Agriculture in India constitutes more than 60% of the occupation. It serves to be the backbone of Indian economy. It is very important to improve the efficiency and productivity of agriculture by simultaneously providing safe cultivation of the farmers. Operations like spraying of pesticides, sprinkling fertilizers are very tedious. Use of drones for spraying of pesticides and sprinkling fertilizers can avoid health risks of farmer. Drones are the best option for capturing high resolution images. For remote sensing, aerial images are a very precise and convenient source of data for agricultural management. Mostly, satellite images have been used as the primary source of information for analyzing crop status in precision agriculture.Drones can used for chemical spraying. UAV estimation of crop nutrient status can directly benefit the application rate recommendations by producer or agronomist consultant by including the entirety of the field.An analysis can be performed with UAVs that has no equivalent in satellite sensors: a three-dimensional representation of surface conditions, also known as digital elevation models (DEMs).. Drones are a solid option for monitoring herds from overhead, tracking the quantity and activity level of animals on one’s field.

1. 1
,

2. 2
Seminar on
Application of drones in agriculture
KERALAAGRICULTURAL UNIVERSITY
Department of Soil and Water Engineering
Kelappaji College of Agricultural Engineering and Technology, Tavanur.
Under guidance of:
Dr. Manoj Mathew
(Professor and Major Advisor)
Dr. Shaji James P
(Professor and Course Teacher)
Dr. George Mathew
(Professor and Course Teacher)
By,
Sreedhara B
2016-18-013

3. INTRODUCTION
 Agriculture in India constitutes more than 60% of the occupation
 It serves to be the backbone of Indian economy
 It is very important to improve the efficiency and productivity of
agriculture
 Operations like spraying of pesticides, sprinkling fertilizers and other are
very tedious
 Use of drones for spraying of pesticides and sprinkling fertilizers can avoid
health risks of farmer (Chavan et al, 2017).
3

4.  Drone is an unpiloted, autonomous unmanned aircraft
 Remotely controlled or autonomously flown
 Autonomously flown drones works based on pre-programmed flight
plans or more complex dynamic automation systems
 Drones are also known as unmanned aerial vehicles (UAV)
 Drones typically fly at low altitudes
(Huang et al., 2013)
4

5.  Drones are Mini model fixed-wing airplanes or rotary-winged helicopters
 Low cost
 Low speed
 Low ceiling altitude
 Light weight
 Low payload weight capability
(Huang et al., 2013)
5

6. DRONES TYPES
I) Fixed wing
High wing
Mid wing
Low wing
II) Multi- rotor( rotary type)
Helicopter
Tricopter
Quadcopter
Hexacopter
Octocopter
(Andrade, 2013)
6

7. Fixed wing drones
 Fixed-wing drones have long-
range flight capacity
 Large area can be covered
 Crash tolerant
 Can cover over 1000 acres at 1.0
inch resolution a day
(Andrade, 2013)
7

8. MULTIROTOR DRONES
 Faster to set up in the field
 can take off and land vertically
 No need to plan takeoffs and landings.
 Used for small scale and research
operations under 50 acres
 For inexperienced operators, these are
the easiest way to get up and running
quickly
(Andrade, 2013).
8

9. COMPONENTS OF DRONES
Propellers
Brushless motors
Landing gear
Boom
Main body
Electronic speed controller
Flight controller
GPS module
Battery
Camera
Sensors Fig. The structure of the fixed and rotary wing drones (Andrade,
2013) 9

10. QUADCOPTER WORKING PRINCIPLE
 Four rotor propellers with controller
 The flight controller is the main part
 Ardupilot controls all the operation
commanded by us
 The four rotors used to create
differential thrust
 It can be hover and move accordance
with the speed of those rotors.
(Meivel et al., 2016) 10

11.  GPS guidance system is used to
navigate the UAV
 Pre-loaded trajectory gives the real
time coordinates to ardupilot
controller
 Based on this GPS coordinates, the
microcontroller navigates the UAV
11
(Meivel et al., 2016)

12. USES OF DRONES
 Remote sense imaging
 Evapotranspiration and Soil Moisture
 Crop Nutrient Monitoring
 Yield and Biomass Analysis
 Planting
 Irrigation
 Health assessment
 Cattle herd monitoring
 Chemical spraying
12

13. REMOTE SENSE IMAGING
 Drones are the best option for capturing high resolution images
 Satellite remote sensing is severely limited by cloud cover, and may not be
available at desired times (Tokekar et al., 2013)
 Real time high resolution images can captured, especially where small
productive areas have to be monitored (Lelong et al., 2008)
 Quadcopter and other drones are the best choice of mapping the remote sensing
data(Meivel et al., 2016)
 This remote sensing data is used to map the growth of crops, moisture level and
more (Meivel et al., 2016)
13

14. Evapotranspiration and Soil Moisture
 Evapotranspiration (ET) and soil moisture
are necessary to estimate water irrigation
needs (Allen et al., 1998)
 Estimating ET using UAV technology
requires temperature camera sensor along
with local weather station information
(USGS., 2016; Irish., 2000)
 Figure shows an ET estimation map and
moisture (Allen et al., 1998) across a
vineyard field in California, area 300 acres
Aggie Air RGB (left) and estimation
of ET in inches/day or mm/day (right)
14

