The scope of securing equipment status data, a prerequisite for AI predictive maintenance, is expanding beyond fixed facilities to include moving vehicles on the road. Monnit Korea, a specialist in industrial wireless IoT sensors, is extending the application of its wireless measurement solutions to the transportation industry and is setting out to establish a real-time data collection system for mobile equipment.


Monnet Korea announced on the 10th that it is expanding its AI predictive maintenance wireless measurement solution, which has been applied to existing logistics, food manufacturing, and chemical plant sectors, to the entire transportation industry.

The expanded scope includes livestock transport vehicles, refrigerated agricultural transport vehicles, hazardous materials tank trucks, and general cargo and container transport vehicles.

The company explained that it configured the solution to enable real-time data transmission even while the vehicle is in motion by utilizing a mobile communication-linked gateway.

In the logistics and warehousing sector, there is a structural risk where the shutdown of critical equipment, such as conveyors, stacker cranes, and refrigeration compressors, leads to delays in the overall logistics flow.

Monnet Korea [provides] △torque of forklift and automated guided vehicle (AGV) drive motors and It was stated that data on load rate, stacker crane wire tension and vibration, pallet rack strain, and refrigeration/freezing compressor overload can be collected at all times using wireless sensors.

Considering that maintaining wired measurements is difficult in the food manufacturing sector due to high temperature and humidity environments and the characteristics of repetitive washing processes, the system is configured to continuously measure the torque of mixer and dough mixer stirring motors, the load rate of drive parts of fillers and packaging machines, and the structural deformation rate of sterilization equipment using dustproof and waterproof wireless sensors.

In the fields of chemical plants and structural infrastructure, it is applied in a way that continuously collects data on compressor load, pump vibration, pipe strain, and structural displacement without additional instrumentation work during operation, thereby reducing the gap between regular inspections.

This wireless measurement system is compatible with sensors widely used in industrial settings, such as load cells, torque sensors, pressure sensors, and displacement transducers.

The company stated that it supports 1/4, 1/2, and full bridge structures, enabling wireless connectivity without replacing existing sensor assets.

Technical specifications include 24-bit precision measurement, frequency hopping wireless communication, dust and water resistance rating (IP65), military-grade data encryption, and long-term battery operation.

It was announced that the collected data is integrated with Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP), Supervisory and Data Acquisition (SCADA), and PLCs through the Monit Edge Gateway, and is directly transmitted to the AI learning environment.

Yeom Jeong-hoon, CEO of Monnet Korea, stated, “Many companies talk about adopting AI, but in most cases, there is actually no data to train on,” adding, “From the moment sensors are installed, the history of equipment status accumulates, and that data forms the basis for AI predictive maintenance one year later.”"It becomes," he said.