Spatio-Temporal Optimization of Perishable Goods' Shelf Life by a Pro-Active WSN-Based Architecture

Area of Science:

• Agricultural Engineering
• Supply Chain Management
• Food Science
• Internet of Things (IoT)

Background:

• Perishable goods supply chains face significant waste, prompting global organizations to develop protocols like Hazard Analysis and Critical Control Points (HACCP).
• Effective warehouse management is crucial for extending the shelf life of perishable products.
• Advances in wireless sensor network (WSN) technology enable "smart" storage solutions for improved management.

Purpose of the Study:

• To propose a low-cost, reprogrammable WSN-based architecture for functional warehouse management of perishable goods.
• To continuously monitor environmental parameters (temperature, humidity, light) for real-time shelf-life prediction.
• To optimize product placement within the warehouse to maximize expiration dates using a "first-expired first-out" strategy.

Main Methods:

• Implementation of a WSN architecture for continuous environmental monitoring.
• Utilizing a 1st order kinetic Arrhenius model to compute product quality decay and predict shelf life.
• Employing a Raspberry Pi-based central unit to manage automated pallet transporters for product relocation based on shelf life.

Main Results:

• The proposed WSN system demonstrated an improvement in the expected expiration date of approximately 1.2 ± 0.5 days per pallet in non-refrigerated environments.
• The system effectively integrates commercial sensors and communication interfaces (ZigBee, Bluetooth, HTTP).
• User interfaces were developed to detect critical situations, enabling timely automated or human interventions.

Conclusions:

• The developed WSN-based architecture offers a proactive and versatile solution for optimizing perishable goods storage.
• This smart storage approach significantly reduces waste and enhances food quality throughout the supply chain.
• The system's adaptability and user-friendly interfaces support efficient warehouse management and minimize product loss.