Ravichandran Mariappan, L. Manjunath, G. Ramachandran, M. Porkodi, T. Sheela
{"title":"具有物联网无线传感器的超级人工智能医疗保健系统","authors":"Ravichandran Mariappan, L. Manjunath, G. Ramachandran, M. Porkodi, T. Sheela","doi":"10.1109/icdcece53908.2022.9792895","DOIUrl":null,"url":null,"abstract":"As well as the design and optimised parameters, will be transmitted for the essential information exchange. This research study focuses on integrating WSN architecture. In actuality, many automated systems still require extensive human engagement; for example, a patient may need to visit multiple pharmacies in order to locate a specific sort of drug. A smart inventory system integrating Wireless Sensor Networks (WSN), Quick Response Codes (QR), and cloud services (Web) would solve numerous difficulties while also saving money for both patients and stakeholders. What we're attempting to figure out with all of these chores is that we need a speedier, more reliable system to manage operational, repeatable processes. Low-power devices are employed at the architectural level so that each component dissipates less power during signal transmission. By optimising load usage in data transmission depending on application-specific demand, significant electricity can be saved. However, in addition to the aforementioned strategies, using a cognitive power management controller can help IoT-enabled systems save even more power, regardless of application.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Super Artificial Intelligence Medical Care Systems with IoT Wireless Sensor\",\"authors\":\"Ravichandran Mariappan, L. Manjunath, G. Ramachandran, M. Porkodi, T. Sheela\",\"doi\":\"10.1109/icdcece53908.2022.9792895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As well as the design and optimised parameters, will be transmitted for the essential information exchange. This research study focuses on integrating WSN architecture. In actuality, many automated systems still require extensive human engagement; for example, a patient may need to visit multiple pharmacies in order to locate a specific sort of drug. A smart inventory system integrating Wireless Sensor Networks (WSN), Quick Response Codes (QR), and cloud services (Web) would solve numerous difficulties while also saving money for both patients and stakeholders. What we're attempting to figure out with all of these chores is that we need a speedier, more reliable system to manage operational, repeatable processes. Low-power devices are employed at the architectural level so that each component dissipates less power during signal transmission. By optimising load usage in data transmission depending on application-specific demand, significant electricity can be saved. However, in addition to the aforementioned strategies, using a cognitive power management controller can help IoT-enabled systems save even more power, regardless of application.\",\"PeriodicalId\":417643,\"journal\":{\"name\":\"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icdcece53908.2022.9792895\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icdcece53908.2022.9792895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Super Artificial Intelligence Medical Care Systems with IoT Wireless Sensor
As well as the design and optimised parameters, will be transmitted for the essential information exchange. This research study focuses on integrating WSN architecture. In actuality, many automated systems still require extensive human engagement; for example, a patient may need to visit multiple pharmacies in order to locate a specific sort of drug. A smart inventory system integrating Wireless Sensor Networks (WSN), Quick Response Codes (QR), and cloud services (Web) would solve numerous difficulties while also saving money for both patients and stakeholders. What we're attempting to figure out with all of these chores is that we need a speedier, more reliable system to manage operational, repeatable processes. Low-power devices are employed at the architectural level so that each component dissipates less power during signal transmission. By optimising load usage in data transmission depending on application-specific demand, significant electricity can be saved. However, in addition to the aforementioned strategies, using a cognitive power management controller can help IoT-enabled systems save even more power, regardless of application.