Monitoring module

Monitoring Module Class
Compact and sturdy, easy to install
Affordable price, high precision
High long-term stability
Wire material: PVC or PTFE
Wide temperature range: -25 to +60℃
Product installation method: Input type
Protection level: IP68
Main Product
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Introduction

Using a photovoltaic power station data collector to collect data from the pump inverter, and upload it to a network server or local computer via GPRS, WIFI, etc., enables users to view relevant data on the Internet or local computer, facilitating the management of power station personnel and users to view and manage the operation data of the photovoltaic power plant. It allows people to monitor and manage the cluster without the need to physically inspect the status of each pump inverter. It is more conducive to data collection, curve generation, and data analysis. Network monitoring facilitates remote management, saving labor costs

Highlights

compact design

remote communication

Auto Run

Introduction

Specifications
  • Wifi 监控 & GPRS Plug


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    Using photovoltaic power station data collectors to gather data from water pump inverters, and then uploading it to network servers or local computers via GPRS, WIFI, etc., enables users to view relevant data on the Internet or local computers, facilitating the management and users of the power station to view and manage the operational data of the photovoltaic power plant.


    It allows people to monitor and manage the cluster without having to physically check the status of each pump inverter. It facilitates data collection, curve generation, and data analysis. Network monitoring makes remote management more convenient for people, saving labor costs


    Solar water pump systems are generally located in remote areas, making on-site inspection inconvenient. Therefore, photovoltaic monitoring helps people to detect and solve problems in a timely manner. Especially for remote network monitoring, management personnel can be notified via mobile phones, emails, etc., to identify issues in the first place and determine the cause of the problem by remotely viewing data.


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