Qualification: 
Ph.D, MSc
rekhap@am.amrita.edu

Dr. Rekha P. currently serves as a Assistant Professor 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
  • Doctoral degree: Ph. D., Amrita Vishwa Vidyapeetham, Amritapuri
     

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: Journal Article

Year of Publication Publication Type Title

2018

Journal Article

Dr. Maneesha V. Ramesh, Rekha, P., Sinitambirivoutin, E., and Passelaigue, F., “Design and Development of an IoT Based Smart Irrigation and Fertilization System for Chilli Farming.”, Wispnet-2018, 2018.[Abstract]


India is an agricultural country and 70% of the people directly or indirectly depends on agriculture for their living. Nowadays, water scarcity is one of the main challenges faced by the farmers. Another major challenge faced by Indian agriculture sector is the increase in rate of farmers’ suicide because of debt. So, effective measures have to be devised in order to reduce the cost of farming and increase the yield from agriculture. This research work proposes the design of a generic IoT framework for improving agriculture yield by effectively scheduling irrigation and fertilization based on the crops’ current requirements, environmental conditions and weather forecasts. This work proposes the design of an affordable irrigation and fertilization system. The proposed fertilization system spreads fertilizers to the root directly. This reduces the amount of fertilizers required and thus reduces the cost and improves the soil health. A user friendly mobile application has been designed to deliver this information to the farmers in their regional language. The generic framework has been validated using a case study for chilli farming.

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2018

Journal Article

P. Rekha, Dr. Maneesha V. Ramesh, and P. Venkat Rangan, “Building Optimal Topologies for Real-Time Wireless Sensor Networks”, Wispnet-2018, 2018.

2017

Journal Article

P. Rekha, Dr. Maneesha V. Ramesh, P. Venkat Rangan, Dr. Usha Kumari P. V., and Hemalatha, T., “Energy Efficient Data Acquisition Techniques Using Context Aware Sensing for Landslide Monitoring Systems”, IEEE Sensors Journal, vol. 17, pp. 6006-6018, 2017.[Abstract]


Real-time wireless sensor networks are an emerging technology for continuous environmental monitoring. But real-world deployments are constrained by resources, such as power, memory, and processing capabilities. In this paper, we discuss a set of techniques to maximize the lifetime of a system deployed in south India for detecting rain-fall induced landslides. In this system, the sensing subsystem consumes 77.5%, the communication subsystem consumes 22%, and the processing subsystem consumes 0.45% of total power consumption. Hence, to maximize the lifetime of the system, the sensing subsystem power consumption has to be reduced. The major challenge to address is the development of techniques that reduce the power consumption, while preserving the reliability of data collection and decision support by the system. This paper proposes a wavelet-based sampling algorithm for choosing the minimum sampling rate for ensuring the data reliability. The results from the wavelet sampling algorithm along with the domain knowledge have been used to develop context aware data collection models that enhance the lifetime of the system. Two such models named context aware data management (CAD) and context aware energy management (CAE) have been devised. The results show that the CAD model extends the lifetime by six times and the CAE model does so by 20 times when compared with the continuous data collection model, which is the existing approach. In this paper, we also developed mathematical modeling for CAD and CAE, which have been validated using real-time data collected in the past.

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2016

Journal Article

P. Rekha, Dr. Maneesha V. Ramesh, Dr. Usha Kumari P. V., and P. Venkat Rangan, “Energy Sustenance in Context Aware Landslide Monitoring systems”, Sensys 2015, InfoComm2016, 2016.

2014

Journal Article

Dr. Maneesha V. Ramesh, Shanmughan, A., and Rekha, P., “Context Aware Adhoc Network for Mitigation of Crowd Disasters”, Ad Hoc Networks, vol. 18, pp. 55-70, 2014.[Abstract]


