Qualification: 
MSc
Email: 
rekhap@am.amrita.edu

Rekha P. currently serves as a Research Associate at the Amrita Center for Wireless Networks & Applications (Amrita WNA), Amritapuri. She is pursuing Phd in the area of Wireless Sensor Networks. She holds a Masters degree in Applied Electronics and possess industrial experience in product development, testing and documentation activities in the embedded domain. Rekha was involved in the project, WINSOC, India’s first ever wireless sensor network to detect rain induced landslides.

Academic Information

First degree :   B. Sc. Computer Science, Kerala University
Postgraduation :   M. Sc. Applied Electronics & Computer Technology, M. G. University

Professional Experience

  • An active member of WINSOC landslide detection project deployment team undertaken by Amrita Vishwa Vidyapeetham in association with the European Union. 
  • Active member of R T Labs project, implemented by the Amrita Center for Wireless Networks and Applications.
  • 2008 – till date: Research Associate at Amrita Center for Wireless Networks & Applications
  • 2006 – 2007: Software Engineer at Chip Integration Technologies Limited, Bengaluru, India. Product development, testing and documentation in embedded systems domain.
     

Awards and Achievements

  • Best Poster Award SenSys2013

Publications

Publication Type: Book Chapter

Year of Publication Publication Type Title

2016

Book Chapter

K. Sangeeth, Preeja Pradeep, Rekha, P., P., D., Aryadevi, R. D., and Sudheer, M., “Over the Air Programming Method for Learning Wireless Sensor Networks”, K. J. Kim and Joukov, N. ICISA 2016, Vietnam: Springer Singapore, 2016, pp. 555–566.

2012

Book Chapter

Dr. Maneesha V. Ramesh, Anjitha, S., and Rekha, P., “Wireless Sensor Network Based Ubiquitous Multi-Context Modeling and Reasoning”, in CAC‐WSN, Korea: Springer, 2012, pp. 721–728.[Abstract]


Ubiquitous Computing with Context Awareness is emerging as a significant technology which is capable of supporting a wide variety of real world applications such as health care, environmental monitoring, security, etc. Most of the existing Context aware frameworks developed are single-application oriented. The key focus of our research work is to bring in multiple application support using single context aware framework. The proposed Ubiquitous Multi-Context Model (UMM) contains a new module “Context Categorizer” for spanning multiple real world applications. The designed model support non redundant information capturing and appropriate data sharing among multiple applications, by utilizing the potentials of wireless sensor networks. The implementation of the proposed model considers two relevant applications, health care and crowd behavior estimation, which are gaining attention nowadays.

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Publication Type: Conference Paper

Year of Publication Publication Type Title

2016

Conference Paper

V. M. Lekshmy, Rekha, P., and Dr. Maneesha V. Ramesh, “Impact of algorithm complexity on energy utilization of wireless sensor nodes”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016.[Abstract]


Nowadays wireless sensor networks are implemented in a variety of fields to obtain real-time measurements. These networks are comprised of small, low cost devices called wireless sensor nodes (WSN). There are different types of wireless sensor nodes available in the market. Based on the requirements, wireless sensor nodes can be selected for each application. Power consumption is a major aspect in developing wireless sensor applications. In this paper, analysis of power consumption in different sensor nodes is conducted based on algorithms with different complexities. The experimental analysis results show that at a particular input current limit, Waspmote consumes 15% less power than MICAz mote in the case of O (1), 11.04% less in the case of O (n), 7.6% less in the case of O (n2), 3.9% less in case of O (log n) and 18.06% less in case of O (m+n)complex algorithms.

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2015

Conference Paper

Preeja Pradeep, P., D., Devi, R. D. A., Rekha, P., Sangeeth, K., and Dr. Maneesha V. Ramesh, “A Remote Triggered Wireless Sensor Network Testbed”, in 2015 Wireless Telecommunications Symposium (WTS), 2015.[Abstract]


This paper presents a remote triggered wireless sensor network (WSN) testbed used to facilitate multi-user remote access to the WSN experiments for virtual learning of wireless sensor network concepts. This testbed provides multiset, multi-group of WSN experimental setup that is capable to provide opportunity to perform remote code editing using over the air programming mechanism. This testbed also provides an intuitive web-based interface to the registered users for running the experiments, accessing and editing the source code of the experiment from anywhere in the world by means of internet. This remote triggering mechanism offers the user a flexible environment for the experimentation. An experimentation setup of 150 wireless sensor nodes are developed to suit the design of both indoor and outdoor experiments. The outdoor lab setup allows the users to learn the wireless propagational effects in the real environment. The WSN indoor lab setup comprises of nine sensor network experiments which allows the users to learn the WSN concepts such as configuring a WSN, clustering mechanisms, time synchronization mechanisms and experience the practical implementation in real time. This test bed offers the researchers and students an opportunity to trigger their inquisitiveness by providing the access to remote equipments and materials needed for the experimentation, shared via virtual manner wherein the experiment conduction and output observation can be performed online through an effective visualization tool.

