cargo_guardian

AG-4: Supply Chain Spoilage Risk Predictor for Perishables is an intelligent decision-support system designed to reduce post-harvest losses of fruits and vegetables across the supply chain. In traditional agri-logistics, spoilage often occurs due to transportation delays, exposure to high temperatures, improper handling, and the absence of real-time risk monitoring. These factors lead to significant food waste and financial losses for farmers, distributors, and retailers.

The proposed system addresses this problem by predicting spoilage risk at different stages of the supply chain using data-driven analysis. It takes key inputs such as transit time, distance traveled, temperature proxies (derived from weather data), and handling stages like harvesting, storage, transportation, and distribution. By continuously evaluating these parameters, the system generates a dynamic spoilage risk score that indicates the likelihood of product degradation.

Based on the calculated risk score, the system provides preventive actions, such as recommending faster routes, improved storage conditions, cold-chain usage, or priority delivery for high-risk consignments. Additionally, it defines escalation triggers that alert stakeholders when risk crosses a critical threshold, enabling timely intervention before spoilage occurs.

The solution can be implemented using APIs for weather and distance estimation, combined with a simple risk prediction model on the backend. A user-friendly dashboard displays risk levels, alerts, and recommended actions in real time.

From a real-world perspective, this system helps reduce food wastage, improves supply chain efficiency, and increases profitability for agricultural stakeholders. It also supports sustainability goals by minimizing losses and ensuring fresher produce reaches consumers, making it a practical and impactful AgriTech innovation.

https://cargo-guardian.vercel.app/

https://github.com/wasrick321/cargo-guardian.git