15. Crop Nutrient Monitoring
 A major economic input for any
agricultural season is the application of
fertilizers
 UAV estimation of crop nutrient status in
the soil is very accurate
 specialized camera sensors such as optical
and thermal cameras, are used for sensing
nutrient status in the soil,(Al-Arab et al.,
2013; Torres-Rua et al., 2002 )
Estimation of Nitrogen Content for Oats (mg/100mg DM)
6 inch/pixel using (Aggie Air., 2017)
15

16. Chemical spraying
 Drones can used for chemical spraying
 In 2010 Zhu et al. have developed remote
controlled UAV for spraying
 It is proved that higher precision and
efficiency can achieved using UAV for
spray applications
 Yamaha is selling (since 2001) a remote-
controlled helicopter-UAV that can be
used to seed, spray rice, or spread granules Integrated spraying system with PWM
controller, where: (A) pump box; (B)
PWM controller box (Zhu et al., 2010) 16

17. Advantages
 Using drones it is possible to very high resolution images
 It is low cast technology compared to satellite
 Real time data can be viewed
 Agriculture productivity can be increased
Disadvantages
 Performance of current UAVs is still limited in terms of payload, range and/or accuracy.
 Fixed-wing vehicles can carry more, but cannot be positioned exactly as they have to keep
flying
 Use of drones creates unemployment
17

18. CASE STUDY-I
Title: Quadcopter for pesticide spraying
Authors: Misbah Rehman.Z, Kavya.B, Divya Mehta, Priya Ranjan Kumar
and Prof. Sunil Kumar G.R
Year:2016
Journal: International Journal of Scientific & Engineering Research
18

19. OBJECTIVES
 To overcome the ill-effects of pesticides on human beings (manual
pesticide sprayers)
 To cover larger areas of fields while spraying pesticides in a short span of
time when compared to a manual sprayer.
19

20. MATERIAL AND METHODS
HARDWARE DESCRIPTION
ATmega168
 High Performance, Low Power AVR® 8-Bit Microcontroller.
BLDC(2200mAh,20C)
 Brushless DC electric motor is used with inverter
ESC
 ESC is used to control BLDC motor
Accelerometer Sensor
 The accelerometer measures acceleration
 It is used to maintain orientation of the device
20

21. Gyroscope Sensor
 It measure angular velocity
LiPo battery
 can be found in a single cell (3.7V) to in a pack of over 10 cells connected in
series (37V).
 A popular choice of battery for a Quadcopter is the 3SP1 batteries which
means three cells connected in series as one parallel,
 which should give us 11.1V 21

22. 22

23. PESTICIDE SPRAYING MECHANISM
 pesticide tank of capacity 180 ml,
 submersible dc motor pump with 9
V battery
 Switch used for ON and OFF
 pipes fitted to T-split and mini
nozzles
23

24.  When the switch is turned ON, the
motor pumps the pesticides through
the pipe.
 The pipes supply the pesticides to
the nozzles via the T-split so that it
sprays with a certain pressure and
uniformity, thereby avoiding
wastage.
24

25. RESULTS
 The spraying time of pesticides is dependent on the quantity of pesticide to
be sprayed
 For 1000 ml of pesticides, spraying time is around 5 minutes
 To increase spraying quantity the weight lifting capacity of the quadcopter
must be increased
 This is done by choosing higher specification of BLDC i.e. more than 1000
rpm/kV
25

26.  The flight time of the quadcopter is around 8 minutes
 To increase the flight time we need to choose higher specification for LiPO
battery.
 The height of spraying is around 6-7 feet.
 The area covered is 10 feet by 10 feet.
26

27. CONCLUSION
 In agriculture, application of pesticides and fertilizers is important at
specific times and at specific locations to control pests.
 Quadcopters are manoeuvrable, cheaper to operate, and require less capital
costs
 Quadcopter can be used to spray on hilly terrains.
 Reduces ill effects to humans while spraying manually.
 Increases the efficiency of spraying.
27

28.  This can also be used in places where labourers are hard to find.
 It can substitute 50 workers thus saving 50 workers from the harmful
effects.
 Reduces the time for spraying when compared to manual spraying
28

29. CASE STUDY-II
Title: Review of effective vegetation mapping using the UAV (unmanned
aerial vehicle) method
Authors: Korehisa K, Seiich N
Year: 2014
Journal: Journal of Geographic Information System
29

30. STUDY SITE AND METHODS
Study Site
The study site was in the estuarine tidal flats of the Niida River, which is a
second-class river located in Minamisoma City, Fukushima Prefecture,
Japan
Fig. Study site. 30

31. UAV Aerial Photography Methods
 Vegetation map is created from the aerial photographs taken by the UAV
 The UAV used a radio-controlled helicopter
 It was equipped with a compact digital camera (Richo GX200) mounted to a small stabilizer
Fig. UAV (unmanned aerial vehicle)
system. *Radio-controlled helicopter
used in the study
Fig.The landscape where aerial photographs
using the UAV (unmanned Aerial vehicle)
were taken 31

