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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Shivashankar, Shivashankar
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Bio-signals compression using auto-encoder N., Sunilkumar K.; Shivashankar, Shivashankar; Keshavamurthy, Keshavamurthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp424-433

Abstract

Latest developments in wearable devices permits un-damageable and cheapest way for gathering of medical data such as bio-signals like ECG, Respiration, Blood pressure etc. Gathering and analysis of various biomarkers are considered to provide anticipatory healthcare through customized applications for medical purpose. Wearable devices will rely on size, resources and battery capacity; we need a novel algorithm to robustly control memory and the energy of the device. The rapid growth of the technology has led to numerous auto encoders that guarantee the results by extracting feature selection from time and frequency domain in an efficient way. The main aim is to train the hidden layer to reconstruct the data similar to that of input. In the previous works, to accomplish the compression all features were needed but in our proposed framework bio-signals compression using auto-encoder (BCAE) will perform task by taking only important features and compress it. By doing this it can reduce power consumption at the source end and hence increases battery life. The performance of the result comparison is done for the 3 parameters compression ratio, reconstruction error and power consumption. Our proposed work outperforms with respect to the SURF method.
Cluster based water leakage detection frame work for the improvement of water management using WSN Shivashankar, Shivashankar; Rajgopal, Manjunath; Karani, Krishna Prasad; Basavaraju, Nandeeswar Sampigehalli; Giddappa, Erappa; Swamy, Shivakumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp603-612

Abstract

Water is a vital resource that is essential for human survival and economic development. In any case, water shortage and wastage have become significant difficulties that undermine economical turn of distribution network. A critical reason for water wastage is water leakage in the distribution system, which prompts an extensive loss of water assets and energy. Conventional manual techniques for identifying water leakage are tedious, work serious, and frequently ineffectual. Hence, there is a need for an automated system that can efficiently detect, control and monitor water leakage to improve water management. In this paper, cluster-based water leakage detection (CBWLAD) algorithm for the improvement of water management using wireless sensor network (WSN) is proposed. The design system contains sensor nodes which are conveyed all through the water distribution networks and associated with central control unit. The sensor nodes can distinguish changes in the water pressure and flow rate, which are indicative of water leakage. The real time monitoring feature also enables timely maintenance and repair of the network of water distribution prolongs the lifespan of infrastructure. Further, the research and development are required to optimize the system’s performance and adapt it to real-world scenarios.
Blockchain and machine learning driven agricultural transformation framework to enhance efficiency, transparency, and sustainability Shivashankar, Shivashankar; Prasad Karani, Krishna; Rajgopal, Manjunath; Totad, Sarala; Giddappa, Erappa; Swamy, Shivakumar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp1976-1988

Abstract

The agricultural sector is undergoing a transformative journey empowered by technological innovations. In this context, this research work endeavors to revolutionize the agricultural supply chain (ASC) by developing a comprehensive online platform that connects sellers, farmers, and customers. Through meticulous planning, design, and implementation, the system aims to streamline the process of buying and selling agricultural products, thereby fostering efficiency, transparency and accessibility. The key features include user registration, product management, order tracking, and blockchain-machine learning (ML) based transaction security. The proposed research work's success hinges on thorough testing and validation, ensuring its reliability and usability. By leveraging technology to bridge gaps in the agricultural ecosystem, this proposed work seeks to empower stakeholders and contribute to the sustainable growth of the agricultural industry. In the current agricultural landscape in India, traceability has been a significant challenge. The industry lacks a comprehensive system that provides visibility into the source and quality of produce. Our proposed system aims to address the shortcomings of the existing agricultural ecosystem by introducing a comprehensive solution powered by blockchain technology and advanced data processing techniques.
Co-Authors Basavaraju, Nandeeswar Sampigehalli Giddappa, Erappa Karani, Krishna Prasad Keshavamurthy, Keshavamurthy N., Sunilkumar K. Prasad Karani, Krishna Rajgopal, Manjunath Swamy, Shivakumar Totad, Sarala