Yes Bank Transformation Series

1. TEAM NEWTON Sudhendra|Gaurav|Saurav

2. TEAM NEWTON Sudhendra | Gaurav| Saurav
Contents
Workflow Model 3
Overview of Crop Damage & Farmer’s income 3
Main causes of low income in Indian Agriculture 3
Factors to be considered 4
Data Collection Technique 5
Predictive Analysis Model 6
KPIs 6
How to involve Farmers with our model 7
How to educate farmers to use our model 7
Scalability Plan for Next 10 years 8
Operations Sequence 8
Possible Problems & Backup plans 9
Collaborators 9
Introduction of Kirhsi Garntha 10
Backend systems of Krishi Grantha 10
Total Cost prediction 11
Social impact of our model 11
References 12
Appendix:
Cost Structure 13
BOT questioning structure to farmers 14

3. Live and personalized data
Processed information
Historical Data Farmers Historical Data
Intermediaries
Government
Institutes &
Departments
Factors Historical Data
Workflow Model
737 768 835
939 970 1025 1083 1145
Crop Damage Growth
0
5000
10000
15000
20000
Farmer Income vs India's Average
Income
Farmer Income India's Average Income
Overview of Crop Damage & Farmer’s income
TEAM NEWTON Sudhendra | Gaurav| Saurav
The education level of Indian farmers is comparatively low than farmers of other countries
Low volume of governmental investment for agriculture sector compared to the industrial sector
The average size of farm holdings in India is very low, less than 2 hectares or 5 acres
The inadequacy of such non-farm services as provision of irrigation, seed, finance, marketing,
etc.
Indian farmers have been using old and inefficient methods and techniques of production
generation after generation
Inadequate Irrigation Facilities
Main causes of low income in Indian Agriculture

4. Factors to be considered
Soil Quality
• PH
• Moisture
• Minerals
• Soil Fertility
Water Quality
• Water Hardness
• Water Pollution
Level
• Air Velocity
• Air Temperature
Air Quality
• Air Pollution
• Air Moisture
• Air Velocity
• Air Temperature
Pest attack
• Historical pest attack data
• Preferable pesticides related data for pest
control in every region
Oil price
• Oil price fluctuation
in India & Imports
country
• Data of
consumption
various crops in
accordance to oil
price
Market Information
• Demand in
market
• Accurate price in
various markets
• Last year reserves
• Consumer taste
change in market
Imports & Exports
• Data related to export countries demand &
supply
• Export Duties of various crops
• Government policies’ change in exports
Personalize farmers
data
• Farmer’s experience
• What kind of crops
farmer sow
• If any electrical
machine is used by
farmer
• Crops which is
familiar to farmer
Farm specific Data
• Quality of seeds
• Quality of pesticides
the farmer uses
• What are the others
crops are sown
• Timing of the
sowing
All the factors are sync. Connected with each
others
Factors would be considered historical as well
as present way
TEAM NEWTON Sudhendra | Gaurav| Saurav

5. Market Data like demand
data, price data of crops in
various regions for the last
10 years for getting the
trends
Use drones with air sensor to
get the air quality,
population level, air velocity,
air moisture etc.
Low cost Helium Balloon +
optical sensor for + VRT
Method to collect soil
related data with optical
analyzing
Data related with weather
change for the last 25 years
to predict the upcoming
change
Data of exports of crops to
different countries and price
of those crops for the last 10
years
Crop production data for last
10 years to get the
production pattern of the
crops
Data Collection Technique
Both historical & live data will require for accurate predictive analysis
Live Data Historical Data
• Farmers Personalized data
• Market demand & price
• Oil price movement data
• Any change in export duty, policy
or foreign demand
• Weather change data
• Soil quality change
• Air quality and pollution level change
• Pest attack in various regions in different times
• Water quality & pollution level data
*All data will be stored in Microsoft cloud in a specified format of database to maintain data integrity
All historical data will be updated after every 6 months and live data updated regularly
Pest attack in various regions
in different timings of year
for last 10 years
Water quality level in
different regions and
pollution level for last 10
years
AI bot will collect
personalized data
from farmers with
feature of Cortana
based language
Cloud Sync.
TEAM NEWTON Sudhendra | Gaurav| Saurav

