S
Sudeep Tanwar
Researcher at Nirma University of Science and Technology
Publications - 410
Citations - 11253
Sudeep Tanwar is an academic researcher from Nirma University of Science and Technology. The author has contributed to research in topics: Computer science & Smart grid. The author has an hindex of 43, co-authored 263 publications receiving 5402 citations. Previous affiliations of Sudeep Tanwar include Bharat Institute of Technology & University Institute of Technology, Burdwan University.
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Blockchain-Based Peer-to-Peer Transactive Energy Management Scheme for Smart Grid System
Aparna Kumari,Urvi Chintukumar Sukharamwala,Sudeep Tanwar,Maria Simona Raboaca,Fayez Alqahtani,Amr Tolba,Ravi Sharma,Ioan Aşchilean,Traian Candin Mihaltan +8 more
TL;DR: In this article , the authors proposed a decentralized and transparent P2P energy trading (DT-P2PET) scheme using blockchain, which aims to reduce the grid's energy generation and management burden while also increasing profit for both consumers and prosumers through a dynamic pricing mechanism.
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IoT Enabled real-Time urban transport management system
TL;DR: iERS uses the Internet of Things (IoT)-based infrastructure to monitor and signal the availability of different parking slots around the smart communities and provides better guidance to the users to reserve the available parking slot in comparison to the other existing solutions.
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A taxonomy of energy optimization techniques for smart cities: Architecture and future directions
TL;DR: An energy‐efficient consensus mechanism, Proof‐of‐High Performance optimization (named as PoHPo), for High‐Performance Computing (HPC) based ecosystems and a taxonomy that classifies energy optimization techniques are proposed.
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DL-GuesS: Deep Learning and Sentiment Analysis-based Cryptocurrency Price Prediction
R. Parekh,Nisarg P. Patel,Nihar Thakkar,Rajesh Gupta,Sudeep Tanwar,Gulshan Sharma,Innocent E. Davidson,Ravi Sharma +7 more
TL;DR: This paper proposes a hybrid and robust framework, DL-Gues, for cryptocurrency price prediction, that considers its interdependency on other cryptocurrencies and also on market sentiments.
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An Energy-Efficient Resource Allocation Scheme for SWIPT-NOMA Based Femtocells Users With Imperfect CSI
TL;DR: SWIPT and NOMA at Femto base station are integrated to improve the energy efficiency and spectral efficiency of femtocells and the simulation results demonstrate that the proposed scheme provides 0.2% and 31.25% higher energy-efficiency in comparison to the existing EH-NOMA and Eh-OFDMA schemes.