News

07/29/2022

Ph.D. student Aanis Ahmad passed the preliminary examination. The thesis title was: Deep Learning-Based Computer Vision for Disease Identification and Monitoring in Corn

07/28/2022 - 07/29/2022

2022 SURF Student Presentations:

July 28- Kenta Oral Presentation (10:15 – 10:30):

SURF ID: 156
Title: 
ROS2/Gazebo Simulation for Autonomous Navigation of Robots in Agriculture

Student: Kenta Hirashima, PI: Dr. Dharmendra Saraswat  and TA: Varun Aggarwal and Aanis Ahmad

 

July 29- Saron Oral Presentation (10:00 – 10:15):

SURF ID: 115
Title:
Software-In-The-Loop Simulation of UAS-UGV Cooperation in Precision Agriculture
Student: Saron Bhoopathy, PI: Dr. Dharmendra Saraswat  and TA: Varun Aggarwal and Aanis Ahmad

July 29- Samia Oral Presentation (10:00 – 10:15):

SURF ID: 282
Title: 
Aiding Farm Operations With Artificial Intelligence Chatbot
Student: Samia Sohail Azim, PI: Dr. Dharmendra Saraswat and TA: Varun Aggarwal

 

07/18/2022 - 07/20/2022

2022 ASABE AIM:

Location: Houston, Texas

Research Presentations:

July 18- Varun Oral Presentation (9:35 – 9:40):

Aggarwal, V., Saraswat, D., & El Gamal, A., (2022). Realtime and Offline Soybean Stand Count from an Unmanned Aerial System in Early Growth Season, ASABE Paper No. 2201187. 

July 18- Varun Oral presentation (10:10 – 10:15):

Chawla, Y., Aggarwal, V., & Saraswat, D., (2022). A Fine-Tuning Based Approach for Generalizing YOLOv4 Network for Soybean Detection in UAS Images, ASABE Paper No. 2100571. 

July 18- Varun Oral presentation (11:30 – 11:45):

Tiwari, S, R., Aggarwal, V., & Saraswat, D., (2022). Determining the effect of resolution on the accuracy of object detection networks in UAS acquired images, ASABE Paper No. 2201188. 

July 18- Aanis Oral presentation (14:35 – 14:45):

Ahmad, A., Aggarwal, V., Saraswat, D., El Gamal, A., & Johal, G. S., (2022). Deep Learning-Based Disease Identification Tool for Tar Spot in Corn, ASABE Paper No. 2201193

06/26/2022 - 06/29/2022

2022 ICPA Conference Research Presentation:

June 28- Aanis Virtual Oral Presentation (15:30 – 15:45):

Ahmad, A., Aggarwal, V., Saraswat, D., El Gamal, A., & Johal, G. S., (2022). Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery, Abstract ID. 8812. 

06/16/2022

 

Latest review article on Deep Learning for plant disease diagnosis, research gaps, and recommended solutions from DAD lab is available at: https://www.sciencedirect.com/science/article/pii/S277237552200048X 

05/23/2022 - 2022 SURF Program

Kenta Hirashima

Saron Bhoopathy

Samia Sohail Azim

03/18/2022

Dr. Saraswat has been awarded the 2022 Outstanding Faculty Mentor Award. He will be honored at the 2022 College of Engineering Graduate Student Awards Luncheon on Wednesday, April 13.

03/09/2022

 

Dr. Saraswat delivered an invited talk on “Usefulness of publicly available datasets for pest management using artificial intelligence (AI) technologies” on March 9, 2022 at the United States Department of Agriculture- National Institute of Food and Agriculture sponsored conference  titled “Envisioning 2050 in the Southeast: AI-Driven Innovations in Agriculture”. The conference was a joint effort by all the land grant universities in the USA southeast.

