{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:22:25Z","timestamp":1779099745949,"version":"3.51.4"},"reference-count":8,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2019,6,13]],"date-time":"2019-06-13T00:00:00Z","timestamp":1560384000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2019,10,25]]},"abstract":"<jats:p>There are many optional basic frameworks of the Internet of Things, which result in high energy consumption for Internet of Things monitoring platform of straw recycling, and cannot improve the thermal energy conversion rate of the straw recycling monitoring system effectively. Thus, the design is based on smart surveillance system of Internet of things of straw recycling process. The WMNBM14s chip and the STM32F103 chip are used in the basic frame of Internet of things to collect and process the straw recycling data in the monitoring system, and obtain the data processing result of the straw recycling process. The data processing result of the straw recycling process is transmitted to Internet of Things Control Terminal through the BCM43362 wireless chip. The experimental results show that the designed platform has low energy consumption and can improve the thermal energy conversion rate of the straw recovery system.<\/jats:p>","DOI":"10.3233\/jifs-179306","type":"journal-article","created":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T12:22:07Z","timestamp":1560860527000},"page":"4717-4723","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Research on smart surveillance system of Internet of Things of straw recycling process based on optimizing genetic algorithm"],"prefix":"10.1177","volume":"37","author":[{"given":"Jia","family":"Mao","sequence":"first","affiliation":[{"name":"School of Transportation, Jilin University, Changchun, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiping","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Transportation, Jilin University, Changchun, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Mechanical Science and Engineering, Jilin University, Changchun, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,6,13]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"112","article-title":"An Immune Genetic Algorithm for Multi-Echelon Inventory Cost Control of IOT Based Supply Chains[J]","volume":"52","author":"Wang Y.","year":"2018","unstructured":"WangY., GengX., FanZ., et al., An Immune Genetic Algorithm for Multi-Echelon Inventory Cost Control of IOT Based Supply Chains[J], IEEE Access 52 (2018), 112\u2013115.","journal-title":"IEEE Access"},{"key":"e_1_3_2_3_2","first-page":"10","article-title":"An Intelligent Outlier Detection Method with One Class Support Tucker Machine and Genetic Algorithm towards Big Sensor Data in Internet of Things[J]","volume":"85","author":"Deng X.","year":"2018","unstructured":"DengX., PengJ., PengX. et al., An Intelligent Outlier Detection Method with One Class Support Tucker Machine and Genetic Algorithm towards Big Sensor Data in Internet of Things[J], IEEE Transactions on Industrial Electronics 85 (2018), 10\u201319.","journal-title":"IEEE Transactions on Industrial Electronics"},{"key":"e_1_3_2_4_2","first-page":"148","article-title":"GACN: Self-clustering Genetic Algorithm for Constrained Networks[J]","volume":"32","author":"Martins J.A.","year":"2016","unstructured":"MartinsJ.A., MazayevA., CorreiaN. et al., GACN: Self-clustering Genetic Algorithm for Constrained Networks[J], IEEE Communications Letters 32 (2016), 148\u2013155.","journal-title":"IEEE Communications Letters"},{"key":"e_1_3_2_5_2","first-page":"252","article-title":"Cost-Aware Multimedia Data Allocation for Heterogeneous Memory Using Genetic Algorithm in Cloud Computing[J]","volume":"63","author":"Gai K.","year":"2016","unstructured":"GaiK., QiuM., HuiZ. 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