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2015

Conference Paper

Preeja Pradeep, P., D., Devi, R. D. Arya, Rekha, P., Sangeeth, K., Tinu, V., and Dr. Maneesha V. Ramesh, “An Energy Aware Schedule Based Remote Triggered Wireless Sensor Network Laboratory”, in 5th International Conference on IT Convergence and Security (ICITCS), Malaysia, 2015.[Abstract]


Over the past decade, experimentation for wireless sensor network (WSN) has been widely used to enrich the learning experience of educators and learners. Our remote triggered WSN laboratory is a multi-set, multi-group, WSN experimental setup that provides an intuitive web-based interface to carry out remote experimentation as well as code editing by registered users. This paper presents a multi-level time based scheduling algorithm for our lab which provides optimum utilization, performance and service. Our WSN testbed consists of more than 150 sensor nodes deployed in indoor and outdoor environment. Energy efficiency and delay optimization of WSN testbed are ensured in the design which employs TDMA and state transition schemes. We have implemented and tested two approaches for energy efficiency namely an on demand scheduling and a TDMA based approach which incorporates state transition and CDMA. The performance evaluation result shows that 78% power consumption has been reduced in second approach compared to first. The paper details the implementation of energy efficiency with dynamic scheduling for our real-time remote triggered WSN.

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2015

Conference Paper

K. Sangeeth, Preeja Pradeep, P., D., Rekha, P., Devi, R. D. Arya, Sheeja, L., and Dr. Maneesha V. Ramesh, “A Remote Code Editing Framework for AMRITA Remote Triggered WSN Laboratory”, in 5th International Conference on IT Convergence and Security (ICITCS), Malaysia, 2015.[Abstract]


Our AMRITA remote triggered lab (RT Lab) for wireless sensor networks (WSN) offer the students and researchers, an easy, efficient, interactive and user friendly environment to trigger their inquisitiveness by providing them with the sensors, equipments, hardwares and study materials for conducting the lab experiments. RT Lab offers a web-based e-learning platform for the registered users to perform experimentation and coding remotely based on the provided study materials which are shared to them virtually. The users can learn nesC programming language and conduct the coding by means of the code editing interface. The sensor nodes in the WSN testbed, deployed in indoor and outdoor environment, undergoes remote reconfiguration and the sensor data's are collected by the WSN gateway. The users can observe the experimentation result such as the plotted sensor data and physical representation of the sensor network along with the remote video through the visualization tool. The paper details the design and implementation of remote code editing platform for RT Lab.

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2013

Conference Paper

Dr. Maneesha V. Ramesh, Rekha, P., Divya, P. L., and Surendran, S., “An adaptive energy management scheme for real-time landslide detection”, in Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems(SenSys), Italy, 2013.[Abstract]


Sensor nodes in wireless sensor network are powered by batteries and thus the utilization of effective energy management techniques becomes one of the most important challenges in realistic design of WSN. This paper deals with an optimal energy management scheme in Landslide detection system deployed in Kerala. Based on the meteorological, hydrological and soil parameters, sensors will be dynamically prioritized, scheduled and selects appropriate sensors for event handling. The results of this research work shows that the life time of the network has been improved due to the implementation of this adaptive energy management scheme.

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2012

Conference Paper

Dr. Maneesha V. Ramesh, Anjitha, S., and Rekha, P., “A Novel Wireless Sensor Network Architecture for Crowd Disaster Mitigation”, in 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 2012 , china, 2012.[Abstract]


Disasters aroused due to dynamic movement of large, uncontrollable crowds are ever increasing. The inherent real-time dynamics of crowd need to be tightly monitored and alerted to avoid such disasters. Most of the existing crowd monitoring systems is difficult to deploy, maintain, and dependent on single component failure. This research work proposes novel network architecture based on the key technologies of wireless sensor network and mobile computing for the effective prediction of causes of crowd disaster particularly stampedes in the crowd and thereby alerting the crowd controlling station to take appropriate actions in time. In the current implemented version of the proposed architecture, the smart phones act as wireless sensor nodes to estimate the probability of occurrence of stampede using data fusion and analysis of embedded sensors such as tri-axial accelerometers, gyroscopes, GPS, light sensors etc. The implementation of the proposed architecture in smart phones provides light weight, easy to deploy, context aware wireless services for effective crowd disaster mitigation.

