Rashmi Priya Sharma

Rashmi Priya Sharma

Postdoctoral Fellow
Universty Of Missouri Columbia, MO, USA

Brief Bio

Hi! I’m Rashmi Priya Sharma a Postdoctoral Fellow at University of Missouri, Columbia. I received my Ph.D from the Indian Institute of Technology, Dhanbad in the Department of Computer Science and Engineering. Growing up in a family of farmers, I have always been fascinated by the ways technology can address the various challenges that farmers face. I have expertise in Machine Learning, Artificial Intelligence and Big Data Processings. For a decade I have been investigating the applications of ICT technologies like artificial intelligence, machine learning, IoT and the digital twin in mitigating the impact of climate change on agriculture, water resources and human health.

Research Interests

I broadly work in Wireless Sensor Network, Big data analytics and its application in the field of precision agriculture, that is, I build the sensors to collect the data, analyze the data and build models to ensure that crops and soil receive exactly what they need for optimum health and productivity. The problems that are addressed in my research work so far are:-

  • Crop recommendation system, using the Naive Bayes algorithm, to find the best time of sowing and ideal crop for plantation based on environmental parameters and predict the expected harvest.
  • Adaboost.RT-based N-P-K prediction to decide required soil NPK content using one-time soil testing like accessible soil contents, type of soil, crop, and yield target.
  • Discussing the core concept of Machine learning and systematic processes to comprehend its application in agriculture.
  • An efficient DBSCAN based model to find and treat the cotton plant affected by Xanthomonas mavacearum and identify the soil areas affected by an overuse of the pesticides.
  • Modular artificial neural network-based crop yield prediction by considering weather attributes and land and suggesting measures to increase the crop yield. .

Current Project

  1. Title: Development of a cyber-physical system that aims to optimize the use of grazing lands by providing accurate biomass estimates.
    Role: Postdoctoral Fellow.

Completed Projects

  1. Title: Precision Agriculture Model to Increase Crop Productivity in India using Big Data. Role: Senior Research Fellow (Team Leader). Collaborator: Department of Science and Technology, Government of India.
  2. Title: IoT based Decision Support System for Efficient Irrigation in Agriculture. Role: Senior Software Engineer (Team Leader). Collaborator: Agro Glean System, Gwalior , India.
  3. Title: Machine learning based agriculture advent for farmer activity development in India. Role: Senior Data Scientist. Collaborator:Agro Glean System, Gwalior , India.

Recent publications

  1. Rashmi Priya Sharma, Dharavath Ramesh, and Damodar R. Edla. “IoFT-FIS: Internet of farm things based prediction for crop pest infestation using optimized fuzzy inference system.” Internet of Things 21 (2023): 100658.
  2. Pankaj Pal, Rashmi Priya Sharma, Sachin Tripathi, Chiranjeev Kumar, and Dharavath Ramesh “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 Transactions on Wireless Communications (2022).
  3. Pankaj Pal, Rashmi Priya Sharma, Tripathi Sachine, Kumar Chiranjeev, Ramesh Dharavath. “Machine Learning Regression for RF Path Loss Estimation Over Grass Vegetation in IoWSN Monitoring Infrastructure.” IEEE Transactions on Industrial Informatics 18.10 (2022): 6981-6990.

Data repository

  1. “Effect of Paddy Rice vegetation on received signal strength between CC2538 SoC based sensor nodes operating at 2.4 GHz Radio Frequency (RF)”, IEEE Dataport
  2. “Effect of Paddy vegetation on path-loss between CC2650 SoC based sensor nodes operating at 2.4 GHz Radio Frequency (RF)”, IEEE Dataport
  3. “Effect of millet vegetation on received signal strength between CC2538 SoC based sensor nodes operating at 2.4 GHz Radio Frequency (RF)”, IEEE Dataport
  4. “Effect of Sugarcane Vegetation On Path-Loss Between CC2650 and CC2538 Soc Based Sensor Nodes Operating At 2.4 Ghz Radio Frequency (Rf)”, IEEE Dataport

News

All-in-one IoWSN weather station deployed in the farm land of gwalior madhya pradesh, India.

The weather station equipped with Ultrasonic Anemometer, Raingauge, Solar Radiation Sensor, Solar panel, and the Gas sensor is an Edge Gateway for the soil moisture sensor network. The Gateway houses the Nvidia Jetson Xavier-nx and has LTE connectivity for Microsoft azure cloud connectivity.

Contact Address:

Plant Science and Technology
University of Missouri
1112 University Ave, Columbia, MO 65201
Email: rashmi.priya.303@gmail.com