Retail and Food Equipment

IoT Sensor Applications For Retail Equipment

Equipment Monitoring

Monitoring critical equipment for status looking at vibration, temperature, noise and leaks.

Food Preparation Equipment

Vibration, temperature, noise and leaks, leak detection and other sensors are installed. Out of limit sensor reading trigger a message to service personnel.

Product Storage

Monitor the storage of product being used for temperature and container status. This information can be recorded and sent wirelessly for review and analysis.

The Solution: Food Service Machinery Condition Monitoring & Quality Assurance

This solution allows Food Service Equipment owners the ability to remotely monitor equipment uptime, product deliver counts, replenishment needs and even cleaning cycles. EP Connect sensor modules can collect and relay vital equipment operating parameters and alert management via text, email or cloud data when abnormal operating conditions arise.

Benefits
  • Better system optimization
  • Scheduled maintenance
  • Longer system usage
  • Minimize downtime
Target Application
  • Food Service Preparation
  • Food Warehousing
  • Cold Chain Monitoring
  • Transportation

Embedded Planet epSensors: Sensors include Air Quality, temperature, proximity, position, moisture, flow, fluid leaks and vibration.

Embedded Planet epGateway™: Sensors connect directly to the Embedded Planet epGateway. The epGateway serves as a sensor hub for both wired and wireless sensors including epSensors. The epGateway can send data to Microsoft Azure, IBM Cloud and Amazon AWS. It also provides remote device management in a secure multi-tenant environment.

epCloud: Sensor data is sent to Microsoft Azure, IBM Cloud and Amazon AWS. Device management is performed via epCloud and can securely update device firmware and manage the system remotely. Data rendered into visualization dashboards which use rules to notify maintenance personnel via texts or push the data to tools for automatic work order creation. Data is stored in a cloud-based database for longer term historical analysis which is required for predictive analytics.

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