Rashmi Priya
Orcid: 0000-0003-2856-5858Affiliations:
- University of Missouri, Division of Plant Science and Technology, Columbia, MO, USA
- Indian Institute of Technology, Indian School of Mines, Department of Computer Science and Engineering, Dhanbad, India (former)
- West Bengal University of Technology, Kolkata, India (former)
According to our database1,
Rashmi Priya
authored at least 11 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Integration and Calibration of Multi-Array Sensors for Biomass Estimation in Pasture Land for Sustainable Grazing.
Proceedings of the International Conference on Computer, 2024
2023
NSGA-III Based Heterogeneous Transmission Range Selection for Node Deployment in IEEE 802.15.4 Infrastructure for Sugarcane and Rice Crop Monitoring in a Humid Sub-Tropical Region.
IEEE Trans. Wirel. Commun., June, 2023
IoFT-FIS: Internet of farm things based prediction for crop pest infestation using optimized fuzzy inference system.
Internet Things, April, 2023
2022
Effect of Paddy Rice vegetation on received signal strength between CC2538 SoC based sensor nodes operating at 2.4 GHz Radio Frequency (RF).
Dataset, May, 2022
NSGA-2 Optimized Fuzzy Inference System for Crop Plantation Correctness Index Identification.
IEEE Trans. Sustain. Comput., 2022
Machine Learning Regression for RF Path Loss Estimation Over Grass Vegetation in IoWSN Monitoring Infrastructure.
IEEE Trans. Ind. Informatics, 2022
IoT-Enabled IEEE 802.15.4 WSN Monitoring Infrastructure-Driven Fuzzy-Logic-Based Crop Pest Prediction.
IEEE Internet Things J., 2022
2020
Sustain. Comput. Informatics Syst., 2020
HHDSSC: harnessing healthcare data security in cloud using ciphertext policy attribute-based encryption.
Int. J. Inf. Comput. Secur., 2020
2018
Crop Prediction on the Region Belts of India: A Naïve Bayes MapReduce Precision Agricultural Model.
Proceedings of the 2018 International Conference on Advances in Computing, 2018
Adaboost.RT Based Soil N-P-K Prediction Model for Soil and Crop Specific Data: A Predictive Modelling Approach.
Proceedings of the Big Data Analytics - 6th International Conference, 2018