Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An IoT-based agriculture maintenance using pervasive computing with machine learning technique Subject The topic of the resource Classification; Crop harvesting; Detection of plant disease; RFO; Threshold segmentation Description An account of the resource Purpose: In cultivation, early harvest offers farmers an opportunity to increase production while decreasing the chances of lower crop production rates, ensuring that the economy remains balanced. The significant reason is to predict the disease in plants and distinguish the type of syndrome with the help of segmentation and random forest optimization classification. In this investigation, the accurate prior phase of crop imagery has been collected from different datasets like cropscience, yesmodes and nelsonwisc. In the current study, the real-time earlier state of crop images has been gathered from numerous data sources similar to crop_science, yes_modes, nelson_wisc dataset. Design/methodology/approach: In this research work, random forest machine learning-based persuasive plants healthcare computing is provided. If proper ecological care is not applied to early harvesting, it can cause diseases in plants, decrease the cropping rate and less production. Until now different methods have been developed for crop analysis at an earlier stage, but it is necessary to implement methods to advanced techniques. So, the detection of plant diseases with the help of threshold segmentation and random forest classification has been involved in this investigation. This implemented design is verified on Python 3.7.8 software for simulation analysis. Findings: In this work, different methods are developed for crops at an earlier stage, but more methods are needed to implement methods with prior stage crop harvesting. Because of this, a disease-finding system has been implemented. The methodologies like Threshold segmentation and RFO classifier lends 97.8% identification precision with 99.3% real optimistic rate, and 59.823 peak signal-to-noise (PSNR), 0.99894 structure similarity index (SSIM), 0.00812 machine squared error (MSE) values are attained. Originality/value: The implemented machine learning design is outperformance methodology, and they are proving good application detection rate. 2021, Emerald Publishing Limited. Creator An entity primarily responsible for making the resource Kailasam S.; Achanta S.D.M.; Rama Koteswara Rao P.; Vatambeti R.; Kayam S. Source A related resource from which the described resource is derived International Journal of Intelligent Computing and Cybernetics, Vol-15, No. 2, pp. 184-197. Publisher An entity responsible for making the resource available Emerald Group Holdings Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1108/IJICC-06-2021-0101" target="_blank" rel="noreferrer noopener">https://doi.org/10.1108/IJICC-06-2021-0101</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119492141&amp;doi=10.1108%2FIJICC-06-2021-0101&amp;partnerID=40&amp;md5=e3435df6852604760887e596f7867b5e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119492141&amp;doi=10.1108%2fIJICC-06-2021-0101&amp;partnerID=40&amp;md5=e3435df6852604760887e596f7867b5e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1756378X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kailasam S., CSE, Koneru Lakshmaiah Education Foundation, Guntur, India; Achanta S.D.M., ECE, Vignan's Institute of Information Technology, Visakhapatnam, India; Rama Koteswara Rao P., ECE, NRI Institute of Technology, Krishna, India; Vatambeti R., CHRIST (Deemed to be University), Bengaluru, India; Kayam S., ECE, Koneru Lakshmaiah Education Foundation, Guntur, India