Portable Vehicle Temperature Prediction System
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Solution Overview
Problem
Existing temperature monitoring systems in vehicles are not effective in predicting and preventing dangerous interior temperatures, especially when the engine is turned off, as they do not consider various factors such as interior and exterior colors, sunlight exposure, vehicle shape and size, and other environmental conditions, leading to potential harm to occupants or pets.
Innovation Solution
A mobile Early Warning Forecasting System that uses a combination of sensors, processors, and communication modules to monitor and predict interior vehicle temperatures, incorporating regression algorithms and fuzzy logic to analyze weather, GPS location, and vehicle features, and can send alerts or take action to prevent unsafe conditions, operating autonomously and transferable between vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If temperature sensors are integrated into vehicles, then temperature monitoring is available, but each vehicle incurs additional expense and sensors cannot be shared between vehicles
Solution Approach 1:
The monitoring system is designed as a universal device that can be installed in multiple vehicles rather than being integrated into a single vehicle. The system includes temperature sensors, processors, and communication modules that can monitor interior temperatures across different vehicles, allowing one system to serve multiple purposes and locations.
Solution Approach 2:
A portable monitoring device serves as an intermediary between the vehicle environment and the user. This standalone device contains all necessary components (sensors, processors, power supply) to independently monitor temperature conditions and communicate warnings without being permanently integrated into the vehicle structure.
2Measurement precision
If embedded temperature sensors are used, then temperature can be displayed when engine is on, but monitoring stops when engine is turned off
Solution Approach 1:
The monitoring system is self-powered with its own power supply (battery or solar panel) independent of the vehicle's engine or electrical system. This allows the device to autonomously monitor temperature conditions even when the vehicle is parked and the engine is off, eliminating dependency on the vehicle's power system.
Solution Approach 2:
The system continuously monitors temperature conditions beyond what is necessary for normal operation, specifically maintaining monitoring during parking conditions when other systems would be inactive. This excessive monitoring ensures safety during the vulnerable period when vehicles are parked and engines are off.
3Device complexity
If threshold-based warning systems are used, then simple alerting is achieved, but warnings are not timely as dangerous temperatures are already reached
Solution Approach 1:
The system performs preliminary calculations using regression algorithms to predict when dangerous temperatures will be reached inside the vehicle. By analyzing current temperature, environmental conditions, vehicle characteristics, and historical data, the system forecasts future temperature conditions and issues warnings before dangerous levels are achieved, providing timely alerting.
Solution Approach 2:
The system uses feedback from multiple sensors (temperature, environmental conditions) and continuously updates predictions using regression algorithms. This feedback loop allows the system to refine its forecasts and adjust warnings based on actual temperature trends and changing conditions, improving both timing and accuracy of alerts.
4Measurement precision
If comprehensive factors are considered for accurate prediction, then prediction accuracy improves, but system complexity increases
Solution Approach 1:
The system changes parameters by using regression algorithms that process multiple input variables (current temperature, environmental temperature, humidity, vehicle color, size, shape, tinted windows) to predict future temperature conditions. These mathematical transformations convert complex multi-factor data into accurate temperature forecasts without requiring physically complex measurement devices.
Solution Approach 2:
The system replaces complex mechanical sensing devices with computational methods. Instead of using sophisticated physical sensors to directly measure predicted temperature, the system uses processors running regression algorithms that calculate future temperatures based on current measurements and environmental factors, substituting mechanical complexity with computational processing.
Data Source
AI summary
The present invention comprises a system or method that collects data regarding the current and predicted weather in the proximity of a targeted vehicle and compares it with aspects of the targeted vehicle comprising the temperature in the passenger compartment, its geographical location, features, interior and exterior colors, size, whether its parked in a shaded area, etc. The system or method also comprises a regression function that may predict the time that a person, animal, or food product may remain in the vehicle in a safe condition. For example, under certain weather conditions, it may not be safe to keep a dog inside of a parked vehicle for more than four minutes. In addition, the system or method may collect and analyze additional factors based on previously collected data for the same vehicle models, and may comprise a prediction unit that may exchange information with other devices over communication protocols.