Qualification: 
MCA, MSc, M.Tech, B-Tech
jisha@am.amrita.edu

Jisha R. C. currently serves as an Assistant Professor (Sr.Gr.) at the Department of Computer Science Applications at Amrita School of Engineering, Amritapuri. Jisha R. C. has qualified a DOEACC Level B Examination deemed professionally equivalent to M. C. A. by Govt. of India. She has pursued an M. Tech in Wireless Networks and Applications.

Publications

Publication Type: Conference Paper

Year of Publication Publication Type Title

2018

Conference Paper

Jisha R. C., Mathews, M. P., Kini, S. P., Kumar, V., V, H. U., and M, S., “An Android Application for School Bus Tracking and Student Monitoring System”, in IEEE ICCIC Dec 13 – 15, 2018, Madurai,TN,India., 2018.

2018

Conference Paper

Jisha R. C., Krishnan, R., and Vikraman, V., “Mobile Applications Recommendation Based on User Ratings and Permissions”, in International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, India, 2018.[Abstract]


Nowadays a large number of portable android applications are coming in the market. So, it has become a very difficult task for the user to ensure the security of the mobile applications that he wants to install. So, to simplify this, we propose a mobile App recommender system with popularity and security awareness. The design aspect is to recommend the mobile applications by evaluating the security risks of mobile apps and popularity based on user ratings. We use a web crawler which indexes the applications and store it in a database. Then the applications are clustered based on its popularity and user ratings. Whenever a query executes the proposed android application lists out apps from Google Play Store with its security rating. The security risk of the applications mainly depends on permissions that the application uses and its user popularity. The objective of this paper is to provide an effective recommendation system without compromising security aspects and popularity.

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2017

Conference Paper

Jisha R. C., Jyothindranath, A., and Kumary, L. S., “Iot based school bus tracking and arrival time prediction”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.[Abstract]


Nowadays, parents are perturbed about school going children because of the increasing number of cases of missing students. On occasion, students need to wait a much longer time for arrival of their school bus. There exist some communication technologies that are used to ensure the safety of students. But these are incapable of providing efficient services to parents. This paper presents the development of a school bus monitoring system, capable of providing productive services through emerging technologies like Internet of Things (Iota). The proposed IoT based system tracks students in a school bus using a combination of RFID/GPS/GSM/GPRS technologies. In addition to the tracking, a prediction algorithm is implemented for computation of the arrival time of a school-bus. Through an Android application, parents can continuously monitor the bus route and forecast arrival time of the bus.

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2017

Conference Paper

P. Das, Jisha R. C., and Dr. Sajeev G. P., “Adaptive web personalization system using splay tree”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.[Abstract]


Web personalization helps in understanding the user interests and creating customized experiences for users. However the user preferences changes dynamically over a period. In order to adapt with the changing information needs of the user, we have developed a novel web personalization system that captures the user changing interest by analyzing the timing information. We use splay tree, which is a self-adaptive data structure, for tracking the changing trends of the users. The proposed web personalization model is validated by building a simulation model, with real and synthetic dataset, and the quality of results are promising.

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2017

Conference Paper

P. Devika, Jisha R. C., and Dr. Sajeev G. P., “A novel approach for book recommendation systems”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, Chennai, India, 2017.[Abstract]


Recommendation systems are widely used in ecommerce applications. A recommendation system intends to recommend the items or products to a particular user, based on user's interests, other user's preferences, and their ratings. To provide a better recommendation system, it is necessary to generate associations among products. Since e-commerce and social networking sites generates massive data, traditional data mining approaches perform poorly. Also, the pattern mining algorithm such as the traditional Apriori suffers from high latency in scanning the large database for generating association rules. In this paper we propose a novel pattern mining algorithm called as Frequent Pattern Intersect algorithm (FPIntersect algorithm), which overcomes the drawback of Apriori. The proposed method is validated through simulations, and the results are promising.

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2016

Conference Paper

Jisha R. C., Hari, S., and Shyba, S., “A novel approach for document extraction based on SVD and FCA”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 2016.[Abstract]


Nowadays Information Retrieval (IR) is difficult because of huge amount of information published on the Internet. So it is very relevant to organize documents based on its content. The proposed work address this issue by generating concepts from the documents and these documents are grouped based on a data mining approach. To generate the concept, keywords are extracted from the documents but the extracted set is very large. So for dimensionality reduction, SVD is applied. This paper proposes a novel approach for document clustering based on Formal Concept Analysis (FCA). Concept generation and dimensionality reduction are the two issues addressed here. FCA approach leads to give a fast searching result based on the domain specific keyword. The test result shows that the dimensionality reduction is attained after applying SVD.

