International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 04 | Apr 2026 www.irjet.net p-ISSN: 2395-0072
Social diversity of IoT adopting farmers and challenges in adoption
Mahamaya Prasad Nayak1 , Pradeep Kumar Raut2, Susanta Kumar Dash2 , Sanat Mishra3 and Sidharth Dash4
1Department of Agriculture Extension, OUAT 2 Odisha Computer Application Centre, 3 Centre for Agri-Management, Utkal University, 4 Asst. Prof., CSE, SIET and Research Scholar, DRIEMS University Odisha, India.
Abstract - Males outplayed females with 66.4 and 36.6% owner ship, respectively, but the trend of distribution across farm size was similar for both the sexes under present study ranging from 30 to 40% in all the cases revealing no dependency of gender on farm size However, significant dependency was established between farm size and all other social factors viz. age, education and marketing. High initial cost in IoT was found to be the most important/vital constraint in the present study and maintenance of IoT was the least important one, taking all the farmers into account. Other constraints like financial support of government, power requirement and enhanced production cost were placed in between these two with rankings of II to IV, respectively.
Keywords: Adoption, Challenges, Diversity, Poultry
Introduction
Growth of poultry sector is fast increasing in Odisha for last ten years [1]. Broiler farming has gained enormous popularity. Temperature,humidityandammoniainpoultryhouseactasmajorhurdlesinpoultryproductionsystem inthispartofIndia [2]itisdifficultduringsummerduetothehotandhumidclimateinthestate.Besides,thesummerisrealizedoversixmonths forbroilerfarminginOdisha.Thecombinationofhighambienttemperatures(oftenexceeding40°C)andhighhumidityresults severeheatstress,whichisamajorrecurringprobleminthestate.Temperatureexceeding30°Cleadschickens’inefficiencyin maintainingtheirinternalbodytemperature,leadingtoheatstress,prostrationandhighmortalityrates.
Heat stress significantly reduces feed consumption, leading to lower weight gain and poor feed conversion efficiency (FCE), particularlyatlaststageofgrowth Heatstressweakenstheimmunesystem,makingbirdsmoresusceptibletodiseases High temperaturealsoleadstoreductioninmeatqualityandcommercialvalue.
Internetof thing(IoT) fortemperaturemonitoring isgaining popularity forsmall holders asenvironmental control deviceis notaffordable.IoT-enabledautomatedcontroloffansandmistershasexperiencedsmoothsummermanagementmaintaining desiredandoptimaltemperature,decreasingstressandmortalityratesandlaborcosts.Besides,animalwelfareisensured.
The present study analyses the social factors associated with adoption of IoT in broiler farming and ranking the challengeswithrespecttoitsadoption
Methodology
The study was carried out on IoT adopted broiler farms in Odisha. Information on social status of farmers and challenges in adoptionofIoTwascollectedfrom235farmersrearingbroilerchickenutilizingIoT-enabledautomatedtemperaturecontrol.
Dataforeachfarmerwasclassifiedaccordingtogender(male,female),age(Upto30years,31to45yearsandabove 46years),education(uptoHSC,Graduationandmorethangraduation)andmarketingoption(localmarketandnearbytown) Thestrengthoffarmwascategorisedinthreegroupsviz.<2000,2000to5000and>5000capacities.
The constraints in IoT adoption were analyzed with regard to different factors. Different points on constraints were raised by farmers at the time of survey. Then those constraints, thus listed were put to farmers or respondents to rank the
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 04 | Apr 2026 www.irjet.net p-ISSN: 2395-0072
constraintsandchallengesthroughthequestionnaire.Garret’sRankingTechniquewasadoptedto rankthechallengesinthis study.Theprimeadvantageofthistechniqueoversimplefrequencydistributionisthatthepreferencesarearrangedbasedon their intensity from the point of view of respondents. Hence, the same number of respondents on two or more preferences mayhavebeengivendifferentrank.Garrett’sformulaforconvertingranksintopercentis:
Percentposition=100*(Rij–0.5)/Nj
Where,Rij=rankgivenforith factorbyjth individual;
Nj=numberoffactorsrankedbyjth individual.
