Qualification: 
M.Tech
ba_sabarish@cb.amrita.edu

Sabarish B. A. currently serves as Assistant Professor at Department of Computer Science and Engineering, School of Engineering, Coimbatore Campus. His areas of research include Wireless Sensors and Data Mining.

 

 

 

 

Publications

Publication Type: Journal Article

Year of Publication Publication Type Title

2018

Journal Article

B.A. Sabarish, R. Karthi, and Kumar, T. G., “Spatial Outlier Detection Algorithm for Trajectory Data”, International Journal of Pure and Applied Mathematics, vol. 118, pp. 325-330, 2018.[Abstract]


Trajectories are spatiotemporal data generated by moving objects containing the spatial position of object at various time intervals. GPS devices record this information and it is possible to construct trajectory of moving objects for analysis. Outlier analysis of trajectories is done to identify abnormal activities like intrusion detection, fraud detection, fault detection and rate event detection. In this paper, Trajectory Outlier Detection algorithm using Boundary (TODB) is proposed using a boundary construction algorithm and a binary classifier. In TODB, Convex Hull algorithm is used to construct the boundary and ray casting algorithm is used to build the binary classifier. TODB is tested for its accuracy using real world data sets. Experimental results on real world data sets demonstrate that TODB correctly classify normal and outlier trajectories

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2018

Journal Article

B.A. Sabarish, R. Karthi, and Dr. Gireesh K. T., “Clustering of trajectory data using hierarchical approaches”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 215-226, 2018.[Abstract]


Large volume of spatiotemporal data as trajectories are generated from GPS enabled devices such as smartphones, cars, sensors, and social media. In this paper, we present a methodology for clustering of trajectories to identify patterns in vehicle movement. The trajectories are clustered using hierarchical method and similarity between trajectories are computed using Dynamic Time Warping (DTW) measure. We study the effects on clustering by varying the linkage methods used for clustering of trajectories. The clustering method generate clusters that are spatially similar and optimal results are obtained during the clustering process. The results are validated using Cophenetic correlation coefficient, Dunn, and Davies-Bouldin Index by varying the number of clusters. The results are tested for its efficiency using real world data sets. Experimental results demonstrate that hierarchical clustering using DTW measure can cluster trajectories efficiently. © 2018, Springer International Publishing AG.

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2018

Journal Article

Vidhya S, B.A. Sabarish, .Rajivkrishnan, J., and .Sachin, P., “e-vaccination:Fingerprint Based Vaccination Monitoring System”, International Journal of Pure and Applied Mathematics, vol. 118, no. 7, pp. 623-627, 2018.[Abstract]


Immunization against common childhood diseases has been an integral part of mother and child health services in India. In developing countries, current vaccination status ofinfants is recorded ina paper, which is ineffective in many ways:information which may go missing, process of looking up data is tedious. The main objective of proposed work is to use biometric traits (fingerprint) of an infant to store their vaccination schedule details,thereby automating the vaccination schedule for the infant.Biometrics traits are usedsince fingerprint of infants have great potential to accurately record immunizations and helps greatly in efficiently searching the data. The proposed method aims at developing an application which provides to alerts on a regular basis toparents and Accredited Social Health Activist (ASHA) workers based on the stored vaccination schedule information.

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2016

Journal Article

Dr. Balasubramanian A. and B.A. Sabarish, “A Study on the Impact of Google Search on the Reading Habits of Academicians”, Indian Journal of Science and Technology, vol. 9, no. 21, 2016.[Abstract]


Background/Objectives: The present day students, research supervisors and faculty members depend on Google search engine as a tool for collecting information on any specific topic of interest. There is a need to understand what extent the materials selected is relevant for their work under consideration. This study investigates the outcome of the use of Google search engine for the choice of material and the reading habits among the research supervisors, research scholars, faculty members and graduate students. Methods: Questionnaires were used to conduct the survey. The responses were obtained through telephonic interviews or receiving duly filled in questionnaire through E-mail. Findings: It has been identified that search engines like Google has reduced the level of lateral thinking and force the academicians to depend on Google for information. This actively reduces the thinking process and developing innovative research ideas.

Applications/Improvements: The use of search engine has resulted in thinking less and searching more when it comes to academic purpose, which also drastically reduces the analytical capability.

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2015

Journal Article

B.A. Sabarish, Divya, C., Shankar, H., and Pradisa, S., “A novel method to preserve privacy: Two- tiered privacy preservation”, International Journal of Applied Engineering Research, vol. 10, pp. 6659-6674, 2015.[Abstract]


Advances in hardware technology like mobile phones, GPS enabled devices etc., have increased the capability to locate and store the spatio-temporal data of moving objects and thereby obtain information about individuals and their behavior. Data leakage from such Location Based Services (LBS) is increasing with the exponential growth of technology, resulting in an innate risk of privacy threats. Data, thus obtained, may be used for a variety of intrusive and malicious purposes and privacy attacks, such as user identification attack, sensitive location tracking attack, sequential tracking attack, etc. A framework is essential to the preserve location privacy of moving objects. In this paper, a two-tier security framework is proposed. In the first tier, algorithms SSET and SIMET are implemented to provide efficient means to encrypt the SIM and IMEI numbers respectively, thus protecting user identity. In the second-tier, Enhanced Privacy Framework (EPF) is used which is a combination of HERMES framework and Statistical framework that protects users against the major attacks on location privacy. Combining these two approaches, a new method named TTPP (Two Tiered Privacy Preservation) is proposed. © Research India Publications.

