The paper presents an optimization algorithm applied to a cloud-driven controller for wireless sensors in Internet of Things (IoT) devices. The experiment investigates operational duty cycle control and energy managem...
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The paper presents an optimization algorithm applied to a cloud-driven controller for wireless sensors in Internet of Things (IoT) devices. The experiment investigates operational duty cycle control and energy management of a wireless sensor node device powered by prediction from global solar irradiance in the environment. Rapid increases in the development and growth of smart technologies is placing greater demands on optimizing computing power. The study attempted to manage and optimize wireless terminals using methods to adjust work cycles and planning. The study's contribution is a simulated wireless environmental IoT sensor node and cloud controller implemented in Matlab. The simulation examined energy management and optimization, supplemented by prediction from data measured at different locations in the period 2016-2019. The experiment investigated suitable modes of operation of the device according to data updates in the cloud. The controller was based on the following parameters: state of energy storage, number of failures relative to correctly performed device cycles, and predicted values for charging energy storage from the cloud.
The paper presents an optimization algorithm applied to a cloud-driven controller for wireless sensors in Internet of Things (IoT) devices. The experiment investigates operational duty cycle control and energy managem...
详细信息
The paper presents an optimization algorithm applied to a cloud-driven controller for wireless sensors in Internet of Things (IoT) devices. The experiment investigates operational duty cycle control and energy management of a wireless sensor node device powered by prediction from global solar irradiance in the environment. Rapid increases in the development and growth of smart technologies is placing greater demands on optimizing computing power. The study attempted to manage and optimize wireless terminals using methods to adjust work cycles and planning. The study's contribution is a simulated wireless environmental IoT sensor node and cloud controller implemented in Matlab. The simulation examined energy management and optimization, supplemented by prediction from data measured at different locations in the period 2016–2019. The experiment investigated suitable modes of operation of the device according to data updates in the cloud. The controller was based on the following parameters: state of energy storage, number of failures relative to correctly performed device cycles, and predicted values for charging energy storage from the cloud.
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