6. Predictive Analysis Model
Sensor Interface
MQTT Broker
FTP Server
Deep
learning
Predictive
Analysis with
Neural
Network
Mapping
of
Future
Data
soil quality
air quality
pest attacks
Crop yield
water quality
Market price &
demand
imports of crops
Database with
historical data &
farming information
Define best possible solution for
farmers to increase income
Cloud Sync.
KPIs
14% 25%
28%33%
KPI A
KPI C KPI D
KPI B
Rough estimation of weights of KPIs
TEAM NEWTON Sudhendra | Gaurav| Saurav
Predictive Index
Compare
predictive
data with
historical
data
Inform farmers through
mobile message
Difference between actual and
predictive crop production
KPI B
KPI C KPI D
How average income and
production increases
KPI A
Decreased in crop damage in
our operating areas
Farmers involvement

7. Farmer
involvement
Cycle
Collectio
n farmer
historica
l data
Farmers
provide
crop
informat
ion
Farmers
use the
system
Feedbac
k
System
Upgrade
Collaborate with Rural Innovators
Recognizing and collaborating with rural
innovators who are working with farmers will
help in increasing the awareness of the
program
Involve Local NGO’s and Influencers
Involving local NGOs will help in increasing the
reach of the program and will also lead to
greater acceptance as these influencers
command greater trust
Gram Panchayats and Government Agencies
As panchayats are the governing body in the
villages, collaborating with them will lead to
greater farmer involvement
Partner with Krishidarshan
Create informative and promotional program
on Krishidarshan(TV channel funded by
government)
1
2
3
4
How to involve Farmers with our model
How to educate farmers to use our model
5
1
4
3
2
Providing content videos of farmers
who got success with our model
Demo of our model through videos in
local languagesFree training of how to use our model
Use radio & TV channels to increase
more to the farmers
Always help the farmers in their
queries
TEAM NEWTON Sudhendra | Gaurav| Saurav

8. Scalability Plan for Next 10 years
Operations Sequence
2019 2020 2021 20232022 2024 20262025 2027 2028
Phase 1 Phase 2 Phase 3
Farmers
Involve
ment
Increase
operatio
nal
regions
Accuracy
Rate
Future
Plan
A
B
C
D
Focus on try to involve more farmers to
use our model to increase their income
• Start with the region where farmer is most educated
• After 1-1.5 years will expand to the most damage prone area for crops
• Next 2-4 years will expand to the areas where farmers will be willing to
involve mostly with our model
2029
• Introduce Krishi Grantha, a tablet like device for
farmers in the most involved region of farmers
• Start with 1000 devices
• Initial target accuracy rate is 95%-97% for predicting all factors
• From 2022 we will try to improve this rate to 99.5% by gathering
more data with accurate database maintaining
TEAM NEWTON Sudhendra | Gaurav| Saurav
Involving farmers
will improve
accuracy rate
Operation should
increase when we will
get enough success in
current regions
With time our operation accuracy
rate should increase, if not then
are errors in our model
Krishi Grantha will be
introduced based on farmers
involvement & accuracy rate

9. Possible Problems & Backup plans
Problems Possible Solutions Implementation
Regular
Review
Long term & Short term thinking
Long term
Short term
* Krishi Grantha will be introduced based on the farmers involvement to our model
Collaborators
Associate with Government
organization
• BSNL (Network Related problem)
• Census of India (Historical data)
Associate with private organization
• Nebulaa (Automatc grain
analyzer)
• PlantMD (3D image processing)
• Yesbank
TEAM NEWTON Sudhendra | Gaurav| Saurav

10. Connected through TCP server
with Microsoft Cloud to get the
historical data and predictive
analysis of data
Introduction of Kirhsi Garntha
High Resolution camera with
image processing technology
to to get the RGB value of
corps
Connection with Automatic Grain
Analyser of Nebulaa to compare
expected quality with actual one
Will suggest farmers how to improve
crop quality by accurate fertilize &
pesticides. Also suggest actual price of
the crops in market
According to our plan in 2025-2027 we are going to introduce Krishi Grantha, a tablet like AI driven device for
farmers such that they can measure their crop production & income level individually
Backend systems of Krishi Grantha
Nebulaa Printer Microsoft Cloud Sync. 3D image processing sensor
Just need to put your seed
and it will analyze your
seed quality
Cloud sync. to get all the
historical and live data of market
and crop production
High resolution camera with 3D
image processing sensors to get
RGB value of crop to analyze crop
health
Demo for Nebulaa printer:
https://www.youtube.com/watch?time_continue=69&v=UU4PXeahFhc
Demo For 3D image processing technique:
https://www.youtube.com/watch?v=UrxIIbkpkbo
Cloud Sync.
TEAM NEWTON Sudhendra | Gaurav| Saurav

