Augmentation of satellite imagery for farming data

1. Augmentation on Satellite
Imagery with Information
Integrated Farming
“IF YOU ATE TODAY , THANK A FARMER !”

2. PBL
Agenda
● Why this field?
● Overview
● Challenges
● Problem Statement
● Objectives
● Existing Work
● Proposed solution
● Design
● Implementation

3. Why this field ?
● Agriculture is the backbone of India.
Being the single largest contributor to GDP of the nation
● 52% of the total population involved with it.

4. Overview
1 To build Low Cost
Integrated Informatics
System
2
Improving efficiency and
productivity of stakeholder
3 Decision Support System
for different stakeholders
4 How it contributes ?

5. Challenges
1 Choice of Visualization
Interface for mixed data
2 Managing multiple plot
and physical status of it
3 Lack of awareness of
relationship and stakeholders
interests
4 Scalability

6. The Gap that's not a addressed
Methods currently available are cumbersome and perishable in
nature. Visualization and processing of data is inefficient and
induced error rate is high, leading to weak support for making
decisions.

7. Problem Statement
Design and development of Decision Support System for
different stakeholders by augmenting physical statistica and
land statistics with Information Integrated Farming

8. Stakeholders:

9. Objectives
● To represent data based on
different stakeholders interest
● Augmentation of Farming stats
on Land stats wrt to GPS
● Develop Integrated system
connecting stakeholders to
market place
● To build DSS to achieve accuracy

10. Existing System
● Crop IO- real time
● AgriVi- track financial expenditure

11. Previous Work
1) Research and Design of an Integrated Farm Information Management System Based on
Component GIShttps:// ieeexplore.ieee.org/document/5190024.
1) Aqeel-ur-Rehman and Zubair Ahmed Shaikh. ONTAgri : Scalable Service Oriented Agriculture
Ontology for Precision Farming. (2011).
1) Muchina, Solomon et al. Agricultural Systems in IGAD Region A Socio-Economic Review. (2018).
1) Pruthvi Vs, Rohit Naik and Vijaya kumar Bp, “Prediction Based Policy Setting by Finding
Significance Of Attributes From The Ontological Framework In Agricultural Domain”, IEEE SSCI,
December 2018, Bangalore.

12. Proposed
Solution

13. Design

14. Data Collection

15. Views Of Stakeholders

16. Visualization

17. Implementation

18. Map Interface
Better representation of
complex relationship
between data and its geo
importance
Query Interface/ User
Interface to visualize,
interests of different
stakeholders.
The results are pictured in
map interface
Scalability
There is a requirement to
handle huge data and
users, hence NO-SQL
fashion storage and query.

19. USE -
CASE
DIAGRAM

20. Current Work
We with help of our Institution
M S Ramaiah Institute Of
Technology
Have collected data from 8 villages
in “Kaiwara” town
&
We are in phase of Implementation

21. Future Work
Image Processing and
Machine Learning
Integrate with E-
mandi and other
beneficiaries
App Based data
collection , harnessing
power of mobile
sensors like GPS etc..

22. Thank you.