Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item SGR: Secure geographical routing in Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2015) Lata, B.T.; Tejaswi, V.; Shaila, K.; Raghavendra, M.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Geographical Routing Technique is a new trend in Wireless Sensor Networks in which the sensor nodes are enabled using Global Positioning Systems(GPS). This helps to easily detect the position of their neighboring nodes. The power consumption is more in the existing routing algorithms, since the nodes build the routing tables and the neighboring node IDs are determined by searching the routing table. In this paper, we have proposed Secure Geographical Routing (SGR) algorithm in which the data traffic and energy consumption is minimized using single copy data transfer. In SGR, initially one copy is transmitted to the next node using greedy approach and another copy is preserved in the sending station. If acknowledgment is not received even after timeout then the second copy is transmitted. This dynamic single copy scheme reduces the data traffic in Wireless Sensor Networks. Security algorithms are incorporated in every sensor node to prevent any malicious node attack that disturb the normal functioning of the network. Simulation result shows that the performance of the proposed algorithm is better in terms of packet delivery probability and energy consumption in comparison with existing algorithms. © 2014 IEEE.Item Ontology based approach for event detection in twitter datastreams(Institute of Electrical and Electronics Engineers Inc., 2015) Kaushik, R.; Apoorva Chandra, S.; Mallya, D.; Chaitanya, J.N.V.K.; Kamath S․, S.In this paper, we present a system that attempts to interpret relations in social media data based on automatically constructed dataset-specific ontology. Twitter data pertaining to the real world events such as the launch of products and the buzz generated by it, among the users of Twitter for developing a prototype of the system. Twitter data is filtered using certain tag-words which are used to build an ontology, based on extracted entities. Wikipedia data on the entities are collected and processed semantically to retrieve inherent relations and properties. The system uses these results to discover related entities and the relationships between them. We present the results of experiments to show how the system was able to effectively construct the ontology and discover inherent relationships between the entities belonging to two different datasets. © 2015 IEEE.Item Data trust model for event detection in wireless sensor networks using data correlation techniques(Institute of Electrical and Electronics Engineers Inc., 2017) Karthik, N.; Ananthanarayana, V.S.A wireless sensor network (WSN) is a conglomeration of scattered self organized sensor nodes to agreeably monitor the physical and surrounding conditions. These sensor nodes are equipped with limited resources such as memory, processing capability, battery power and transceiver for monitoring, processing and communicating the observed phenomena to make critical decisions with respect to collected data. Evaluating the trustworthiness of data is a primary preprocessing process of event detection in WSN. The trustworthy data which is free from data fault, inaccuracy and inconsistency is used to identify the interesting events and critical decision making in WSN. In this paper, we present our current work on data trust model that focuses on data fault detection, data reconstruction, data quality estimation for reliable event detection in WSN. The aim of this paper is to propose a novel data trust model for harsh environment of WSN to identify the events and strange environmental data behavior. This proposed framework combines different data processing methods through data correlation techniques to mitigate the data security risks of pervasive environments. © 2017 IEEE.Item Case Studies of Event Detection for Indian Power System using Signal Processing Methods(Institute of Electrical and Electronics Engineers Inc., 2021) Johnson, T.; Pathak, A.; Arya, S.A.; Dahanuwala, S.D.; Gachhi, P.; Moger, T.With the deployment of phasor measurement units (PMU) and wide area measurement system (WAMS), it is feasible to have an insight into the real-time events occurring in power systems based on measured PMU data. Any critical disturbance occurring in a power system is noted as an Event. The analysis carried out in this paper are based on PMU data inferences derived using various signal processing methods like Fast Fourier Transform, Yule-Walker Spectral Analysis, Matrix Pencil and Min-Max. The results of each of these methods have been described and an intersection of results from two or more methods are finally identified as Events. The results have been compiled on two different data sets: one for the Northern Region of Indian Power Grid and another for entire Indian power system. The data with respect to Northern Region was collected on 20th May 2020, during the cyclone Amphan, which caused many disruptions in electric power network. The second data was gathered from 30 stations all over India during an electromechanical oscillation fault. © 2021 IEEE.Item Spike Sorting and Event Detection in Neuromorphic Computing(Institute of Electrical and Electronics Engineers Inc., 2024) Vaishnavi, V.G.S.S.; Bhowmik, B.Neuromorphic computing is a cutting-edge field of research that focuses on designing and developing computer systems and hardware architectures inspired by the structure and functioning of the human brain. The main objective of neuromorphic computing is to create computational systems that imitate the parallel processing, learning, and energy efficiency observed in biological neural networks. Two essential tasks in the analysis of brain data from extracellular recordings are spike sorting and event detection. Spike sorting involves identifying and categorizing discrete neural spikes, while event detection focuses on recognizing specific patterns or occurrences within the spiking activity of neuromorphic networks. Typically, each neuron generates spikes with a characteristic shape, and these clusters correspond to the activity of different neurons. Here, the outcome of spike sorting is the identification of which spike corresponds to which neuron. In-depth analysis of the spike sorting and event detection which are two critical processes in interpreting the intricate neuronal activity that underpins brain function are provided. © 2024 IEEE.