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2012

Conference Paper

Dr. Maneesha V. Ramesh, Sruthy Anand, and Rekha, P., “Mobile Software Platform for Rural Health Enhancement”, in Advances in Mobile Network, Communication and its Applications (MNCAPPS), 2012 International Conference on, 2012, pp. 131-134.[Abstract]


The patients in rural areas lose their lives due to the unavailability of proper healthcare at the right time. This research work aims to develop a system suitable for continuous and real-time monitoring of rural patients to enhance healthcare facilities. The proposed system integrates existing and freely available mobile technology with wearable wireless sensors for patient monitoring. This research work has designed and developed a mobile software platform for continuous and real-time monitoring of rural patients. The prototype platform has been enhanced by integrating power optimizing and risk based data collection and transmitting methodologies. The system also provides an emergency warning message to the doctor's mobile phone. This proposed system collects the patient's health related sensor details in mobile phone, performs a first level analysis of the collected data, and transmits it to a central server for further processing. The system also enables the doctor to receive and view patient's ECG reports to a mobile phone. This paper introduces a dynamic algorithm to increase the battery life of a health monitoring mobile phone.

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2012

Conference Paper

Dr. Maneesha V. Ramesh, Divya, P. L., Rekha, P., and Kulkarni, R. V., “Performance Enhancement in Distributed Sensor Localization Using Swarm Intelligence”, in Advances in Mobile Network, Communication and its Applications (MNCAPPS), 2012 International Conference on, 2012, pp. 103-106.[Abstract]


Wireless Sensor Networks (WSNs) consist of distributed autonomous devices which sense the environmental or physical conditions cooperatively and pass the information through the network to a base station. Sensor Localization is a fundamental challenge in WSN. Location information of the node is critically important to detect an event or to route the packet via the network. In this paper localization is modeled as a multi dimensional optimization problem. This problem is solved using bio inspired algorithms, because of their quick convergence to quality solutions. Distributive localization is addressed using Particle Swarm Optimization (PSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). The performances of both algorithms are studied. The accuracy of both algorithms is analyzed using parameters such as number of nodes localized, computational time and localization error. Comparison of both the results is presented. A simulation was conducted for 100 target nodes and 20 beacon nodes, which resulted in CLPSO being 80.478% accurate, and PSO 61.48% accurate. The simulation results show that the PSO based localization is faster and CLPSO is more accurate.

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2012

Conference Paper

Dr. Maneesha V. Ramesh, Divya, P. L., Kulkarni, R. V., and Rekha, P., “A Swarm Intelligence Based Distributed Localization Technique For Wireless Sensor Network”, in Proceedings of the International Conference on Advances in Computing, Communications and Informatics, 2012, pp. 367-373.[Abstract]


Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. Sensor Localization is a fundamental challenge in WSN. In this paper localization is modeled as a multi dimensional optimization problem. A comparison study of energy of processing and transmission in a wireless node is done, main inference made is that transmission process consumes more than processing. An energy efficient distributed localization technique is proposed. Distributive localization is addressed using swarm techniques Particle Swarm Optimization (PSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) because of their quick convergence to quality solutions. The performances of both algorithms are studied. The accuracy of both algorithms is analyzed using parameters such as number of nodes localized, computational time and localization error. A simulation was conducted for 100 target nodes and 20 beacon nodes, the results show that the PSO based localization is faster and CLPSO is more accurate.

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2012

Conference Paper

Dr. Maneesha V. Ramesh, Prabaharan, P., Shameem, A. A., and Rekha, P., “DVM based Scalable and Adaptive Multipath Routing in MANET For Emergency Rescue Application”, in Wireless and Optical Communications Conference (WOCC), 2012 21st Annual, 2012, pp. 123-129.[Abstract]


Mobile ad hoc networks [MANET] are typically characterized by high mobility and frequent link failures that result in low throughput and high end-to-end delay. Present approaches to multipath routing make use of pre-computed routes determined during route discovery. All the paths are maintained by means of periodic update packets unicast along each path. In existing method best path is determined and maintained only with signal strength of disjoint paths. Signal strength between nodes is only the mobility prediction factor, which does not address the durability and stability of paths. Residual energy of nodes determines stability of path contains those nodes. Also does not consider the consistency of node through the previous behaves. This paper provides a design and a simulation frame work for measuring a Decision Value metric for mobility prediction of each alternate paths in MANET. Here a Periodic update packets measure Decision Value metric [DVM] and route maintenance is possible by means of the Signal strength between nodes, Residual energy and Consistency of each hop along the alternate paths, helps protocol to select the best scalable paths.

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Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2013

Conference Proceedings

Dr. Maneesha V. Ramesh, Preeja Pradeep, P., D., Devi, R. D. Arya, Rekha, P., Sangeeth, K., and Rayudu, Y. V., “AMRITA Remote Triggered Wireless Sensor Network Laboratory Framework”, Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems (SenSys). ACM, Italy, 2013.[Abstract]


In this paper, we present a real time remote triggered laboratory which has multi-set, multi-group of wireless sensor network experimental setup which is envisioned to provide a practical experience of designing and implementing wireless sensor networks' algorithms in both indoor and outdoor conditions. The architecture provides a remote code editing mechanism using deluge protocol that offers the user a flexible environment for the experimentation. Central and local authentication agents serve a two level security mechanism which makes the system robust to security threats. The lab is accessible for all the students in the world through internet and it will provide an intuitive web-based interface, where registered users can access the code and do code editing.

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