Digitalization of Agriculture

A session on "Digitalization of Agriculture" at Entrepreneurship Conclave organized by Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay.

1. RESEARCH, TECHNOLOGY, DIGITIZATION
BIGDATA, ARTIFICIALINTELLIGENCE & MACHINELEARNING,
BLOCKCHAIN, INTERNET OFTHINGS, CLOUDCOMPUTING
DIGITALIZINGTHE
AGRICULTURE

2. ABOUTME–DEEPAKPAREEK
•Apublishedauthorof7booksonvarioustechnologyand
businesssubjects.
•WorldEconomicForumhonoredTechnologyPioneer
2018andExpert–DigitalTransformation.
•Amongsttop100SocialEntrepreneurlistedbyNational
UniversityofSingaporeandDBSFoundation.
•Regularspeakerofglobalreputewithhonorofspeakingat
eventsofhighreputeincludingWorldEconomicForum
AnnualMeeting–Davos,WorldEconomicForumASEAN
-Hanoi,WorldEconomicForumAnnualMeetingof
Champions(Mini-Davos)–Tianjin,ASEANMarketing
Forum–Jakarta,GeospatialWorldForum–Hyderabad,
SustainableFoodSystems–Bangkok,BetterRice
Initiative–Vietnam,NGTech-SaltLakeCity,ITU
Americas–Brazil.

3. AGRICULTURE, INDIANCONTEXT

4. TOTALOPERATIONAL HOLDINGS ININDIA(%)

5. OPERATIONAL HOLDINGS ININDIA(HA)

6. AREAUNDERIRRIGATION(%)

7. INDEBTEDNESS OFOURFARMERS

8. ISMSP MODELSUSTAINABLE???

9. ISOURAGRICULTURE SUSTAINABLE???

10. AGRICULTURE, A STORYOFTWOWORLDS

11. PREGREENREVOLUTION–BEFORE1960
INPUTS
SEEDS
ANIMALWASTE
FARMWASTE
WATER
HUMANLABOR
ACTIVITIES
MANUAL
CLEANING
RESOURCES
GUNNYBAGS
SILOS
REACH
PERISHABLES–
DOMESTIC/LOCAL
NONPERISHABLES–
LOCAL/DOMESTIC/EX
PORTS

12. POSTGREENREVOLUTION
INPUTS
SEEDS
FERTILIZERS
CROPPROTECTION
MECHANIZATION
ACTIVITIES
DRYING
CLEANING
SORTING
AGGREGATION
CONVERSION
RESOURCES
TREATEDGUNNY
/POLYTHENEBAGS
SILOS
CHEMICAL
TREATMENT
COLDSTORAGE&
TRANSPORTATION
REACH
PERISHABLES–
GLOBAL
NONPERISHABLES–
GLOBAL

13. CURRENTSTATUS, THEIMPERFECTWORLD
TODAYHUMANCIVILIZATIONIS
ATTHECROSSROADSPLAGUED
BYTHREEMAJORCHALLENGES
FOOD
SECURITY
CLIMATE
CHANGE
AGRARIAN
DISTRESS

14. FOOD SECURITY
WITH0.8 BILLIONPEOPLEALREADY
HUNGRYWHILE2 BILLIONMOREWILLBE
ADDEDBY2050 ANDANOTHER2 BILLION
BY2100,
WRITINGISALREADY ONTHEWALL

15. CLIMATECHANGE
DEFORESTATION DUETOUNSUSTAINABLE
FARMINGISCONSIDERED TOBEKEYDRIVER
BEHINDWORLD BECOMING LESSHABITABLE
WEAREPASSINGOURNEXT
GENERATION FARWORSTTHEN
WHATWEINHERITED

16. AGRARIANDISTRESS
SMALLHOLDERFARMERS AREIN
ENORMOUS DISTRESSDUETOUNVIABLE
OPERATIONS, LOWYIELD, UNSUSTAINABLE
FARMING
TODAYMOSTFARMERS DON’T
WANTTHEIRCHILDREN TO
CONTINUE FARMING

