Abstract: Cold storage facilities play a critical role in preserving perishable goods, such as food and pharmaceuticals. However, ensuring optimal storage conditions, such as maintaining precise temperatures and humidity levels, is essential to prevent spoilage and maintain product quality. Traditional monitoring systems often lack real-time capabilities and intelligent decision-making, leading to inefficiencies and potential losses.In response to these challenges, this paper proposes an innovative IoT-based real-time intelligent monitoring and notification system for cold storage facilities. The system integrates various IoT sensors to continuously collect data on temperature, humidity, and other relevant parameters within the storage environment. These sensors transmit data to a central hub, where it is processed and analyzed using advanced algorithms and machine learning techniques.The intelligent system is capable of monitoring the storage conditions in real-time, identifying deviations from optimal parameters, and generating timely notifications/alerts to relevant stakeholders, such as facility managers or maintenance personnel. Moreover, the system employs predictive analytics to anticipate potential issues and recommend proactive measures to mitigate risks, thereby minimizing product losses and ensuring regulatory compliance.
Keywords:Temperature,Humidity,Light Intensity,Sensors,Random Forest.
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DOI:
10.17148/IJARCCE.2024.13382
