20240036539. Asset Management and IOT Device for Refrigerated Appliances simplified abstract (True Manufacturing Co., Inc.)
Asset Management and IOT Device for Refrigerated Appliances
Organization Name
Inventor(s)
Dominik Gothe of O'Fallon MO (US)
Asset Management and IOT Device for Refrigerated Appliances - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240036539 titled 'Asset Management and IOT Device for Refrigerated Appliances
Simplified Explanation
The abstract of the patent application describes an asset management system that connects various types of refrigeration appliances to an asset manager through an asset management network. The system includes IoT devices at the device layer, which are connected to the refrigeration appliances and have edge compute capability, backup power management function, and a modem for network communication. The IoT devices integrate with sensors, switches, and/or serial data controllers of the refrigeration appliances, and initiate push notification alarms on the edge of the network. The operating data of the appliances is tagged by appliance serial number and stored by the asset manager using serial numbers as primary keys. The asset manager streams data from multiple appliances and uses event-driven processing to promptly respond to edge alarms. The operating data, enriched with proprietary data organized by appliance type, is used to develop new predictive models.
- The asset management system connects refrigeration appliances to an asset manager through an asset management network.
- IoT devices at the device layer are connected to the refrigeration appliances and have edge compute capability, backup power management function, and a modem for network communication.
- IoT devices integrate with sensors, switches, and/or serial data controllers of the refrigeration appliances.
- Push notification alarms are initiated on the edge of the network by the IoT devices.
- The operating data of the appliances is tagged and stored by the asset manager using serial numbers as primary keys.
- The asset manager streams data from multiple appliances and uses event-driven processing to respond to edge alarms.
- The operating data is enriched with proprietary data organized by appliance type.
- The enriched data is used to develop new predictive models by appliance type.
Potential Applications
- Asset management and monitoring of refrigeration appliances in various industries such as food and beverage, pharmaceuticals, and logistics.
- Predictive maintenance and fault detection for refrigeration appliances.
- Energy optimization and efficiency improvement for refrigeration systems.
Problems Solved
- Lack of centralized asset management and monitoring for refrigeration appliances.
- Inefficient maintenance practices and reactive repairs.
- Limited visibility into the performance and health of refrigeration systems.
Benefits
- Improved asset management and monitoring efficiency.
- Early detection of faults and proactive maintenance.
- Enhanced energy optimization and cost savings.
- Development of predictive models for better performance and reliability.
Original Abstract Submitted
an asset management system includes an asset management network that connects various types of refrigeration appliances to an asset manager. at the device layer, iot devices are connected to the refrigeration appliances and have edge compute capability, including a backup power management function, and a modem for network communication. iot device ports directly integrate with sensors, switches, and/or serial data controllers of refrigeration appliances. push notification alarms are initiated on the edge of the network by iot devices. the network tags operating data by appliance serial, and the asset manager stores the data using serial numbers as primary keys. the asset manager streams data from numerous appliances and uses event driven processing to promptly respond to edge alarms. the operating data keyed by serial number is enriched with proprietary data organized by appliance type and is used to develop new predictive models by appliance type.