17. WECANTACKLETHESE
CHALLENGES
BYPRODUCING MOREFOODWITHLESS
LAND, LIMITEDWATERANDFEWER
RESOURCES HENCEMAKING FARMING
PROFITABLE FORSMALLHOLDER
FARMERS

18. 1.8 BILLIONSMALLHOLDERFARMERS AREKEYTOFOOD
SECURITY ASA LARGESTCULTIVATORS OFFOODCROP, THEY
MANAGE500 MILLIONFARMS
BUTSMALLHOLDERFARMERS AREIN
ENORMOUS DISTRESS
BECAUSEOF
INSIGHT
VACUUM
INCREASINGCOST
OFCULTIVATION
HIGHRISK&
ACCESSTO
FINANCE
LOW
REALIZATION
FROMSALES

19. FARMERS
(LACK
OF..)
ACCESSTO
RESOURCES
RELEVANT
CUSTOMIZE
D
INFORMATI
ON
ACTIONABL
EINSIGHTS
TOASSIST
DECISION
MAKING
REAL-TIME
INTERVENT
ION&
SUPPORT
PROFIT
ENHANCEM
ENT& RISK
MITIGATIO
NTOOLS
SAYIN
THEREOWN
FUTURE
ECOSYSTEM
PLAYERS
(LACK
OF..)
ACCURATE
FARM&
FARMER
DATA
LASTMILE
ACCESSTO
FARMERS
REAL-TIME
DATAOF
FARMER
ACTIVITIES
MEANINGF
UL
INFORMATI
ON
DISSEMINA
TION
FARMING
AUTOMATI
ON&
MECHANIZ
ATION
INTELLIGE
NT
INSIGHTS
FROM
COMPLEX
DATA
GAPS-INDEVELOPINGECONOMIES

20. APOCALYPSE TORE-WRITINGTHEFUTURE
DATADRIVEN
INSIGHTFUL
SCALABLE
HOLISTIC
DISTRIBUTED
SELF-LEARNING
TRANSPARENT
REAL-TIME
COLLABORATIVE
PROFITABLE
WENEED, A TRULYSUSTAINABLE
AGRIFOODSYSTEM

21. CHALLENGES
AGRICULTURAL DISPARITY–LOCALCONTEXT
FARMINGSETUP–SIZEMATTERS
PERSONALIZATION VITAL-INDIVIDUAL, ADAPTABLE, CONTEXTUAL
MANYSTAKEHOLDERS –DIVERSIFIEDINTERESTS
DEMANDING CUSTOMERS–DIFFERENTNEEDSANDINCREASEDAWARENESS
INFRASTRUCTURE BOTTLENECKS –BOTHDIGITAL& PHYSICAL

22. GOINGFORWARD–FUTUREOFFOODPRODUCTION

23. SMARTFARMS–FUTUREOFFARMING

24. BREAKING THEICE–DIGITALTRANSFORMATION

25. •ISTHEECONOMIC ANDSOCIETALEFFECTSOFDIGITIZATION AND
DIGITALIZATION.
DIGITALTRANSFORMATION
•ISTHECONVERSION OFANALOGUE DATAANDPROCESSES INTOA
MACHINE READABLE FORMAT.
DIGITIZATION
•ISTHEUSEOFDIGITALTECHNOLOGIES ANDDATAASWELLAS
INTERCONNECTION THATRESULTS INNEW ORCHANGES TO
EXISTINGACTIVITIES.
DIGITALIZATION
•AREICT,INCLUDING THEINTERNET,MOBILE,DEVICES,AND
DATA ANALYTICS USED TOIMPROVE THE GENERATION,
COLLECTION,EXCHANGE,AGGREGATION ,ANALYSIS,ACCESS,
SEARCHABILITY ANDPRESENTATION OFDIGITALCONTENT.
DIGITALTECHNOLOGIES
DIGITALTRANSFORMATION –DEFINITION
DIGITALTRANSFORMATION HASBEENASTRONGTHEMEINBOTHBUSINESSANDIT OVERTHEPASTFIVE
YEARSANDOFTENISATERMMISTAKENLY USEDFORALMOSTANYKINDOFNEWTECHNOLOGY ADOPTION.

