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14 results on '"Indumathi, S. K."'

1. Design and Development of Energy Meter for Energy Consumption

Author

Hariharan, K., Vivek Ramanan, Mathiarasan, Kumar, Naresh, Krishna, D. Kesava, Joshuva, Arockia Dhanraj, Indumathi, S. K., Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Das, Biplab, editor, Patgiri, Ripon, editor, Bandyopadhyay, Sivaji, editor, Balas, Valentina Emilia, editor, and Roy, Sukanta, editor

Published
2024
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2. Fully Automated Cricket Bowling Machine

Author

Balaji, C. R., Pranav Raj, R. G., Harish, V., Indumathi, S. K., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Chaurasiya, Prem Kumar, editor, Singh, Abhishek, editor, Verma, Tikendra Nath, editor, and Rajak, Upendra, editor

Published
2022
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10. A Smart Structure for Environmental Sustainability in Rose Fields

Author

Indumathi S K

Subjects
Rose (mathematics), Computer science, Sustainability, Agricultural economics
Abstract

Indian floriculture industry has grown by multiple folds in the past decade and has become one of the top ten leading producers of varieties of flower production. This tremendous growth of floriculture industry has proportionally also contributed to the depletion of environmental system. The current work narrows down to handle the environmental hazards of rose farming in the floriculture industry through technology-driven fertilization process. The composition and quantity of nutrients, and the period of its application is very crucial for the plant’s growth.The smart fertigation process helps in providing a balanced nutrient dose to the plants.The internet of things (IoT) is defined as a network of physical objects called as “things” that have embedded with sensors and software that allow these objects to communicate with each other. These objects areaccessed, monitored and controlled remotely. While the reduction of one of the nutrients might result in poor development of the plant, overfeeding of nutrients leads of stagnation of salts and soil wilting. The paper proposes a smart IoT-based fertilizer application infrastructure for an optimal growth of plants with under a controlled usage of fertilizers.The dependency of fertilizers and insecticides during each stage of the plant development is monitored and a smart fertigation infrastructure is built to automate the process of feeding the plants with appropriate chemicals at appropriate intervals.

Published
2021

11. Deep learning enabled smart charging technology for electric vehicles.

Author

Sheeba, T. Blesslin, Sharanya, C., Nayanatara, C., Indumathi, S. K., Kalins, K., and Rajathi, G. Ignisha

Subjects
ELECTRIC charge, DEEP learning, ARTIFICIAL neural networks, MNEMONICS, ELECTRIC vehicles, FUTURES sales & prices
Abstract

Reliability, efficiency, and cost-effectiveness of smart grids are enhanced with power demand softening by means of efficient load management in electric vehicles. In such initiatives, the involvement of EV users may reduce due to the lack of adaptable user-centric approaches. During the connection sessions, the EV charging time is determined using a deep learning algorithm-based smart charging strategy proposed in this paper. Here, the total energy cost of the vehicle is minimized by making charging decisions considering demand time series, pricing, environment, driving, and other auxiliary data. The memorization technique is used for the estimation of the optimal solution of the existing connection sessions in the initial stage. The deep learning models are trained with this existing data and optimal decisions to make suitable decisions in real-time scenarios where car usage or future energy price values are undetermined. A significant reduction in the charging cost is observed by training the neural network with the proposed model. The results obtained are compared to the optimal charging costs computed and are found to be closely similar. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Performance Analysis of Controller for Non-Linear System using Model Based and Data Driven Techniques.

Author

Indumathi, S. K. and Ramachandraiah, U.

Subjects
*NONLINEAR systems, *NONLINEAR analysis, *LIQUID fertilizers, *FOOD industry, *SYSTEM identification, *STORAGE tanks, *BACTERIAL leaching
Abstract

The main challenge for every sector is regulating the flow and level of the liquid during the process. In various manufacturing sectors, the conical tank is frequently employed. The conical tank's design causes non-linearity, therefore controlling the liquid level in a conical tank process is the most difficult issue. As a result, the process output may occasionally be impacted. The level control of the conical process has been the subject of a great deal of research. A conical bottomed tank is utilized for complete fluid drainage in various process industries, where its nonlinearity may only be at the bottom. The tank can be made entirely conical to increase drainage effectiveness even further. However, because of the tank's constant change, the process is highly nonlinear, making it challenging to manage the liquid level. Most commonly, a conical-shaped tank system is used in colloidal mills, leaching extractions in the chemical and pharmaceutical industries, food processing industries, petroleum industries, molasses, liquid feed and liquid fertilizer storage, chemical holding and mix tanks, and reactor tanks for the processing of biodiesel. Conical tanks are employed in storage and holding tanks to prevent settlement and sludge. On the basis of traditional modelling (transfer function modelling), system identification and data-based methodology, modelling and controller design are carried out on a single conical tank. Based on time domain specifications, the performance of the designed controllers is examined. Data-based controller design has been shown to be superior to the other two strategies. A controller is designed and then modelled using the MATLAB platform. [ABSTRACT FROM AUTHOR]

Published
2022
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