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2016

Conference Paper

S. S., S., R., and Jisha R. C., “A Real Time Patient Monitoring System for Heart Disease Prediction Using Random Forest Algorithm”, in Advances in Signal Processing and Intelligent Recognition Systems, Cham, 2016, vol. 425, pp. 485-500.[Abstract]


The proposed work suggests the design of a health care system that provides various services to monitor the patients using wireless technology. It is an intelligent Remote Patient monitoring system which is integrating patient monitoring with various sensitive parameters, wireless devices and integrated mobile and IT solutions. This system mainly provides a solution for heart diseases by monitoring heart rate and blood pressure. It also acts as a decision making system which will reduce the time before treatment. Apart from the decision-making techniques, it generates and forwards alarm messages to the relevant caretakers by means of various wireless technologies. The proposed system suggests a framework for measuring the heart rate, temperature and blood pressure of the patient using a wearable gadget and the measured parameters is transmitted to the Bluetooth enabled Android smartphone. The various parameters are analyzed and processed by android application at client side. The processed output is transferred to the server side in a periodic interval. Whenever an emergency caring arises, an alert message is forwarded to the various care providers by the client side application. The use of various wireless technologies like GPS, GPRS, and Bluetooth leads us to monitor the patient remotely. The system is said to be an intelligent system because of its diagnosis capability, timely alert for medication etc. The current statistics shows that heart disease is the leading cause of death and which shows the importance of the technology to provide a solution for reducing the cardiac arrest rate. Apart from that the proposed work compares different algorithms and proposes the usage of Random Forest algorithm for heart disease prediction.

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2010

Conference Paper

Jisha R. C., Dr. Maneesha V. Ramesh, and Lekshmi, G. S., “Intruder Tracking Using Wireless Sensor Network”, in 2010 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2010, Coimbatore, 2010, pp. 389-393.[Abstract]


Nowadays, almost all the countries are facing threats from terrorists and intruders from their border areas, challenging the internal security of the country in those areas. So many civilian and military applications require locating an intruder in a secured area. Target tracking, data processing and analysis play a major role in this type of applications. The proposed system is to develop a centralized computer application that needs to identify moving objects in a specific area using sensors. The system will be basically designed to detect human intruders. The objective is to design and implement an object tracking system using a wireless sensor network. This application is able to detect and track objects, and report direction and speed of the intruder to a central base station. The human intruder is detected using a passive infrared (PIR) sensor. The sensor is connected to a MICAz sensor node. The PIR sensor is able to detect the humans and provide information about the direction of the movement. The gathered information from the sensor network is to be given to the base station for processing. The proposed system provides an environment for easy deployment and which does not require any existing infrastructure or constant monitoring by humans. © 2010 IEEE.

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PDF iconIntruder-Tracking-Using-Wireless-Sensor-Network.pdf

Publication Type: Journal Article

Year of Publication Publication Type Title

2015

Journal Article

P. K. Binu, Jisha R. C., Sai, A., and Salim, S., “A Hadoop Based Architecture Using Recursive Expectation Maximization Algorithm for Effective and Foolproof Traffic Anomaly Detection and Reporting”, vol. 10, pp. 2101-2106, 2015.[Abstract]


The proposed work suggests a model to sense various traffic anomalies like accidents, celebrations, protests, disasters etc., and thereby avoiding the traffic congestion in those areas so that the travelers can save their time and money by the automatic route suggested by the application. The system also proposes a method to check the authenticity of those detected anomalies with the help of social media. The application works in a distributed environment where an android application acts as the client, J2EE application as server and Hadoop in the back-end. The client side application contains basic navigation features along with an interface to report various traffic anomalies by the users. The proposed work maintains a twitter account to tweet the exact location and incident details to post automatically by the system. The authenticity of those reported incidents/anomalies are verified by the Recursive Expectation Maximization Algorithm. After ensuring the authenticity of the reported anomaly, all the users in that particular route will get intimation in advance. The system also suggests a best alternate path to the destination. MapReduce framework is used to process bulk amount of GPS data received during travelling with the help of Hadoop based infrastructure which is deployed in the backend. The system has been tested successfully using android and GPS location spoofing application.

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