Thepercentpositionofeachrank wasconvertedintoscoresreferringtothetable given by [3].Foreachfactor,thescoresof individualrespondentswereaddedtogetheranddividedbythetotalnumberoftherespondentsforwhomscoreswereadded. Thesemeanscoresforallthemodeswerearrangedindescendingorder;thechallengeswereaccordinglyranked. Therespondentswereaskedtorankthefiveconstraintsidentifiedforthepurposeofthisstudyas1,2,3,4 and5inorderto know their preference. The calculated percentage position for the rank 1, 2, 3,4 and 5 and their correspondent Garrett table are shown in Table 1. For individual constraint, the total score was calculated by multiplying the number of respondents ranking that factor as 1, 2, 3,4 or 5 and then the mean score of the individual constraint was calculated by dividing the total numberofrespondentsandfurtherrankedwithregardtothemeanscore.
Results and Discussion
Frequency distribution of farmers
FrequencydistributionofpoultryfarmerswithregardtotheirsocialdivbersityacrossfarmsizealongwithChi-square test of independence to examine the dependency between farm size and individual social factors of IoT adopted broiler farmersispresentedinTable2
Itwasrevealedthat,86(36.6%)ofallfarmerswerefoundtobefemalesagainst149(66.4%)males.Genderoffarmers wasindependentoffarmsize,indicatingthefactthat, thetrendofdistributionacrossfarmsizewassimilarforboththesexes underpresentstudyrangingfrom30to40%inallthecases.
Maximum farmers (65.5%) were found to be under moderate age group in pooled sample and corresponding proportionsofyoungerandolderfarmerswereestimatedas20.9%and13.6%,respectively.Inotherwords,outof20farmers 13were middle agedfarmersand 4fromyoung and 3from oldgroup. However, significant dependency wasfound between thetwofactorsviz.farmsizeandage,revealingthat,youngerfarmersagedbelow30yearshaveoptedforlargefarms(53.1%), butmoreelderlyfarmerspreferredforsmallfarmsizesinthepresentstudy.Ithasbeenrevealedthat,thefrequencyoflarger farmsdecreasedastheageoffarmerincreased.
Farmershaving qualificationof more than graduation were 119against 71and45 havinggraduation and uptoHSC level, respectively in the present study. Besides, there was dependency of farm size on education of the farmer. It is ascertainedthat, educationlevel belowHSC optedforsmallfarmsize butgraduatesandmorethanthatleveloptedmorefor largerfarmsinthepresentstudy.
Table 1. Percent position vis-à-vis garret table score
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 04 | Apr 2026 www.irjet.net p-ISSN: 2395-0072
Veryhighlysignificantdependencywasrealizedbetweenfarmsizeandsellingoption,revealingthat,verylargefarms optedtosellthebirdsmoreinnearbytown(53.4%)thaninlocalmarket(9.2%) However,boththesmallerfarmsoftensold theirproducelocallywithalmostsimilartrend.
Mostoftheabovefindingsareinlinewiththeopinionof[4]inHaringhatablackchickenfarmers,[5]innativechicken farmersinMizoram,[6]amongtribalfarmersinOdishaandVasanthakumarand[7]onastudyinTamilnadu.
Table 2. Frequency distribution of IoT enabled broiler farmers across social factors and farm size.
Figuresinparenthesesindicatepercentageacrossrowunderafactor,*p<0.01
Table 3. Ranking of different challenges in IoT adoption
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 04 | Apr 2026 www.irjet.net p-ISSN: 2395-0072
Analysis of challenges in IoT enabled poultry production system
Distribution of responses with regard to individual rankings along with mean Garrett scores and final Garrett rankingsarepresentedinTable3.HighinitialcostinIoTwasfoundtobethemostimportant/vitalconstraintinthepresent studyandmaintenanceofIoTwastheleastimportantone,takingallthefarmersintoaccount.Otherconstraints likefinancial supportofgovernment,powerrequirementandenhancedproductioncost wereplacedinbetweenthesetwowithrankingsof IItoIV,respectively.Thishasanalignmentwiththeattitudeoffarmersthatfarmersoftengiveprioritytoinitialcostinvolved fromtheirownfunds.Besides,thefarmerswantedsomesubsidyorsupportfromgovernmentinadoptinga newtechnology. AstheIoTsareinstalledwithinlastonetothreeyears,maintenancerequirementwasinveryfewcases.Hence,itwaskeptlow asachallenge.
The present trend of constraint analysis was broadly at par with reports of [8] in Goa and [9] on a similar study in Bangladesh.
Future
Scope
Presentfindingsonfrequencydistributionoffarmersacrosssocialparametersandrankingof challengesinadoption ofIoTcouldbeusedindecisionmakingstrategyunderstatepolicytriggeringlivelihoodenhancementofpoultryfarmers
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