Our research works focuses on the design and implementation of a novel ubiquitous multi context-aware mobile phone sensing network for mitigation of crowd disasters using machine-to-machine (M2M) communications. A mobile sensor network system integrated with wireless multimedia sensor networks (WMSNs) was designed for effective prediction of a stampede during crowd disasters. This proposed sensor network consists of mobile devices that are used as crowd monitoring participant nodes that employ light sensors, accelerometers, as well as audio and video sensors to collect the relevant data. Real-time crowd dynamics modeling and real-time activity modeling have been achieved by implementing the algorithms developed for Context Acquisition and multi-context fusion. Dynamic crowd monitoring was achieved by implementing the context based region identification and grouping of participants, distributed crowd behavior estimation, and stampede prediction based on distributed consensus. The implementation of the proposed architecture in Android smartphone provides light-weight, easy to deploy, context aware wireless services for effective crowd disaster mitigation and generation of an in time alert to take measures to avoid the occurrence of a stampede. The system has been tested and illustrated within a group of people for stampede prediction by using empirically collected data.© 2013 Elsevier B.V.

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PDF iconContext-Aware-Adhoc-Network-for-Mitigation-of-Crowd-Disasters.pdf

Publication Type: Conference Paper

Year of Publication Publication Type Title

2017

Conference Paper

P. Rekha, P. Venkat Rangan, Dr. Maneesha V. Ramesh, and K. V. Nibi, “High Yield Groundnut Agronomy: An IoT Based Precision Farming Framework”, in 2017 IEEE Global Humanitarian Technology Conference (GHTC), 2017.[Abstract]


Agriculture is one of the main needs for human to survive. Agriculture has to tackle many problems like changing climate, water shortage, changing soil quality, etc. Due to the increasing demand for cereals and other crops for daily usage by the consumers there is a need for smarter implementation of irrigation and also develop farming methods that alter the basic eco systems and is less harmful to other creatures. India is one of highest crop producing countries all over the world. At the same time, India is facing the challenge of farmers committing suicide because of crop failure and debt. Most of the land in India is still being used for agriculture purposes. Still there exists several places that uses very primitive methods for irrigation, fertilization etc. This leads to the reduction in the crop yield and eventually less income for the farmers. This paper discusses the design and development of an IoT framework that helps farmers to improvise their methods of farming and also make the best use of their land for a better yield and income. The major goal of this IoT framework is to sense agriculture characteristics and advice farmers to properly grow and treat the crops. The system deploys a group of wireless sensor networks nodes deployed in the field for sensing agricultural parameters and the RF communication of WSN node is used to transmit the measured data to base station. Base station is connected to a decision support system. Based on the sensed parameters and the optimum values, the decision support system will generate an appropriate message for farmers. By using the collected data from the sensors, the proposed system will provide suggestions about the monitoring crop such as irrigation timings, directions for optimum usage of fertilizers etc. in accordance to the farmers' lands. An android application has been designed to deliver the messages to farmers in their regional language. The android app also gives information regarding the weather forecast and precaution to be taken based on the weather forecast.

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2016

Conference Paper

Balaji Hariharan, P. Venkat Rangan, Simi Surendran, Rekha, P., Arya Devi R. D., and Dr. Maneesha V. Ramesh, “Delay and energy optimization in multilevel balanced WSNs for landslide monitoring”, in 2016 IEEE Global Humanitarian Technology Conference (GHTC), 2016.[Abstract]


In most of the real world wireless sensor network deployments, the energy utilization is a critical factor as the nodes are battery powered. In most of the real-world deployments it is observed that the sensing subsystem consumes higher power. In order to extend the lifetime of such systems it is required to reduce the sensing energy than communication energy. We have deployed a system for monitoring Landslides in India consists of 150 geo-physical sensors and used solar panels to power these sensor nodes. The decision making in favor of Landslide occurrence is based on the maximum values obtained from the high priority sensors. As this maximum value is not frequently changing in the deployment, locating the sensor node with maximum value allows us to switch off the other sensors for a predetermined period of time. This work proposes an optimal balanced network topology for delay minimization by parallelizing data aggregation operation in each sub-network. The sensor node switch off schemes on the top of delay minimized topology enables the optimal utilization of the available solar power. The analysis of these mechanisms shows that, more number of nodes can be powered with the available source of energy and can increase the network life time.