03/05/2022

 

Dr. Saraswat gave a keynote address on the topic “ICT for Plant Disease Management and Development of Early Warning Systems” at the Third International Conference on “Rural Technology Development and Delivery (RTDD-2022)”. The conference was organized by the Center for Emerging Technologies for Sustainable Development, Indian Institute of Technology, Jodhpur, Rajasthan, India.

03/04/2022

 

Dr. Saraswat gave an invited talk on the topic “Harnessing Deep Learning Networks on IoT Devices for Weed Identification” in a session on “Internet of Things, Connectivity, and Big Data in Agriculture” at the International Workshop on “Applied Computing in Agriculture”. The workshop was jointly organized by De La Salle University (DLSU)– Manila and National Taiwan University (NTU)- Taipei City with funding from DLSU and the Department of Science and Technology, Philippines.

02/15/2022

Aanis Ahmad, Ph.D. student, has received first position at the 2022 American Society of Agricultural and Biological Engineers (ASABE) Agriculture Equipment Technology Conference (AETC) Student Poster Presentation Competition Award. Congratulations!!!

The presentation was titled “Promise of Computer Vision-Based Corn Disease Management Systems Using Deep Learning for Disease Identification and Severity Estimation”.
The award consists of a cash prize of US$250.00 and a certificate. The award winners are selected from among all undergraduate and graduate students who submit an abstract, register to attend, and present at the ASABE AETC.
The funding for the research was provided by the Foundation of Food and Agricultural Research grant number 534662 and USDA National Institute of Food and Agriculture Hatch project 1012501. Thanks are also due to Dr. (s) Bryan Dilkes and Raj Khangura for their help with field data collection.

11/23/2021

 

Dr. Saraswat receiving a citation from the Deputy Chief Minister, State of Bihar and the Agriculture Minister, State of Bihar.

11/23/2021

 

Dr. Saraswat delivered a keynote talk on “Evaluation of Deep Learning Networks for Corn Diseases” in the International Symposium organized as part of 55th Annual Convention of Indian Society of Agricultural Engineers ( ISAE), November 23, Patna, India.
 

11/5/2021 - Diwali Celebration

10/25/2021

 

Accurate identification of corn diseases and their severity estimation is important consideration for developing disease management strategies. Our latest contribution is an effort to promote evaluation of deep learning models for corn disease management http://arxiv.org/abs/2110.12084

10/14/2021

Aanis Ahmad, Ph.D. student, has received the 2021 American Society of Agricultural and Biological Engineers (ASABE) Annual International Meeting (AIM) Student Oral/Poster Presentation Competition Award for the Information Technology, Sensors, and Control Systems (ITSC) Community. Congratulations!!!

The presentation was titled “Comparison of Deep Learning Models for Corn Disease Identification, Tracking, and Severity Estimation Using Images Acquired from UAV-mounted and Handheld Sensor”.

The award consists of a cash prize of US$250.00 and a certificate. Only 30 awards across all ASABE technical communities are presented. The award winners are selected from among all undergraduate and graduate students who submit an abstract, register to attend, and present at the ASABE AIM.

The funding for the research was provided by the Foundation of Food and Agricultural Research grant number 534662 and USDA National Institute of Food and Agriculture Hatch project 1012501. Thanks are also due to Dr. (s) Bryan Dilkes and Raj Khangura for their help with field data collection.

10/06/2021

 

Shah Lab announces 2021 Grant Recipients– Seed Drill Technology award comes to a team consisting of Dr. Saraswat (PI) and two partners namely Dr. Rajendra Prasad Central Agricultural University (RPCAU, Dr. Sanjay Patel) and Catholic Research Service (CRS), India (Ms. Viji Arora).
 

Grant

10/02/2021

 

Mentoring first time undergraduate research fellows is time well spent. A video about the research accomplishments of Ava Riaziat is provided for evidence. She deserves applause for her courage and initiative.
 

09/30/2021

 

Real-time identification of weeds at different flight speed of unmanned aerial vehicle (UAV) is fun but at the same time a bit dizzying.
 

