMESTER||THIRD SEMESTER||FOURTH SEMESTER|
|Modern Computer Architecture||Parallel and Distributed Systems||Elective –IV||Dissertation|
|Advanced Algorithms and Analysis||Machine Learning||Elective –V|
|Systems Security||Enterprise Architecture||Dissertation|
|Mathematical Foundations of Computer Science||Elective–II|
|Cultural Education||Negotiated Studies|
|Elective-I (General Electives)||(Mathematical Foundations) Elective-II|
|Computational Intelligence||Advanced Linear Algebra|
|Topics in Databases||Randomized Algorithms|
|Object Oriented Design||Computational Optimization|
|Computational Statistics||Random Process and Optimization theory|
|Advanced Computer Networks||Networks and Spectral Graph Theory|
|Foundations for Signal and Image Processing|
|Stream-I Machine Learning and Data Science||Stream –II Architecture and Systems||Stream –III Networks and Intelligent Systems||Stream –IV Computer Vision|
|Machine Learning for Big Data||Hardware Software Co-Design||Mobile Networks||Digital Image Processing|
|Foundations of Data Science||Parallel Computer Architecture||Principles of Software Designed Networks||Video Analytics|
|Applications of Machine Learning||Reconfigurable Computing||Wireless Sensor Networks||Medical Image Analysis|
|Statistical Learning Theory||Advanced Operating Systems||Network Security||Content Based Image and Video Retrieval|
|Natural Language Processing||Critical Systems and Verification||Pervasive Computing||Pattern Recognition|
|Information Retrieval||Compiler Optimization Techniques and Design||Agent Based Intelligent Systems||Data Compression|
|Data Mining and Business Intelligence||Computer Systems’ Performance Analysis||Scripting Languages|
|Semantic Web||Parallel Programming||Computer Crimes, Security and Cyber Laws|
|High Performance Computing||Debugging Tools|