32.  The aerial photography using an aircraft was taken at altitude 2400 m
 resolution about 24 cm/pixel, scale1/20,000 (photographic camera: DMC )
 The aerial photography using UAV was the altitude of about 10 m
 Resolution:3 mm/pixel and scale:1/546.4 (photographic camera: richo newgr)
 The scale and resolution ratios were 36.6 and 80.0 times respectively,
compared with those of aerial photography using an aircraft.
32

33.  The schematic diagram of the general process of mapping using the UAV method is
shown in below fig
The schematic diagram of mapping using the UAV method
33

34.  The aerial photography using UAV was
conducted over a 1.5 km section upstream
from the Niida River estuary (the secondary
river flowing into Minamisoma City in
Fukushima Prefecture) in Agust 2012
 Fixed photography points were set up in a
line from the right bank to the left bank at
approximately 20 m intervals
 aerial photographs at 5 m above the ground
surface was taken.
 There were 13 line numbers in the
investigated section from upstream to
downstream. each line included 8 fixed
photography points, for a total of 104 points UAV photography lines and points (No. 1-
13). *There were 8 fixed Photography
points on each line. 34

35. RESULTS
 In the aerial photographs of
the main plant communities
(Phragmites australis, Typha
domingensis, and
Miscanthussacchariflorus)
taken by the UAV, a clear
discrimination of each plant
community was possible at
a scale of 1/50. At a scale of
1/10,
 it was possible to clearly
confirm the shape of an
individual plant
(a) Phragmites australis community; (b) Typha domingensis community;
(c) Miscanthus sacchariflorus community photographed by UAV methods
(the photo on the right is a close-up of the photo on the left).
35

36.  The borders among the plant communities and mixes of different plant
species in the vicinity of the community borders could also be
discriminated at this scale.
 An example of this resolution is the discrimination between the
Phragmites australis/Scirpus yagara community and the Phragmites
australis/Typha domingensis community
36

37. 37
The vegetation division obtained by UAV methods (Top photograph: Phragmites australis community,
Scirpus yagara community. Bottom photograph: Phragmites australis community, Typha domingensis
community)

38. 38
The vegetation map of the Niida River (vegetation mapping
using an aerial photograph (above); vegetation mapping using
UAV methods

39.  A detailed community division was confirmed on the vegetation map created using the
UAV method, and the difference in precision was remarkable.
 The vegetation map created using the UAV method could clearly discriminate community
divisions and distributions
Vegetation maps using UAV methods and aerial photography (Aerial
photograph, left; UAV methods, right).
39

40. Conclusions
 The aerial photography using UAV was conducted in the Niida River ,Japan
 The aerial photographs of the main plant communities (Phragmites australis, Typha
domingensis, and Miscanthus sacchariflorus) was taken at the 1/50 scale
 Clearly discriminate plant community distributions
 It can conclude that vegetation surveys using UAV are possible and are capable of a highly
precise community division in places where field reconnaissance is difficult
40

41. References
• AggieAir., 2017. A Remote Sensing Unmanned Aerial System for Scientific
Applications. <www.aggieair.usu.edu> (7 March 2017 ).
• Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. 1998. Crop evapotranspiration -
Guidelines for computing crop water requirements - FAO Irrigation and drainage paper
56, Irrig. Drain. Syst. 300(9).
• Al-Arab, M., Torres-Rua, A., Ticlavilca, A., Jensen, A.., and McKee, M. 2013. Use of
high-resolution multispectral imagery from an unmanned aerial vehicle in precision
agriculture, IEEE International Geoscience and Remote Sensing Symposium -
IGARSS, 2852–2855, ieeexplore.ieee.org.
• Andrade, R.D.O., 2013. The flight of the falcon. Availableonline:
http://revistapesquisa.fapesp.br /en/2013/10/23/the-flight-of-the-falcon
• Huang, Y.B., Thomson, W.C., Hoffmann, Y.B., Lan, B.K., and Fritz, 2013.
Development and prospect of unmanned aerial vehicle technologies for agricultural
production management. Int J Agric & Biol Eng 6(3): 1-10.
41

42. • Irish, R. R., 2000. Landsat 7 science data users handbook, NASA Contract. Rep. NASA CR
:430–415.
• Lelong, C.D., Burger, G., Jubelin, B., Roux, S., Labbe, F., and Baret, 2008. Assessment of
unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots.
Sensors. 8: 3557-3585
• Tokekar, P.,J., Vander Hook, V., and Isler, 2013. Sensor Planning for a Symbiotic UAV and
UGV system for Precision Agriculture. Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems Tokyo, Japan. pp 5321-5326.
• Torres-Rua, A., Al Arab, M., Hassan-Esfahani, L., Jensen, A., and McKee, M. 2015.
Development of unmanned aerial systems for use in precision agriculture: The AggieAir
experience, IEEE Conference on Technologies for Sustainability.
• USGS., “Landsat 8 Data Users Handbook,” USGS (2016).
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