IOT News

Industry Background

As important earthmoving machinery, electric loaders are widely used in highway, railway, construction, hydropower, port, and mining projects. As enterprises raise both cost-control requirements and after-sales service standards, traditional electric loader management approaches are facing growing challenges—such as difficulty obtaining real-time equipment operating data, delayed fault diagnosis, and high maintenance costs. These issues seriously affect production efficiency and management standards.

Solution Overview

To address this, WideIOT offers an IoT remote monitoring system solution for electric loaders. By connecting industrial smart gateways to the electric loader's generator set controller, GPS, sensors, and other devices, the system collects real-time information on equipment operating status, location distribution, and process parameters, and uploads it via 5G/4G wireless networks to a monitoring and maintenance platform—enabling remote monitoring, fault early warning, maintenance management, and data analytics for distributed equipment.

Functions

Data Acquisition – Collects various real-time operating data from electric loaders—such as oil pressure, voltage, current, operating hours, and location distribution—and uploads it to the remote monitoring platform.

Remote Monitoring – Through the monitoring platform, users can view the electric loader's operating status and process parameters in real time, and use the electronic map to understand equipment distribution, quantity, and types.

Fault Early Warning – With configurable alarm thresholds, the system can promptly detect hidden fault risks and send notifications via WeChat, SMS, or email—enabling rapid localization, diagnosis, and corrective action.

Maintenance Management – Enables assignment, management, and querying of maintenance work, providing maintenance personnel with a scientific management basis—improving maintenance efficiency and reducing maintenance costs.

Remote Maintenance – Supports remote PLC programming, debugging, and program upload/download for off-site equipment—reducing travel frequency and expenses.
Data Analytics – Through equipment maps and data dashboards, users can understand equipment quantity, distribution, types, and alarm and maintenance information—summarizing experience and supporting scientific decision-making.