26. DIGITALTRANSFORMATION –ENABLERS

27. DIGITALTRANSFORMATION –AGRICULTURE
DIGITALTRANSFORMATION IN
AGRICULTURE ISNOTJUSTABOUT
TECHNOLOGY . WHILESURELYITIS
ENABLED BYTECHNOLOGY BUTTHE
UNDERLYING FACTISTHATIT
IMPACTSEVERYFUNCTION INTHE
AGRICULTURE ECOSYSTEM AND
NEEDSANINNOVATIVE APPROACH
WITHINANDOUTSIDETHE
BOUNDARY OFBOTHECOSYSTEM AS
WELLASORGANIZATIONS
PARTICIPATING INTHEECOSYSTEM
TOYIELDENVISIONED BENEFITS

28. DIGITALTRANSFORMATION –
HUGEOPPORTUNITY FOR
AGRICULTURE SECTOR
THEDIGITIZED21STCENTURY
FARMISBECOMING AREALITYAT
ARAPIDPACE, THE$12 TRILLION
AGRIBUSINESS INDUSTRY
REMAINS ININITIALPHASEOF
ITSDIGITALTRANSFORMATION .
THENEXTPHASEWILLCONNECT
INDIVIDUAL TECHNOLOGY
PRODUCTS ANDTHEDATATHEY
GENERATE INTOAHIGHLY
INTEGRATED, EASYTOUSE
NETWORK OFINFORMATION ,
TOOLS, SYSTEMSANDSOLUTIONS
TOGENERATE BETTERTANGIBLE
RESULTSFORTHEFARMER, AS
WELLASFORTHEBROADER
AGRICULTURE ECOSYSTEM.
INDUSTRY LEADERSACROSSTHE
AGRICULTURE VALUECHAINARE
FORMING COMPREHENSIVE
DIGITALSTRATEGIES TOWIN
MINDSHARE, ANDWALLET
SHARE, OFBOTHTHEFOOD
GROWERS ANDFOOD
CONSUMERS . THESESTRATEGIES
NEEDTODELIVERTHEHOLISTIC,
OUTCOME-BASEDSOLUTIONS
THATOURGLOBALFOODSYSTEM
NEED.

29. TECHNOLOGY MEGATRENDS

30. DIGITIZATIONTHEWAYFORWARD
THEIMMENSE AMOUNTS OFAGRONOMIC DATA
OFFER INSIGHT,UNDERSTANDING ,ANDQUICK
LEARNINGS.DIGITALFARMING ISPARTICULARLY
REVOLUTIONARY FORSMALLHOLDERS ASITHAS
THE POTENTIAL TOREMOVE THE CURRENT
INFORMATION ASYMMETRY .
TOBENEFIT FROM THENEWDIGITALFARMING
FRAMEWORK ,CERTAIN KEYWORDS AREALWAYS
APPLICABLE:LOCAL,RELEVANT,ANDPERSONAL.
NEWTECHNOLOGIES CANALIGN WITH THIS
FRAMEWORK . CONNECTING LARGE-SCALE
COMPANIES (BOTHINPUTANDOUTPUT)WITH
LOCALFARMERS WILLBEMADEPOSSIBLE WITH
DIGITALTECHNOLOGIES .HOWEVER,INORDERTO
TRULY FACILITATE DIGITAL FARMING,THE
FUNDAMENTAL QUESTION THATMUSTALWAYS BE
ADDRESSED IS“WHY?”