09/03/2021

 

Thanks to funding support provided by India’s Science and Engineering Research Board ( SERB) Overseas Visiting Doctoral Fellowship Program ( OVDF) that I will have the opportunity of hosting Ms. Sangeetharani Munusamy, a PhD student from Indian Institute of Technology, Bombay ( IITB) in Digital Agriculture Discovery ( DAD) lab at Purdue. She will spend a year in Purdue starting from January 2022 onwards. Congratulations are due to Prof. Eswar Rajasekaran for mentoring a promising scientist in his lab at IITB. Looking forward to outstanding contributions by Ms. Sangeetharani.
 

07/30/2021

2021 SURF Student Presentations:

2:15 PM – 2:30 PM Anushka Gupta Presentation:

SURF ID: 151
Title: Workflow Design and Visualization of Water Quality Data
Student: Anushka Gupta, PI: Dr. Dharmendra Saraswat  and TA: Ben Hancock

 

3:15 PM – 3:30 PM Hieu Phan Presentation:

SURF ID: 211
Title: SLIC Segmentation and Deep Learning for Corn Disease Monitoring Using PlantVillage Dataset
Student: Hieu Phan, PI: Dr. Dharmendra Saraswat  and TA: Aanis Ahmad

 

07/27/2021

REEU is a 10-weeks research program designed to impart data science skills that compliments agricultural discipline knowledge of the participants. The 2021 REEU program had 18 participants from 13 different institutions. The participants showcased their skills by completing a project of their choice and presented it in “Agriculture Summer Research Poster Session” on July 27. The following participants completed their projects under the mentorship of Prof. Saraswat and other team members in DAD group:

 

Participant

Abraham Alvarez Garcia                              
Austin Berenda                                             
Landon Feese                              
Taylor Mitchel                                    
Lizbeth Plaza-Torres                                         

Project Title

IoT Sensing Integration for Indoor Agriculture
Expenses Correlated with Yield & Cost-Benefit of Hydroponics 
Wine Grape Variety Database
Locating Waste Sites in North Carolina
Counting Corn Plants Using Deep Learning

Mentor(s)

Prof. Saraswat and Madhu Lekha Guntaka
Prof. Saraswat                                                   
Prof. Saraswat and Ben Hancock
Prof. Saraswat and Ben Hancock
Prof. Saraswat, Ben Hancock, and Varun Aggarwal
idea, empty, paper-1876659.jpg
A smiling Lizbeth M Plaza-Torres posing in front of her poster

07/16/2021

Congratulations! Graduate student Madhu Lekha Guntaka successfully defended her Master’s thesis on July 16th, 2021

Title: IoT Based Low-Cost Precision Indoor Farming
Abstract

There is a growing demand for farm management systems that can track plant growth, allow automatic control and aid in real-time decision making to make indoor farms more viable. IoT is being applied to meet these needs and numerous researchers have created prototypes for specific purposes with sensors, algorithms, and automations. There is, however, a critical need for comprehensive large-scale experiments to test the aspects of such systems’ availability, scalability, reliability, especially the low-cost ones. The purpose of this study is to develop a low-cost IoT ecosystem using off-the-shelf components in an indoor farm setting to move from a prototype to a real-world testbed for experiments and address some of the challenges identified. Additionally, to utilize the data captured for intelligent farm management. This testbed realized collection and monitoring of nutrient quality, light intensity, environmental variables, images, and corresponding actuation of LED, irrigation, camera modules using commercially available sensors, components and Raspberry Pis, Arduino microcontrollers for computing. It featured a cloud-based dashboard for remote monitoring and control. Novel techniques of edge-computing, anomaly detection, machine vision were applied. The developed testbed is used to successfully investigate the effects of nutrition, lighting, and density on growth of microgreens guided by a statistical design and can motivate, serve as a reference to interested growers. A framework for anomaly detection and yield prediction in the farm is proposed. This study complements and expands the previous works on building low cost IoT farm systems. While the experience with the testbed indicates its importance in conducting research in a practical setting, it also points to some major lessons from the field which are described in detail.

