An Efficient Route Predictor and Cold Chain Analytics System For Logistics Operation

The logistics and transportation industries in cold chain systems are critical to the growth and development of economies. However, the industry's current predominant use of manual processes is fraught with problems, such as limited transparency, inefficient route determination, poor supply planning, and quality assurance of product. The adoption of sensor, GPS and WI-FI positioning technologies and effective analytical applications for tracking the essential parameters of the product, determining the product's real-time location in transit and analyzing the collected data can address these problems.This paper is aimed at the development of a cold chain analytics system that provides the real-time location coordinates and essential parameters of the perishable and fragile product in transit with the possible shortest route for the driver through a user-friendly interface that addresses these manual processes. It employs bimodal location tracking and incorporates a robust quality prediction algorithm for product analytics. The prototype efficiently leverages Wi-Fi positioning for location tracking, integrates essential product quality parameters, provides the shortest route and real time messaging resulting in improved supply chain planning and quality assurance for logistics operations. The completion of the cold chain analytics system demonstrates the viability of a solution that offers real-time product and location tracking, significantly improving logistics operations and transparency