31. TECHNOLOGY
MEGATRENDS
SHAPING
FUTUREOF
FOOD&
AGRICULTURE
SECTOR
DIGITIZATION
BIGDATA
BLOCKCHAIN
AI & ML

32. ALLTYPESOF
ORGANIZATIONS
AREGETTING
IMPACTED
DIFFERENTLY,
DEPENDING ON
THEIREXPOSURE
ANCILLARY
SERVICES
•BANKS
•MICROFINANCE
•INSURANCE
•LOGISTICS
•NGOS
•EXTENSION
•ACADEMICS
•GOVERNMENT
•CERTIFICATION
•WEATHER&
METEOROLOGY
FOOD
•AGGREGATORS
•COMMODITY
TRADERS
•FOOD
PROCESSORS
•INTERMEDIARIES
•RETAILERS
•FOODSAFETY
•FOODPACKAGING
AGRICULTURE
INPUT
•SEEDS
•CROPNUTRIENTS
•CROP
PROTECTION
•FARM
CONSUMABLES
•FARM
MECHANIZATION

33. BIGDATA, DATADRIVENDECISIONS

34. UNDERSTANDING BIGDATA
PETABYTES, EXABYTES, ZETABYTES OFDATA
WHERE VOLUMES TOOGREATFORTYPICALDBMS
MASSIVESETSOFUNSTRUCTURED /SEMI-
STRUCTURED DATAI.E. TEXT, IMAGES, VIDEOS
RAPIDGENERATIONOFTIMESERIESDATAI.E.
PROCESSMONITORINGDATA, WEATHERSTREAM,
SENSORI/O, SATELLITEIMAGES
VELOCITY
VOLUME

35. UNDERSTANDING BIGDATA–5VS
VELOCITY VALUE
VERACITY VARIETY
VOLUME

36. BIGDATAISABIGOPPORTUNITY
BIGDATA ISABIGDEAL.MORETHAN HALF OF
ENTERPRISES GLOBALLY VIEW BIGDATA ASAN
OPPORTUNITY AND PLAN TO INCREASE THEIR
INVESTMENTS INBIGDATAINTHENEXTFEWYEARS.
BUTBIGDATA’SVALUE DOESN’TCOME FROM THE
COLLECTION OFINFORMATION ;THAT’SJUST THE
STARTING POINT.THEREALVALUEOFBIGDATACOMES
FROMYOURABILITYTOCOMBINE ANDANALYZE IT–NO
MATTER HOW MUCH YOUHAVE,INANYNUMBER OF
SOURCES–TOUNCOVER NEWINSIGHTS THATDRIVE
BUSINESSVALUE.
BIGDATAMAYMEANDIFFERENT THINGSTODIFFERENT
BUSINESSES–WHETHER IT’SDEALINGWITHNEWTYPES
OFDATA,STREAMING,ORCONSOLIDATING EXISTING
DATA THAT’STOOLARGE TOFITONTRADITIONAL
SYSTEMS.BUTNOMATTER HOWYOUDEFINEBIGDATA,
THECHALLENGE ANDTHEGOALARETHESAMEFOR
EVERYBUSINESS:GETTINGTHEMOSTVALUEOUTOFIT.

37. DATADELUGEENABLINGPRECISIONAGRICULTURE
PRECISIONAGRICULTURE
DEMONSTRATES THATITIS
POSSIBLETOGENERATE ALOTOF
DATAVIAFARMING MACHINERY
ANDCOMBINE ITWITH
GEOSYSTEMS, DRONES, SENSORS
ANDSATELLITES, MAKING IT
POSSIBLETOSUPPORT
OPERATIONAL FARMING WITH
LOCATION-SPECIFICDATATAGS.
SMARTFARMEQUIPMENT ALONG
WITHBIG
DATAANALYTICS WILLENABLE
INSIGHTSANDOPTIMIZATION ON
THEFIELD.

