Systems and methods for smart temperature control devices
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Solution Overview
Problem
Existing temperature control devices lack the ability to effectively monitor and adjust to temperature fluctuations, leading to potential product spoilage and false alarms due to inadequate parameter settings.
Innovation Solution
A smart temperature control system that utilizes historical data to set and update setpoints, reducing false alarms and ensuring timely notifications of actual abnormalities by determining operating parameters based on temperature cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional temperature control devices use fixed threshold alarms, then the alarm system is simple to implement, but it generates false alarms and cannot adapt to temperature fluctuations
Solution Approach 1:
The system performs preliminary learning of temperature cycles during an initial period to establish baseline patterns before normal monitoring begins. This preliminary action allows the system to adapt to the specific container and environmental conditions, reducing false alarms while maintaining simplicity.
Solution Approach 2:
The system continuously monitors temperature data and uses feedback from historical temperature cycles to dynamically adjust alarm thresholds. The alarm system learns from past temperature patterns and adapts its sensitivity, eliminating false alarms while accounting for normal temperature fluctuations.
2Measurement precision
If the system monitors temperature continuously with strict thresholds, then temperature control accuracy is improved, but false alarms increase due to normal temperature cycles
Solution Approach 1:
The system transitions from static fixed thresholds to dynamic adaptive thresholds that change based on learned temperature patterns. The alarm thresholds are no longer fixed but adapt to the container's specific temperature cycles, allowing continuous monitoring without false alarms.
Solution Approach 2:
The system changes the alarm threshold parameter dynamically based on historical temperature data. Instead of using a single fixed threshold, the threshold adapts to account for normal temperature variations, maintaining measurement precision while improving alarm reliability.
3Adaptability or versatility
If the system uses fixed alarm parameters, then the device complexity is low, but it cannot adapt to different containers and conditions
Solution Approach 1:
The system performs self-learning by automatically monitoring and analyzing temperature patterns specific to each container without requiring manual configuration. The container essentially teaches the system its normal operating patterns, enabling adaptability while keeping the user interface simple.
Solution Approach 2:
The system implements a preliminary learning phase where it collects and analyzes temperature data to establish baseline patterns for the specific container and environment. This preliminary adaptation enables the system to handle different containers automatically without complex setup procedures.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system improves temperature control accuracy, reduces false alarms, and ensures that products are stored within safe temperature ranges, enhancing operational reliability and user confidence.
Implementation Method 1
the temperature control hardware comprises one or more temperature sensors communicably coupled to the one or more processors and positioned to sense a temperature within the container
Data Source
AI summary
A smart temperature control system is disclosed. The smart temperature control system includes processing circuitry and a temperature control device. The temperature control device includes a container configured to store a product and temperature control hardware configured to control a temperature within the container. The processing circuitry includes one or more processors configured to monitor the temperature cycles within the container, determine a duration of at least portions of each temperature cycle over a time period, determine a selected time value based on the duration of the portions of each temperature cycle, and update a time limit variable with the selected time value.