Why is edge computing needed?
First, many industries have strict requirements for real-time performance and reliability. For example, when fire alarm equipment detects a fire, if the data is transmitted to the cloud and then the cloud issues a command to open the fire hydrant, network latency and other factors may cause delays. In this case, edge computing is needed to handle the situation in a timely manner.
Second, fully utilize the CPU computing power of edge devices to reduce the computing power requirements and hardware costs of cloud servers. Devices perform reasonable preprocessing of data to ensure optimal use and avoid resource waste. Therefore, edge computing services should be provided locally.
Cloud platform support for edge computing
ZWS Cloud Platform is a general-purpose IoT cloud platform developed by ZLG Zhiyuan Electronics. It enables remote management, remote operation and maintenance, and data monitoring of IoT devices. It also supports edge computing, primarily providing edge computing services to devices in three aspects: data parsing, alarm triggering, and scheduled tasks. 1. Data Parsing: Data parsing transforms raw data into recognizable JSON data. Parsing can be performed in the cloud or at the edge. After configuring parsing rules and sending them to the devices, the devices can automatically parse the data and report it to the cloud, reducing the need to send large amounts of data processing requests to the central processing unit.
2. Alarm Trigger
Alarm triggering occurs when monitoring device data; any abnormal data will trigger an alarm event. For example, abnormal data such as excessively high temperature, overvoltage, or undervoltage will trigger an alarm event, notifying personnel to handle the situation. Alarms can be sent from the cloud or alarm rules can be distributed to devices for edge alarm implementation, reducing latency.
3. Scheduled tasks
Scheduled tasks are commands that devices need to execute at regular intervals in certain scenarios. Examples include a master device periodically sending instructions to a slave device, or a lighting device being scheduled to automatically turn off at 6:30 PM every day. Scheduled tasks can be executed in the cloud or distributed to devices for edge execution, reducing costs and increasing efficiency.