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PDF iconDelay-and-energy-optimization-in-multilevel-balanced-WSNs-for-landslide-monitoring.pdf

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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PDF iconImpact-of-Algorithm-Complexity-on-Energy-Utilization-of-Wireless-Sensor-Nodes.pdf

2015

Conference Paper

V. V.T., Sasidhar, K., and Rekha, P., “A status quo of WSN systems for agriculture”, in 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015, 2015, pp. 1775-1781.[Abstract]


Wireless Sensor Networks have revolutionized mobile Computing in the past decade or so. A myriad of systems have been designed and developed for various applications, most commonly, environmental monitoring, water quality monitoring, structural monitoring etc. One particular domain where there is a dearth of sensor networks implementation is agriculture. The advantages of sensor networks have not been leveraged for agriculture, particularly in the Indian agriculture scenario. Indian agriculturists or farmers have been using primitive methods such as use of bullock karts for plowing, use of Persian water wheel to collect water for irrigation, manual sowing, Harvesting of crops manually, etc. With India's major economy earnings coming from agricultural products, it is imperative to use technology to improve productivity and consequently the economic growth of the country. This work presents a survey of wireless sensor network systems deployed for the agricultural domain. We clearly lay out the working methodologies and the drawbacks of existing systems, build upon them and finally propose our idea of a wireless sensor network for estimating crop yield that would help the farmer in making a right decision in choosing the right kind of crop. © 2015 IEEE.

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2015

Conference Paper

Sangeeth K., Preeja Pradeep, P., D., Rekha, P., Arya Devi R. D., L., S., 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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PDF iconA-Remote-Code-Editing-Framework-for-AMRITA-Remote-Triggered-WSN-Laboratory.pdf

2015

Conference Paper

Preeja Pradeep, P., D., Arya Devi R. D., Rekha, P., Sangeeth K., Tinu Vinod, 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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PDF iconAn-Energy-Aware-Schedule-Based-Remote-Triggered-Wireless-Sensor-Network-Laboratory.pdf

2015

Conference Paper

P. Rekha, P., D., Arya Devi R. D., Preeja Pradeep, K, S., K, R., and Dr. Maneesha V. Ramesh, “A Remote Triggered Laboratory for Wireless Sensor Network Experimentation”, in ICCTS2015, 2015.[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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PDF iconA-Remote-Triggered-Laboratory-for-Wireless-Sensor-Network-Experimentation.pdf

2015

Conference Paper

Preeja Pradeep, P., D., Arya Devi R. D., 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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PDF iconA-Remote-Triggered-Wireless-Sensor-Network-Testbed.pdf

2014

Conference Paper

K. Sasidhar, Sreeresmi, R., and Rekha, P., “A WSN lifetime improvement algorithm reaping benefits of data aggregation and state transitions”, in Global Humanitarian Technology Conference - South Asia Satellite (GHTC-SAS), 2014 IEEE, 2014.[Abstract]


Wireless sensor networks consist of different subsystems such as sensing, transmission, reception, power and processing systems. Battery power of sensor nodes is one of the important factors to consider in a wireless sensor system. Moreover, when such systems are deployed in remote environments for critical applications where the availability of electrical power is less, the factor presents a major constraint. Prior work has tackled this problem by introducing sleep, sense, transmit and receive states. Although most work employed these states in tree and cluster based networks they only incorporated at the leaf nodes. This paper introduces state transitions for cluster head nodes to further reduce energy. The algorithm basically combines data aggregation and state transition to improve the overall life time of the network. To validate the algorithm, we apply to a landslide monitoring and detection system and obtain 33% energy savings for leaf node and 30% energy saving for cluster head node when compared to naive algorithms that do not apply state transitions.

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2013

Conference Paper

Dr. Maneesha V. Ramesh, Rekha, P., P., D., and Simi Surendran, “An Adaptive Energy Management Scheme for Real-time Landslide Detection”, in Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, New York, NY, USA, 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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PDF iconAn-Adaptive-Energy-Management-Scheme-for-Real-time-Landslide-Detection.pdf

2013

Conference Paper

J. D. Freeman, Varghese, J. T., and Rekha, P., “WSN based heliostat control for a solar thermal cooking system”, in 2013 IEEE Energytech, 2013.[Abstract]


This paper proposes a wireless sensor network based heliostats control method for an industrial scale solar cooking system. Even though different designs are available they have suffered from different problems especially regarding effective tracking, high cost and convenience and other constraints such as scalability and simplicity. This paper, therefore, describes an efficient design that overcomes the earlier problems by using a highly precise astronomical calculation based approach along with wireless communication for efficient tracking of the sun which in turn reduces the overall system cost and simplicity. The proposed system uses a one tier wireless sensor network (WSN). The main feature of this work is the implementation of the highly accurate NREL algorithm, with precision timing provided by a GPS receiver within a low-cost wireless sensor network framework.