38. DATADRIVENDECISIONMAKING–ANALYTICALMODELS
PRESCRIPTIVE
ANALYTICS
PREDICTIVE
ANALYTICS
DIAGNOSTIC
ANALYTICS
WHAT
HAPPENED?
WHATWILL
HAPPEN?
HOWCANWE
MAKEITHAPPEN?
WHYDIDIT
HAPPEN?
DESCRIPTIVE
ANALYTICS
VALUE
DIFFICULTY

39. BIGDATA–BUSINESSCASES
SUPPLYCHAINOPTIMIZATION–FARMTOFORK
FARMOPERATIONSMANAGEMENT
SALESEXCELLENCEFORAGRICULTUREINPUTCOMPANIES
REALTIMEFARMERCREDITRATING
AGRICULTUREONLINEMARKETPLACES–OUTPUTANDINPUT

40. AI & ML, ACHIEVINGWHEREHUMANSFAILED

41. LEVELSOFINTELLIGENCE

42. MACHINESBECOMINGMOREHUMANTHENHUMAN

43. MACHINESLEARNINGMODELS

44. AI & ML BUSINESSCASES-AGRICULTURE
•CROPHEALTHMONITORING USINGDEEPLEARNINGALGORITHMS BASEDONREAL-TIMEDATAFROM
SENSORS,SATELLITE/DRONE IMAGES,ONGROUND FARMING PRACTICES ANDGROUND TRUTHING
TECHNIQUES.CROPMONITORING
•ARTIFICIALNEURALNETWORKS(ANN)TOIDENTIFYPOTENTIALDEFECTSBOTHINSOILANDPLANTS.IMAGE
PROCESSINGALGORITHMS ALONGWITHHISTORIC/CURRENTLOCALPEST,SOIL,WEATHERANDACTIVITYDATA
ISUSEDFORTRAININGANN.
PEST& SOILDEFECT
DETECTION
•MACHINELEARNINGTECHNIQUESAREUSEDTOCAREFORPLANTSBYDEPLOYINGUAVS&UAGSINCLUDING
AUTOMATED APPLICATIONOFPESTICIDESANDPLANTNUTRIENTS,ELIMINATIONOFWEEDS,IRRIGATION.FARMAUTOMATION
•AIALGORITHMS AREUSEDFORPREDICTIONOFYIELD,CROPQUALITY,INPUTSIDEDEMANDS,OUTPUT
AGGREGATION NEEDSLEADINGTOOPTIMIZATION OFSUPPLYCHAIN(INPUT&OUTPUT),POLICY
INTERVENTION ETC.
PREDICTIVE
ANALYTICS
•FARMING ACTIVITY RECOMMENDATIONS INCLUDING CROP/VARIETY SELECTION,CROP
NUTRIENT/PROTECTION ANDSOWING/IRRIGATION/HARVESTTIMING BASED ONDEMOGRAPHIC,
AGRICULTUREANDMARKETPROFILES.
RECOMMENDATION
ENGINE

45. BLOCKCHAIN, MAKINGAGRICULTURE
TRANSPARENT ANDFAIR

46. BLOCKCHAIN ISNOTBITCOIN
BUTITSORIGINSLIEINBITCOIN, MAKINGITA10 YEAROLDTESTEDTECHNOLOGY.
BITCOINWASDEVELOPEDASCRYPTOCURRENCY -ATECHNOLOGICAL ALTERNATIVETOFIATCURRENCIES
(DOLLAR, EURO, POUND).ANANONYMOUS“BANKOFTHEINTERNET”.
FINITENUMBEROFBITCOINSSUPPOSEDLYPROVIDESGOLD-STANDARDTYPEGUARANTEE AGAINSTINFLATION.
BITCOINDEPENDSONTHEBITCOINBLOCKCHAINTOFUNCTIONANDALLBITCOINTRANSACTIONS ARE
RECORDEDONTHEBITCOINBLOCKCHAIN.
THEBLOCKCHAINISTHEINFRASTRUCTURE UPONWHICHBITCOINRESTS, EVERY10 MINANEWBLOCKISADD
BY“MINERS” (WHOCONSUMEHUGEAMOUNTSOFENERGY).

