Science and Technology

Automated farm-to-shop freight quality assurance system

freight quality assurance system

This PhD project aims to develop an end-to-end quality monitoring and assurance system based on a wide area IoT (Internet of Things) network architecture.

The focus will be on the cradle-to-gate freight delivery of perishable cargo from farms to shops.

It will develop an automated system to

  • monitor the quality of products in the freight system, and
  • maintain the product quality by taking necessary actions based on the real-time quality data obtained from the freight containers.

The project approach will be based on the following automated actions:

  1. Sense: Environmental variables in which the goods are stored will be measured in real time
  2. Monitor: This measured data will be sent to a server (or distributed servers) for monitoring
  3. Control: Actions will be taken if the environmental variables fall out of their expected ranges

While actions 1 and 2 monitor the conditions of the goods, action 3 assures the quality of them. These actions rely on communications of data among different devices, and as such they will be implemented on an IoT infrastructure.

Participants

Project background

Delivery of perishable goods is subject to stringent requirements. Not only does the end-to-end delivery duration need to be met, the environments in which the goods are delivered throughout the transport chain must be tightly controlled and monitored.

This project aims to develop an end-to-end freight quality monitoring and assurance system based on an IoT network architecture, focussing on the cradle-to-gate freight delivery of perishable cargo from farms to shops.

See the full list of iMOVE projects here

It will study the fresh food supply chain management system to develop fresh food delivery and quality assurance techniques. Additionally, it will result in the design and development of a sensor-based monitoring system which can be utilised in the fresh food supply chain vehicles to obtain real-time status of food in transit.

A cloud-based intelligent system will be used that will generate a freshness index to manage the food delivery process, and a prototype system will be developed for laboratory experiments. The research work will develop algorithms and a prototype system for field implementation.

Project objectives

  • Study fresh food delivery requirements, standards and management systems
  • Develop logistic quality monitoring specification
  • Design and develop algorithms and sensing techniques to implement the monitoring specification
  • Design and develop a smart food quality IoT-based sensing system
  • Develop food quality fresh index and validate the data using food laboratory experiments
  • Develop simulation models to analyse performance of developed algorithms and IoT sensing systems

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