The Corona Virus Disease 2019(COVID-19) pandemic has taught us many valuable lessons regarding the importance of our physical and mental health. Even with so many technological advancements, we still lag in developing...The Corona Virus Disease 2019(COVID-19) pandemic has taught us many valuable lessons regarding the importance of our physical and mental health. Even with so many technological advancements, we still lag in developing a system that can fully digitalize the medical data of each individual and make it readily accessible for both the patient and health worker at any point in time. Moreover, there are also no ways for the government to identify the legitimacy of a particular clinic. This study merges modern technology with traditional approaches,thereby highlighting a scenario where artificial intelligence(AI) merges with traditional Chinese medicine(TCM), proposing a way to advance the conventional approaches. The main objective of our research is to provide a one-stop platform for the government, doctors,nurses, and patients to access their data effortlessly. The proposed portal will also check the doctors’ authenticity. Data is one of the most critical assets of an organization, so a breach of data can risk users’ lives. Data security is of primary importance and must be prioritized. The proposed methodology is based on cloud computing technology which assures the security of the data and avoids any kind of breach. The study also accounts for the difficulties encountered in creating such an infrastructure in the cloud and overcomes the hurdles faced during the project, keeping enough room for possible future innovations. To summarize, this study focuses on the digitalization of medical data and suggests some possible ways to achieve it. Moreover, it also focuses on some related aspects like security and potential digitalization difficulties.展开更多
近年来,我国支持发展万头规模羊场,在全行业的共同努力下,我国畜禽标准化规模化养殖发展迅速,涌现一批大型现代化养殖企业,新品种、新技术及新设备推广应用加快,生产机械化、信息化及智能化水平不断提高。根据羊业集约化养殖现状,团队...近年来,我国支持发展万头规模羊场,在全行业的共同努力下,我国畜禽标准化规模化养殖发展迅速,涌现一批大型现代化养殖企业,新品种、新技术及新设备推广应用加快,生产机械化、信息化及智能化水平不断提高。根据羊业集约化养殖现状,团队建立“吉羊”智慧养殖管控系统,并在示范场完成系统开发及应用测试。系统主要通过搭建人工智能物联网AIoT(artificial intelligence&Internet of Things)平台,实现羊只数据的共享与传输,实现物联网数据一体化,提高羊场饲养管理水平;通过采集环控环境数据实现智能控制,明确饮水、用电、用料量,准确采集生产数据,掌握生产成本,能耗数据实时准确采集,达到增产增效的目的;通过卷积算法和深度学习技术深度开发AI(artificial intelligence)盘点技术,提高饲养管理效率,进一步实现疾病诊断及溯源管理。本研究对该平台进行系统的应用测试,对主要的饲养管理功能及AI盘点功能进行数据检测,结果发现饲养管理功能数据传输准确、管理功能均可实现,AI盘点功能准确率远超预期,达到98%。该平台的开发利用将数字化管理系统引入羊场,为提高养羊业的集约化生产水平奠定基础。展开更多
As the profundity of open-pit mining operations has increased,so has the frequency of geological disasters.The complex interaction of factors causing these disasters presents technical challenges for early warning and...As the profundity of open-pit mining operations has increased,so has the frequency of geological disasters.The complex interaction of factors causing these disasters presents technical challenges for early warning and control systems.However,emergent technologies such as the internet,5G networks,and artificial intelligence provide new opportunities for constructing integrated digital early warning platforms that synthesise multifaceted monitoring data to predict and mitigate open-pit mine hazards.Using efficient Internet-mediated information integration,data from various sources can be consolidated for enhanced disaster management.This paper reviews the current state of digital early warning platforms for open-pit mines using a Web of Science database search for pertinent literature.The framework,data layer,technology layer,and application layer of these platforms are investigated in order to identify associated technologies and obstacles.Important results include:(1)Inconsistent data formats and monitoring software diminish platform workflow efficiency.Robust data exchange protocols and feature-rich software could increase efficiency.(2)Platforms rely on limited data types as opposed to intelligent algorithms that integrate diverse monitoring inputs into global disaster predictions.The underutilization of advanced technologies such as artificial intelligence,the internet of things,and cloud computing.Mining calamity mechanisms and rock mechanics require additional study.展开更多