47. BLOCKCHAIN, A DISTRIBUTEDLEDGERTECHNOLOGY
A BLOCKCHAINISSIMPLY
DATABASEBUT
•DISTRIBUTEDACROSSTHENETWORK
(INTERNET) -EVERYONEHASACOPY
•AUTO-SYNCED-EVERYCOPYISTHE
SAMEALMOSTINSTANTLY
•ENCRYPTED-ALLBLOCKSARE
ENCRYPTEDWITHPRIVATEKEYS
•IMMUTABLE-NOTRANSACTIONCAN
BEDELETED
•COMMONLY OPENANDPUBLIC-
EVERYONE(AUTHORISED) CANADD
•CONSENSUSBASED-ENSURESONLY
ONEVERSIONOFTHETRUTH

48. HISTORYOFBIGGESTDISRUPTION AFTERINTERNET
ONOCTOBER31,2008,SATOSHINAKAMOTO RELEASED THEBITCOINWHITEPAPEROUTLINING APURELY
PEERTOPEERELECTRONIC CASH/DIGITALASSETTRANSFER SYSTEM.THISISTHEFIRSTPOPULAR
IMPLEMENTATION OFBLOCKCHAIN ANDISATTRIBUTED ASBIRTHING TODAY’SBLOCKCHAIN INDUSTRY.
SINCETHEN,ADDITIONAL BLOCKCHAINS HAVE BEEN POPULARIZED INCLUDING SMART CONTRACT
TECHNOLOGY ,ETHEREUM.

49. UNDERSTANDING WHERETOBLOCKCHAIN

50. BLOCKCHAIN AGRIUSECASES
AGRI-INPUT
E-COMMERCE
•OPTIMIZED
ECONOMICAL
DELIVERYOF
RELEVANT
AGRICULTURE
INPUTSATFAIR
PRICE.
FARM
CREDIT
•EMPOWERING
FARMERSBY
MAKINGLOW
COSTFINANCE
REACHINMOST
OPTIMAL
MANNERIN
ENVIRONMENT
OFTRUST.
PROFITABLE
REALIZATION
•TRANSPARENT
OUTPUTSALES
ENSURE
FARMERSGET
WHATTHEY
DESERVE.
FOOD
SAFETY
•ENSURINGTHE
FOODTOPLATE
ISGROWN
SUSTAINABLY.

51. THEHOLISTICDIGITALVISION

52. WELEVERAGEDIGITAL

53. A HOLISTIC
SOLUTIONFOR
EVERY
STAKEHOLDER IN
AGRICULTURE
ECOSYSTEM

54. OUR
TECH-STACK

55. OURTECH-ARCHITECTURE

56. DIGITAL
INNOVATION
STRATEGY
FUTURE
BUSINESS
MODEL
TECHNOLOGY
CONSOLIDATION
MARGIN
MANAGEMENT
SUPPLYCHAIN
OPTIMIZATION
REGULATION
& RISK
MANAGEMENT
SUSTAINABILITY
& SOCIAL
RESPONSIBILITY
HUMAN
CAPITAL
ENHANCEMENT
WEASSESSYOUR
INNOVATION
READINESS AND
BUILDACUSTOMIZED
INNOVATION
STRATEGY AND
TECHNOLOGY
ROADMAP WITH
ANDFORYOU

57. MAPPING
PROJECTION
DATACAPTURE
DELIVERY
PREDICTION
O
UR
E
XPERTISE
WHATWEDELIVER
RESEARCH
CONSULTING
TECHNOLOGY
PROJECTS

58. “IFYOUDONOTHINGTODAY, TECHNOLOGY MEGATRENDS
WILLDISRUPTYOURMARKETANYWAYTOMORROW.”
THANKYOU!
www.digi-agri.com
[email protected]
Deepak Pareek, CEO & Founder
[phone]