Via the IoT Hub Console, attribute information such as device name, device scenario, device model and others are added, quickly completing registration of a single or a batch of devices
Once the device is connected, device status information can be obtained in real time
Customize products or create products by presetting template.
Set the verification method for all devices under the products. Including: Close dynamic registration (adopt one-machine-one-secret verification for all devices), and enable dynamic registration (adopt one-machine-one-password verification for all devices)
Report the device data through the Thing Model to the cloud, and search the device data at any time
The functional descriptions of devices on the cloud, through unified Thing Model definition and standard data, support definitions covering device attribute, event and service and simplify application development on devices and the cloud
The packet streaming data of device uplink is an observation value describing objective facts, which cannot be modified by the Cloud Service or other applications.
Compared with packet data, the device status data, such as running status of device, device version number and sending frequency of device packet data, is updated with lower frequency. The status property can be modified by the Cloud Service or other applications.
The control instructions of devices positively called by the Cloud Service or other applications or triggered by a rule in the rule engine will not modify the device status property. For example, the message broadcast instruction of all devices.
Pre-process device data received by IoT Hub, set conditions as per prescribed business rule, quickly pre-process device data received by IoT Hub, forward and dump processed data to other service of JD Cloud, such as RDS, JCQ, ES, etc.
After the cloud onboarding of device data, customers can configure the rule engine of the IoT Hub so as to store the device data to the storage service, e.g. Database RDS instance or ES instance; final customers can integrate their applications, such as machine learning, AI application, to achieve business objectives such as intelligent device management and predictive maintenance.
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