Designing a scalable agricultural information system for pest detection and decision support in hazelnut cultivation

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dc.authorid0000-0001-7355-5339
dc.contributor.authorAydın, Şahinen_US
dc.date.accessioned2025-11-14T08:11:20Z
dc.date.available2025-11-14T08:11:20Z
dc.date.issued2025-11-12
dc.departmentIşık Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, Enformasyon Teknolojileri Bölümüen_US
dc.departmentIşık University, Faculty of Economics, Administrative and Social Sciences, Department of Information Technologiesen_US
dc.description.abstractThis study presents a microservices-based, multi-tiered information system to detect, monitör and manage pest species that cause yield losses in hazelnut production. The system integrates a deep learning model for classifying pest images submitted by field users, the generation of pest density maps and location-based early warning mechanisms for growers. Delivered through mobile, web and desktop platforms, the system enables data sharing among farmers, researchers and decision-makers, supporting agricultural decisions. Experimental findings show that the DNN+ResNet50 architecture achieved the highest accuracy (91.88%) among all tested CNN models. Performance evaluations indicated that the Authentication and Heatmap services sustained high stability under loads of up to 1000 requests, while the Bug Classification Service was reliable up to 750 requests before reaching a critical resource threshold. The usability test resulted in an overall score of 38 out of 50, with sub-scores of Appropriateness Recognizability (0.73, Acceptable), Learnability (0.71, Acceptable), Operability (0.65, Questionable), User Error Protection (0.86, Good), User Interface Aesthetics (0.83, Good) and Accessibility (0.74, Acceptable). With its robust technical architecture and practical implementation, the proposed system can generate economic, social and commercial outcomes. This study provides a software engineering-oriented approach to the digitalization of agricultural production and the sustainable management of pests.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationAydın, Ş. (2025). Designing a scalable agricultural information system for pest detection and decision support in hazelnut cultivation. International Journal of Software Engineering, 1-34. doi:https://doi.org/10.1142/S0218194025500780en_US
dc.identifier.endpage34
dc.identifier.issn0218-1940
dc.identifier.issn1793-6403
dc.identifier.scopus2-s2.0-105021385472
dc.identifier.scopusqualityQ3
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/6786
dc.identifier.urihttps://doi.org/10.1142/S0218194025500780
dc.identifier.wosWOS:001612137500001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorAydın, Şahinen_US
dc.institutionauthorid0000-0001-7355-5339
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherWorld Scientific Publishing Companyen_US
dc.relation.ispartofInternational Journal of Software Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInformation systemen_US
dc.subjectSoftware architectureen_US
dc.subjectMicroservicesen_US
dc.subjectAgricultural pestsen_US
dc.subjectHazelnut productionen_US
dc.subjectCultivationen_US
dc.subjectData sharingen_US
dc.subjectDecision makingen_US
dc.subjectDecision support systemsen_US
dc.subjectDeep learningen_US
dc.subjectInformation managementen_US
dc.subjectInformation useen_US
dc.subjectLearning systemsen_US
dc.subjectUser interfacesen_US
dc.subjectAgricultural information systemsen_US
dc.subjectDecision supportsen_US
dc.subjectDensity locationsen_US
dc.subjectLearning modelsen_US
dc.subjectMulti-tiereden_US
dc.subjectPests imagesen_US
dc.subjectYield lossen_US
dc.subjectClassificationen_US
dc.subjectManagementen_US
dc.titleDesigning a scalable agricultural information system for pest detection and decision support in hazelnut cultivationen_US
dc.typeArticleen_US
dspace.entity.typePublicationen_US

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