文摘The Corona Virus Disease 2019(COVID-19) pandemic has taught us many valuable lessons regarding the importance of our physical and mental health. Even with so many technological advancements, we still lag in developing a system that can fully digitalize the medical data of each individual and make it readily accessible for both the patient and health worker at any point in time. Moreover, there are also no ways for the government to identify the legitimacy of a particular clinic. This study merges modern technology with traditional approaches,thereby highlighting a scenario where artificial intelligence(AI) merges with traditional Chinese medicine(TCM), proposing a way to advance the conventional approaches. The main objective of our research is to provide a one-stop platform for the government, doctors,nurses, and patients to access their data effortlessly. The proposed portal will also check the doctors’ authenticity. Data is one of the most critical assets of an organization, so a breach of data can risk users’ lives. Data security is of primary importance and must be prioritized. The proposed methodology is based on cloud computing technology which assures the security of the data and avoids any kind of breach. The study also accounts for the difficulties encountered in creating such an infrastructure in the cloud and overcomes the hurdles faced during the project, keeping enough room for possible future innovations. To summarize, this study focuses on the digitalization of medical data and suggests some possible ways to achieve it. Moreover, it also focuses on some related aspects like security and potential digitalization difficulties.
文摘近年来,我国支持发展万头规模羊场,在全行业的共同努力下,我国畜禽标准化规模化养殖发展迅速,涌现一批大型现代化养殖企业,新品种、新技术及新设备推广应用加快,生产机械化、信息化及智能化水平不断提高。根据羊业集约化养殖现状,团队建立“吉羊”智慧养殖管控系统,并在示范场完成系统开发及应用测试。系统主要通过搭建人工智能物联网AIoT(artificial intelligence&Internet of Things)平台,实现羊只数据的共享与传输,实现物联网数据一体化,提高羊场饲养管理水平;通过采集环控环境数据实现智能控制,明确饮水、用电、用料量,准确采集生产数据,掌握生产成本,能耗数据实时准确采集,达到增产增效的目的;通过卷积算法和深度学习技术深度开发AI(artificial intelligence)盘点技术,提高饲养管理效率,进一步实现疾病诊断及溯源管理。本研究对该平台进行系统的应用测试,对主要的饲养管理功能及AI盘点功能进行数据检测,结果发现饲养管理功能数据传输准确、管理功能均可实现,AI盘点功能准确率远超预期,达到98%。该平台的开发利用将数字化管理系统引入羊场,为提高养羊业的集约化生产水平奠定基础。
基金supported by the National Natural Science Foundation of China(No.52178393,No.51578447)the Science and Technology Innovation Team of Shaanxi Innovation Capability Support Plan(No.2020TD005)the Special Project of Shaanxi Provincial Education Department(No.20JK0709).
文摘As the profundity of open-pit mining operations has increased,so has the frequency of geological disasters.The complex interaction of factors causing these disasters presents technical challenges for early warning and control systems.However,emergent technologies such as the internet,5G networks,and artificial intelligence provide new opportunities for constructing integrated digital early warning platforms that synthesise multifaceted monitoring data to predict and mitigate open-pit mine hazards.Using efficient Internet-mediated information integration,data from various sources can be consolidated for enhanced disaster management.This paper reviews the current state of digital early warning platforms for open-pit mines using a Web of Science database search for pertinent literature.The framework,data layer,technology layer,and application layer of these platforms are investigated in order to identify associated technologies and obstacles.Important results include:(1)Inconsistent data formats and monitoring software diminish platform workflow efficiency.Robust data exchange protocols and feature-rich software could increase efficiency.(2)Platforms rely on limited data types as opposed to intelligent algorithms that integrate diverse monitoring inputs into global disaster predictions.The underutilization of advanced technologies such as artificial intelligence,the internet of things,and cloud computing.Mining calamity mechanisms and rock mechanics require additional study.
