基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution an...基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution and knowledge base,MAPE-K)模型思想,将IoT对象实例生命周期的行为状态与微流程实例状态一一映射,实现对单个IoT对象的环形自动监控和调节;其次,基于从IoT传感设备获取的数据,定义基于SASE+语言的业务规则,提取对业务流程有意义的业务事件,避免了无关事件对宏流程的干扰;最后,通过设计一个微流程建模工具原型系统,结合真实案例分析,验证了提出建模方法的有效性,实现了业务流程与IoT实时流式感知数据的结合,并显著减少了宏流程需要处理的业务事件数量。展开更多
Considering the quality of life, manpower, and expenditure, an IoT-based health monitoring system has been proposed and implemented. Devices are placed on the human body to collect data, which is then uploaded to an o...Considering the quality of life, manpower, and expenditure, an IoT-based health monitoring system has been proposed and implemented. Devices are placed on the human body to collect data, which is then uploaded to an online data server. Specialist doctors can access this data as needed, allowing them to assess the patient’s initial condition and provide advice at any time. This approach enhances the quality and reach of health services. The module, designed and installed using modern technology, minimizes latency and maximizes data accuracy while reducing delay and battery drain. An accompanying app motivates public acceptance and ease of use. Various sensors, including ECG, SpO2, gyroscope, PIR, temperature-humidity, and BP, collect data processed by an Arduino microcontroller. Data transmission is handled by a WiFi module, with ThingSpeak and Google Sheets used for data processing and storage. The system has been fully tested, and patient data from two hospitals compared with the proposed model shows 97% accuracy.展开更多
The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to pred...The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults.This technique identifies the faulty sensor and determines the correct working of the sensor.Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described.There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique.So,some solutions are provided to overcome the limitations of the fall curve technique.In this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years.Its novelty is to predict a fault before its occurrence by looking at the fall curve.The sensing of current flow in devices is important to prevent a major loss.So,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices.The analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to zero.Various evaluation metrics for fault prediction are also described in this paper.At last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.展开更多
结合自动化技术、嵌入式技术、物联网技术,设计一套基于阿里云IoT平台的气雾栽培式家庭植物工厂控制系统,该系统采用触摸屏PLC一体机为主控制器,通过网关模块接入阿里云IoT平台,并采用IoT Studio Web可视化开发工具进行手机端应用软件设...结合自动化技术、嵌入式技术、物联网技术,设计一套基于阿里云IoT平台的气雾栽培式家庭植物工厂控制系统,该系统采用触摸屏PLC一体机为主控制器,通过网关模块接入阿里云IoT平台,并采用IoT Studio Web可视化开发工具进行手机端应用软件设计,可实现对家庭植物工厂的远程监控,满足实际应用需求,使用户获得良好的应用体验。展开更多
文摘基于物联大数据赋能的业务流程能够更快更准地感知物理世界并及时做出响应的需求突现,提出一种物联网(Internet of Things,IoT)感知的业务微流程建模方法。首先,以单个IoT对象为中心建模,融合MAPE-K(monitor,analysis,plan,execution and knowledge base,MAPE-K)模型思想,将IoT对象实例生命周期的行为状态与微流程实例状态一一映射,实现对单个IoT对象的环形自动监控和调节;其次,基于从IoT传感设备获取的数据,定义基于SASE+语言的业务规则,提取对业务流程有意义的业务事件,避免了无关事件对宏流程的干扰;最后,通过设计一个微流程建模工具原型系统,结合真实案例分析,验证了提出建模方法的有效性,实现了业务流程与IoT实时流式感知数据的结合,并显著减少了宏流程需要处理的业务事件数量。
文摘Considering the quality of life, manpower, and expenditure, an IoT-based health monitoring system has been proposed and implemented. Devices are placed on the human body to collect data, which is then uploaded to an online data server. Specialist doctors can access this data as needed, allowing them to assess the patient’s initial condition and provide advice at any time. This approach enhances the quality and reach of health services. The module, designed and installed using modern technology, minimizes latency and maximizes data accuracy while reducing delay and battery drain. An accompanying app motivates public acceptance and ease of use. Various sensors, including ECG, SpO2, gyroscope, PIR, temperature-humidity, and BP, collect data processed by an Arduino microcontroller. Data transmission is handled by a WiFi module, with ThingSpeak and Google Sheets used for data processing and storage. The system has been fully tested, and patient data from two hospitals compared with the proposed model shows 97% accuracy.
基金supported by Taif University Researchers supporting Project number(TURSP-2020/347),Taif University,Taif,Saudi Arabia.
文摘The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults.This technique identifies the faulty sensor and determines the correct working of the sensor.Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described.There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique.So,some solutions are provided to overcome the limitations of the fall curve technique.In this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years.Its novelty is to predict a fault before its occurrence by looking at the fall curve.The sensing of current flow in devices is important to prevent a major loss.So,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices.The analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to zero.Various evaluation metrics for fault prediction are also described in this paper.At last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.
文摘结合自动化技术、嵌入式技术、物联网技术,设计一套基于阿里云IoT平台的气雾栽培式家庭植物工厂控制系统,该系统采用触摸屏PLC一体机为主控制器,通过网关模块接入阿里云IoT平台,并采用IoT Studio Web可视化开发工具进行手机端应用软件设计,可实现对家庭植物工厂的远程监控,满足实际应用需求,使用户获得良好的应用体验。
