In order to achieve the remote centralized management of the equipment in the wastewater treatment plant, InHand Networks has developed a remote monitoring solution including the InRouter900 IoT gateway and InHand Device Networks Cloud. The complete “Cloud + End” solution enables real-time SCADA system communication and efficient remote plant monitoring & control.
- Remotely monitor the operation status of on-site pumping stations, pipe networks, and wastewater equipment
- Perform centralized operation management with rapid response to pump station and pipe network failures
- Quick Response to onsite failures and efficient maintenance
- Provide a one-stop process for operation and maintenance personnel with real-time status
InHand Remote Monitoring Solution
The remote monitoring system consists of Device Layer and Cloud Layer.
Device Layer: Wastewater treatment station utilizes the PLCs to automatically control and collect data including COD, ammonia nitrogen, hydrogen ion concentration, flow rate, concentration, equipment operation, fault status and etc. InHand InRouter900 edge computing gateway collects field data then uploads to the cloud and SCADA system to achieve real-time PLC data acquisition and operation monitoring.
Cloud Layer: The InRouter900 sends the data to InHand Device Networks Cloud via a secure VPN tunnel. Authorized users can monitor the operation status and receive fault alerts through the Web interface and mobile APP wherever they are. The Device Networks Cloud also enables remote monitoring, management, debugging and preventive maintenance.
- Utilizes Python programming to achieve data analysis and processing: customers can customize the intelligent logic process method, perform local pre-processing and sent data to the cloud server
- Support local cache mechanism to reduce bandwidth costs
- Microsoft Azure IoT certified
- Industrial rugged design, IP30, dual SIM
- Support VRRP and link detection mechanism to ensure redundancy
Device Networks Cloud:
- Utilizes big data analytics capabilities to analyze the health status of different nodes
- Enable pre-fault alerts with machine learning and AI algorithms
- Establish a maintenance process to convert analysis to maintenance tickets
- B/S architecture to support easy access via the Web interface