07/12/2021 - 07/15/2021

2021 ASABE AIM Presentation:

Invited Presentation- Dr. Saraswat gave a talk titled “Teaching Geospatial Programming and Data Science to AgriScience Students: Analyzing Weather Network Data (WND) in Jupyter Notebook” in an invited session on “Instructional Case Studies with Data Sets for YOUR Instruction” on July 14, 2021. Dr. Gang Shao from Purdue Libraries was the collaborator on the presentation.

Research Presentations:

July 12- Aanis Poster Presentation:

Ahmad, A., Saraswat, D., El Gamal, A., & Johal, G. S., (2021). Comparison of Deep Learning Models for Corn Disease Identification, Tracking, and Severity Estimation using Images Acquired from UAV-Mounted and Handheld Sensor, ASABE Paper No. 2100566. 

July 13- Varun Oral presentation:

Aggarwal, V., Saraswat, D., & Young, B. (2021). Evaluation of Semantic Segmentation for Assessing Accuracy of Weed Identification at Different Growth Stages Based on UAS Imagery, ASABE Paper No. 2100571. 

July 14- Madhu Oral presentation:

Guntaka, M. L., Saraswat, D., & Langenhoven, P., (2021). Design and Evaluation of an IoT-Testbed for Precision Indoor Farming, ASABE Paper No. 2100617. 

Latest Update

ITSC Paper Award Presented to Mr. Aanis Ahmad on July 15, 2021

06/14/2021

Aanis Ahmad, Ph.D. student, has been selected for 2021 American Society of Agricultural and Biological Engineers (ASABE) Information, Technical, Sensors, and Controls (ITSC) Technical Community Meeting Paper Award. Only the top 10% of ITSC meeting papers are honored – Congratulations!!!

The paper is titled “COMPARISON OF DEEP LEARNING MODELS FOR CORN DISEASE IDENTIFICATION, TRACKING, AND SEVERITY ESTIMATION USING IMAGES ACQUIRED FROM UAV-MOUNTED AND HANDHELD SENSORS”, by Aanis Ahmad, Dharmendra Saraswat, Aly El Gamal, Gurmukh S. Johal.

The award will be presented on July 15, 2021 during the virtual awards ceremony of 2021 ASABE Annual International Meeting.

The funding for the research was provided by the Foundation of Food and Agricultural Research grant number 534662 and USDA National Institute of Food and Agriculture Hatch project 1012501. Thanks are also due to Dr. (s) Bryan Dilkes and Raj Khangura for their help with field data collection.

05/19/2021

Dr. Saraswat invited as a panelist in AgTech session on May 19, 2021 as part of 7th Annual India-Purdue Collaborative Lecture Series in Honor of Bharat Ratna Professor C.N.R. Rao

https://connect.purdue.edu/s/listing/a0L3k00000pU4Kk/indiapurdue-collaborative-lecture-series

05/07/2021

Dr. Saraswat wins 2021 Purdue Shah Lab Seed Design award:

Dr. Saraswat and his team was awarded 2021 Purdue’s Shah Lab Seed Design award. The award will be used for developing and evaluating an affordable, scalable, seed drill for resource poor farmers in India. Other project collaborators include Ms. Vijayalakshmi Arora, Head of Programme- India, Catholic Research Service and Dr. SK Patel, Associate Professor, Rajendra Prasad Central Agricultural University ( RPCAU), Pusa, Bihar.
barley, field, sunset

05/01/2021

Dr. Saraswat to serve as one of the faculty experts for US$ 1 Million The Nudge Prize and the 2021 Cisco Agri Challenge 

https://www.purdue.edu/india/

Latest Publication

Broadleaf weeds versus grassy weeds- how accurate are deep learning methods in classifying and identifying them under field conditions in corn and soybean production systems? Read the article to find your answer:

 https://www.sciencedirect.com/science/article/pii/S0168169921000995?dgcid=author

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