{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T12:59:31Z","timestamp":1740142771085,"version":"3.37.3"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2022,7,30]],"date-time":"2022-07-30T00:00:00Z","timestamp":1659139200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This article devised an effective Student Psychology-based Dragonfly Political Optimizer (SPDPOA) for predicting heat level and soil moisture to monitor plant health in the Internet of Things (IoT). The developed SPDPOA is modeled by integrating the Student Psychology-based Optimization (SPBO) algorithm, Dragonfly Algorithm (DA) and Political optimizer (PO), respectively. The prediction process is done in the base station (BS), which gathers the IoT nodes\u2019 information through optimal Cluster Head (CH) using Deep Recurrent Neural Network (Deep RNN). Moreover, the CH selection and routing process are established using a developed SPDPOA scheme. The data transformation and feature selection processes are done based on Box-Cox transformation and wrapper model, correspondingly, which helps in the selection of best features. Moreover, the developed SPDPOA scheme attained better performance in Packet Delivery Ratio (PDR), energy and testing accuracy of 0.7232, 0.6342\u00a0J and 0.9372, respectively.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac096","type":"journal-article","created":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T20:10:15Z","timestamp":1659125415000},"page":"2059-2074","source":"Crossref","is-referenced-by-count":2,"title":["SPDPOA: Student Psychology Dragonfly Political Optimizer Algorithm-Based Soil Moisture and Heat-Level Prediction for Plant Health Monitoring in Internet of Things"],"prefix":"10.1093","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2946-3354","authenticated-orcid":false,"given":"Satish","family":"Muppidi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, GMRIT , Rajam 532127 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2963-4272","authenticated-orcid":false,"given":"Kishore","family":"Bhamidipati","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Manipal Institute of Technology, MAHE , Manipal 576104 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9699-3729","authenticated-orcid":false,"given":"Sajeev Ram","family":"Arumugam","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence and Data Science, Sri Krishna College Of Engineering And Technology , Coimbatore 641008 , India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,7,30]]},"reference":[{"key":"2023081805254097100_ref1","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.35940\/ijisme.D1186.016420","article-title":"Real time IoT application for classification of crop diseases using machine learning in cloud environment","volume":"6","author":"Thakur","year":"2020","journal-title":"IJISME"},{"key":"2023081805254097100_ref2","first-page":"639","article-title":"Advanced sensor materials based real-time soil moisture content and temperature monitoring using IoT Technology in Smart Agriculture","volume":"39","author":"Aniley","year":"2019","journal-title":"Intl. 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