11. Total Cost prediction
Cost Drivers
Social impact of our model
• Drones
• Sensors
• Helium Balloon
• Server
• Tablet
• Server
• Bot
• Data
• Sensors
• VRT Technology
• AI Development
• Developer
• Server Maintainer
• AI Maintainer& DeveloperHuman Resource Cost
Develop
ment
cost
Maintenance
Cost
Equipment Cost
Total
Cost
Estimated cost for 10 years : Rs.509,52,14,000
Lifestyle of farmers
will improve
Farmers income will
increase
Crop Damage will
decrease &
production rate will
increase
Loan taken by farmers
will decrease
Net
producti
on &
exports
will
increase
for
country
Suicide rate of
farmers will decrease
TEAM NEWTON Sudhendra | Gaurav| Saurav

12. TEAM NEWTON Sudhendra | Gaurav| Saurav
Total Word count: 1978

13. From which region
you are from?
1.
North
2.
West
3.
South
4.
East
For How Many
years you
associated with
sowing?
1.
<5 years
2.
5-15 years
3.
15-25 years
4.
>25 years
What kind of crops
you use to sow?
1.
Option 1
2.
Option2
3.
Option 3
4.
Option 4
Do you have
machinery for
cropping
1.
Yes
2.
NO
Is water supply is
prominent in your
field?
1.
Yes
1.
No
In which month
you sow your
seeds?
1.
Jan
2.
Feb
3.
Mar
ch
4.
Apri
l
5.
Ma
y
6.
Jun
e
7.
July
8.
Aug
ust
9.
Sep
tem
ber
*
Oct
obe
r
0.
Nov
em
ber
#.
Dec
em
ber
When do you cut
your crops?
1.
Jan
2.
Feb
3.
Mar
ch
4.
Apri
l
5.
Ma
y
6.
Jun
e
7.
July
8.
Aug
ust
9.
Sep
tem
ber
*
Oct
obe
r
0.
Nov
em
ber
#.
Dec
em
ber
Do you have any
machinery for
sowing?
1
Yes
2.
No
If Yes, then what
kind of machinery
do you have?
1.
Option 1
2.
Option 2
3.
Option 3
4.
Option 4
What kind of
pesticides do you
use?
1.
Option 1
2.
Option 2
3.
Option 3
4.
Option 4
What kind of
fertilizer do you
use>
1.
Option 1
2.
Option 2
3.
Option 3
4.
Option 4
Appendix 1. BOT questioning structure to farmers
(All the numbers & symbols will be represented by mobile keyword.
All questions will be asked in farmers local language)
TEAM NEWTON Sudhendra | Gaurav| Saurav

14. 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029
Drone 600000 882000 864000
141000
0
138000
0
135000
0
132000
0
206400
0
201600
0
196800
0
192000
0
Hellium Ballon 480000 480000 480000 800000 800000 800000 800000
128000
0
128000
0
128000
0
128000
0
Optical Sensor 720000 720000 720000
120000
0
120000
0
120000
0
120000
0
192000
0
192000
0
192000
0
192000
0
High Resolution
camera 8110000 10000 10000
135000
00 10000 10000 10000
216000
00 10000 10000 10000
VRT setup +
maintainance cost
2400000
00
240000
000
240000
000
240000
000
400000
000
400000
000
400000
000
640000
000
640000
000
640000
000
640000
000
Server 4150000 150000 150000 150000 150000 150000 150000 150000 150000 150000 150000
Tablet 0 0 0 0 0 0 0
200000
0
300000
0
100000
00
100000
00
AI
Making+Delopem
ent Cost
5000000
0
300000
00
300000
00
300000
00
300000
00
200000
00
200000
00
200000
00
100000
00
100000
00
100000
00
AI maintaining 100000 100000 100000 100000 100000 100000 100000 100000 100000 100000 100000
Total
3041600
00
272342
000
272324
000
287160
000
433640
000
423610
000
423580
000
689114
000
658476
000
665428
000
665380
000
Total Cost for 10
years
5095214
000
Appendix 2 : Cost Structure
(All figures is in Rupees)
TEAM NEWTON Sudhendra | Gaurav| Saurav