Abstract
The work emphasizes the importance of maintaining a consistent temperature while transporting temperature-sensitive goods in the logistics cold chain. Refrigerated transportation plays a critical role in this chain, and the safe and efficient transport of perishable goods, such as food or pharmaceuticals, heavily relies on maintaining appropriate temperature levels. Real-time temperature monitoring and timely response to deviations are vital to prevent spoilage and financial losses. This paper presents an intelligent temperature monitoring system that employs a WiFi-enabled IoT platform NodeMCU-ESP32 to collect real-time temperature data, which is then transmitted to the AWS cloud platform. The system uses machine learning algorithms to predict temperature deviations and sends alerts to relevant stakeholders via the Telegram messaging service. The system architecture comprises AWS services, including API Gateway, IAM, Lambda, DynamoDB, and SNS, offering a scalable, secure, and cost-effective temperature monitoring solution.
Publisher
Lviv Polytechnic National University
Subject
Industrial and Manufacturing Engineering,Metals and Alloys,Strategy and Management,Mechanical Engineering
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