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2015

Journal Article

B.A. Sabarish, Mohan, Sb, MamthaShri, D. Pb, Ajit, R. Cb, and Arun, A. V. Rb, “Automating runout decisions in cricket using image processing”, International Journal of Applied Engineering Research, vol. 10, pp. 25493-25500, 2015.[Abstract]


Decision making is crucial in any part of the game to ensure fairness among the teams. An unfair decision due to human error may change the result of the game. Cricket is the game which is most worshiped after the game of soccer. This paper introduces the concept of automating run out decisions given by the third umpire, which is achieved through various image processing techniques and algorithms like Speeded Up Robust Features, absolute difference algorithm, edge detection etc. We work on the frame in which the bails have first deflected. Popping crease position and leg/bat position of the batsman in the selected frame is compared to make a decision on run out. Implementation of the system shows better accuracy than human decision and also improves the quality of decision making process. © Research India Publications.

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Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2018

Conference Proceedings

S. Krishnan, B.A. Sabarish, Gayathri V., and Dr. Padmavathi S., “Enhanced Defogging System on Foggy Digital Color Images”, Computational Vision and Bio Inspired Computing, Part of the Lecture Notes in Computational Vision and Biomechanics book series, vol. 28. Springer International Publishing, Cham, pp. 488-495, 2018.[Abstract]


Images which are captured using camera can cause degradation in images by the effect of climatic conditions such as haze and fog. Image restoration makes a notable change in performing different application of computer vision and pattern recognition. The main aim of this paper is to improve the effect of fog and hazy images compared to the existing methods. The enhanced defogging system [EDS] consists of different image improvement techniques with a Dark Channel Prior [DCP] Algorithm to estimate the amount of fog is there in the images and transmission as well. Fusion based fog removal will reduce the amount of haze remained in those images. Experiments were done more than 100 images and the results are discussed below.

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Publication Type: Conference Paper

Year of Publication Publication Type Title

2017

Conference Paper

B.A. Sabarish, Kailassh, B., Baktha, K., and Janaki, Y., “Recommendations of location for facilities using domination set theory”, in Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, 2017, vol. 2018-January, pp. 1540-1544.[Abstract]


Facility location deals with the optimal placement of a facility to reduce transportation costs. It is important for useful facilities such as schools, hospitals and police stations be placed in appropriate locations in the city for easy access. Thus, the proposed framework aims to produce dominating sets using the domination theory in a graph which serves as a purpose for facility location algorithms. To find suitable locations, junction points (Vertices) of the city are carefully identified. The points are then studied and connected (Edges) with distance between them using Google's 'My Maps' to form a graph. Using this resultant graph, an adjacency list is created which serves as an input for the dominating set algorithm. The algorithm then produces all possible dominating sets. This paper looks towards identification of all plausible dominating sets of the city graph which will thereby help facility location algorithms determine appropriate locations for the right beneficial facility. © 2017 IEEE.

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2011

Conference Paper

B.A. Sabarish and Sashirekha, K., “Clustering based energy efficient congestion aware protocol for Wireless Sensor Networks”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, ICETECT 2011, Chunkankadai, 2011, pp. 1129-1135.[Abstract]


Wireless Sensor Networks (WSNs) have inherent and unique characteristics rather than traditional networks. They have many different constraints, such as computational power, storage capacity, energy supply and etc. Energy aware routing protocol is very important in WSN, but routing protocol which only considers energy has not efficient performance. Therefore considering other parameters beside energy efficiency is crucial for protocols efficiency. Depending on sensor network application, different parameters can be considered for its protocols. Congestion management can affect routing protocol performance. Cluster-based architectures are one of the most practical solutions in order to cope with the requirements of large-scale wireless sensor networks (WSN). Cluster-head election problem is one of the basic QoS require-ments of WSNs, yet this problem has not been sufficiently explored in the context of cluster-based sensor networks. Specifically, it is not known how to select the best candidates for the cluster head roles. In this paper, we investigate the cluster head election problem and congestion management problem. Specifically concentrating on applications where the energy of full network is the main requirement, and we propose a new approach to exploit efficiently the network energy, by reducing the energy consumed for cluster forming and reducing the congestion to provide the better efficiency for the high priority data. © 2011 IEEE.

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Publication Type: Book Chapter

Year of Publication Publication Type Title

2015

Book Chapter

B.A. Sabarish, R. Karthi, and Dr. Gireesh K. T., “A Survey of Location Prediction Using Trajectory Mining”, in Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 1, P. L. Suresh, Dash, S. Subhransu, and Panigrahi, K. Bijaya New Delhi: Springer India, 2015, pp. 119–127.[Abstract]


This paper is a research and analysis on the prediction of location of moving objects that gained popularity over the years. Trajectory specifies the path of the movement of any object. There is an increase in the number of applications using the location-based services (LBS), which needs to know the location of moving objects where trajectory mining plays a vital role. Trajectory mining techniques use the geographical location, semantics, and properties of the moving object to predict the location and behavior of the object. This paper analyses the various strategies in the process of making prediction of future location and constructing the trajectory pattern. The analyses of various mechanisms are done based on various factors including accuracy and ability to predict the distant future. Location prediction problem can be with known reference points and unknown reference points, and semantic-based prediction gives an accurate result whereas the probability-based prediction for unknown reference points.

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Faculty Research Interest: 
207
PROGRAMS
OFFERED
5
AMRITA
CAMPUSES
15
CONSTITUENT
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A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
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