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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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PDF iconDVM-based-Scalable-and-Adaptive-Multipath-Routing-in-MANET-For-Emergency-Rescue-Application-.pdf

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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PDF iconA-Swarm-Intelligence-Based-Distributed-Localization-Technique-For-Wireless-Sensor-Network.pdf

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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PDF iconMobile-Software-Platform-for-Rural-Health-Enhancement.pdf

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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PDF iconPerformance-Enhancement-in-Distributed-Sensor-Localization-Using-Swarm-Intelligence.pdf

2012

Conference Paper

Dr. Maneesha V. Ramesh, Shanmugam, A., 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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PDF iconA-Novel-Wireless-Sensor-Network-Architecture-for-Crowd-Disaster-Mitigation.pdf

2012

Conference Paper

Dr. Maneesha V. Ramesh, Sruthy Anand, and Rekha, P., “A Mobile Software for Health Professionals to Monitor Remote Patients”, in 2012 Ninth International Conference on Wireless and Optical Communications Networks (WOCN), 2012.[Abstract]


introducing wireless technology to monitor patients, in remote areas. A reliable system to continuously monitor the patients in the remote areas has been developed, this software suite consists of two mobile software platforms. The first mobile software platform uses wearable wireless sensors to collect a Patient's ECG and Blood Pressure based on the patient's health condition. This sensed data is transmitted to the Patient's mobile phone where the first level of analysis is performed and an emergency warning may be indicated. If the patient's parameters are at a certain level a message is sent immediately to the Health Professional's mobile phone. The health data is also transmitted it to a central server for storage and further processing. This database can be of great value to health researchers. The second mobile software platform enables health professionals to view patient's health reports on their mobile phones from the central database. The health professional can also assign the risk levels of each patient, from the health professional's mobile phone. Both platforms communicate with the central database using a web server. This research also considers power optimization in the patient's mobile.

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PDF iconA-Mobile-Software-for-Health-Professionals-to-Monitor-Remote-Patients.pdf

Publication Type: Book Chapter

Year of Publication Publication Type Title

2016

Book Chapter

Sangeeth K., Preeja Pradeep, Rekha, P., P., D., Arya Devi R. D., and Dr. Maneesha V. Ramesh, “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, Shanmugam, A., and Rekha, P., “Wireless Sensor Network Based Ubiquitous Multi-Context Modeling and Reasoning”, in CAC‐WSN, Korea: IEEE, 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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PDF iconWireless-Sensor-Network-for-Disaster-Monitoring.pdf

Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2013

Conference Proceedings

Dr. Maneesha V. Ramesh, Preeja Pradeep, P., D., Arya Devi R. D., Rekha, P., Sangeeth K., and YV, R., “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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PDF iconPoster-Abstract-AMRITA-Remote-Triggered-Wireless-Sensor-Network-Laboratory-Framework.pdf

2012

Conference Proceedings

Dr. Maneesha V. Ramesh, G.S., L., and Rekha, P., “Integrated Wireless Sensor Network For Smart Sesame Farming”, Proceeding Int. Conf. on Computational Intelligence and Information Technology, CIIT. 2012.[Abstract]


Wireless Sensor Network technology has been used for continuous monitoring of farm lands to increase the agriculture yield. This research work proposes the design of a wireless sensor network system for continuous monitoring of sesame cultivation. It proposes a design of an integrated wireless sensor network
that senses various agriculture parameters such as soil moisture, soil pH and soil temperature. The research has developed several decision algorithms to alert the
farmers, the field conditions and the remedial measures to attain higher yield. The prototype system has been tested and the results are given along with this paper.
This work presents a cost effective technology to increase production and improve agriculture yield for sesame farming in India.

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